diff options
Diffstat (limited to 'runtimes/tests/neural_networks_test/generated')
183 files changed, 6860 insertions, 14 deletions
diff --git a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp index 4dc3d5935..e163b602f 100644 --- a/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp +++ b/runtimes/tests/neural_networks_test/generated/all_generated_tests.cpp @@ -1,5 +1,5 @@ // DO NOT EDIT; -// Generated by ml/nn/runtime/test/specs/generate_test.sh +// Generated by nnfw/runtimes/tests/neural_networks_test/specs/generate_test.sh namespace add_broadcast_quant8 { std::vector<MixedTypedExample> examples = { @@ -57,6 +57,20 @@ TEST_F(GeneratedTests, avg_pool_float_1) { avg_pool_float_1::examples); } +namespace avg_pool_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated avg_pool_float_2 test +#include "generated/examples/avg_pool_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/avg_pool_float_2.model.cpp" +} // namespace avg_pool_float_2 +TEST_F(GeneratedTests, avg_pool_float_2) { + execute(avg_pool_float_2::CreateModel, + avg_pool_float_2::is_ignored, + avg_pool_float_2::examples); +} + namespace avg_pool_float_3 { std::vector<MixedTypedExample> examples = { // Generated avg_pool_float_3 test @@ -71,6 +85,20 @@ TEST_F(GeneratedTests, avg_pool_float_3) { avg_pool_float_3::examples); } +namespace avg_pool_float_4 { +std::vector<MixedTypedExample> examples = { +// Generated avg_pool_float_4 test +#include "generated/examples/avg_pool_float_4.example.cpp" +}; +// Generated model constructor +#include "generated/models/avg_pool_float_4.model.cpp" +} // namespace avg_pool_float_4 +TEST_F(GeneratedTests, avg_pool_float_4) { + execute(avg_pool_float_4::CreateModel, + avg_pool_float_4::is_ignored, + avg_pool_float_4::examples); +} + namespace avg_pool_float_5 { std::vector<MixedTypedExample> examples = { // Generated avg_pool_float_5 test @@ -155,6 +183,62 @@ TEST_F(GeneratedTests, avg_pool_quant8_5) { avg_pool_quant8_5::examples); } +namespace concat_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated concat_float_1 test +#include "generated/examples/concat_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/concat_float_1.model.cpp" +} // namespace concat_float_1 +TEST_F(GeneratedTests, concat_float_1) { + execute(concat_float_1::CreateModel, + concat_float_1::is_ignored, + concat_float_1::examples); +} + +namespace concat_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated concat_float_2 test +#include "generated/examples/concat_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/concat_float_2.model.cpp" +} // namespace concat_float_2 +TEST_F(GeneratedTests, concat_float_2) { + execute(concat_float_2::CreateModel, + concat_float_2::is_ignored, + concat_float_2::examples); +} + +namespace concat_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated concat_float_3 test +#include "generated/examples/concat_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/concat_float_3.model.cpp" +} // namespace concat_float_3 +TEST_F(GeneratedTests, concat_float_3) { + execute(concat_float_3::CreateModel, + concat_float_3::is_ignored, + concat_float_3::examples); +} + +namespace concat_float_4D_axis3_1_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated concat_float_4D_axis3_1_nnfw test +#include "generated/examples/concat_float_4D_axis3_1_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/concat_float_4D_axis3_1_nnfw.model.cpp" +} // namespace concat_float_4D_axis3_1_nnfw +TEST_F(GeneratedTests, concat_float_4D_axis3_1_nnfw) { + execute(concat_float_4D_axis3_1_nnfw::CreateModel, + concat_float_4D_axis3_1_nnfw::is_ignored, + concat_float_4D_axis3_1_nnfw::examples); +} + namespace concat_quant8_1 { std::vector<MixedTypedExample> examples = { // Generated concat_quant8_1 test @@ -477,6 +561,76 @@ TEST_F(GeneratedTests, conv_quant8_weights_as_inputs) { conv_quant8_weights_as_inputs::examples); } +namespace depth_to_space_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated depth_to_space_float_1 test +#include "generated/examples/depth_to_space_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/depth_to_space_float_1.model.cpp" +} // namespace depth_to_space_float_1 +TEST_F(GeneratedTests, depth_to_space_float_1) { + execute(depth_to_space_float_1::CreateModel, + depth_to_space_float_1::is_ignored, + depth_to_space_float_1::examples); +} + +namespace depth_to_space_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated depth_to_space_float_2 test +#include "generated/examples/depth_to_space_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/depth_to_space_float_2.model.cpp" +} // namespace depth_to_space_float_2 +TEST_F(GeneratedTests, depth_to_space_float_2) { + execute(depth_to_space_float_2::CreateModel, + depth_to_space_float_2::is_ignored, + depth_to_space_float_2::examples); +} + +namespace depth_to_space_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated depth_to_space_float_3 test +#include "generated/examples/depth_to_space_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/depth_to_space_float_3.model.cpp" +} // namespace depth_to_space_float_3 +TEST_F(GeneratedTests, depth_to_space_float_3) { + execute(depth_to_space_float_3::CreateModel, + depth_to_space_float_3::is_ignored, + depth_to_space_float_3::examples); +} + +namespace depth_to_space_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated depth_to_space_quant8_1 test +#include "generated/examples/depth_to_space_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/depth_to_space_quant8_1.model.cpp" +} // namespace depth_to_space_quant8_1 +TEST_F(GeneratedTests, depth_to_space_quant8_1) { + execute(depth_to_space_quant8_1::CreateModel, + depth_to_space_quant8_1::is_ignored, + depth_to_space_quant8_1::examples); +} + +namespace depth_to_space_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated depth_to_space_quant8_2 test +#include "generated/examples/depth_to_space_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/depth_to_space_quant8_2.model.cpp" +} // namespace depth_to_space_quant8_2 +TEST_F(GeneratedTests, depth_to_space_quant8_2) { + execute(depth_to_space_quant8_2::CreateModel, + depth_to_space_quant8_2::is_ignored, + depth_to_space_quant8_2::examples); +} + namespace depthwise_conv2d_float_2 { std::vector<MixedTypedExample> examples = { // Generated depthwise_conv2d_float_2 test @@ -575,6 +729,76 @@ TEST_F(GeneratedTests, depthwise_conv2d_float_weights_as_inputs) { depthwise_conv2d_float_weights_as_inputs::examples); } +namespace depthwise_conv2d_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated depthwise_conv2d_quant8_2 test +#include "generated/examples/depthwise_conv2d_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/depthwise_conv2d_quant8_2.model.cpp" +} // namespace depthwise_conv2d_quant8_2 +TEST_F(GeneratedTests, depthwise_conv2d_quant8_2) { + execute(depthwise_conv2d_quant8_2::CreateModel, + depthwise_conv2d_quant8_2::is_ignored, + depthwise_conv2d_quant8_2::examples); +} + +namespace depthwise_conv2d_quant8_large { +std::vector<MixedTypedExample> examples = { +// Generated depthwise_conv2d_quant8_large test +#include "generated/examples/depthwise_conv2d_quant8_large.example.cpp" +}; +// Generated model constructor +#include "generated/models/depthwise_conv2d_quant8_large.model.cpp" +} // namespace depthwise_conv2d_quant8_large +TEST_F(GeneratedTests, depthwise_conv2d_quant8_large) { + execute(depthwise_conv2d_quant8_large::CreateModel, + depthwise_conv2d_quant8_large::is_ignored, + depthwise_conv2d_quant8_large::examples); +} + +namespace depthwise_conv2d_quant8_large_weights_as_inputs { +std::vector<MixedTypedExample> examples = { +// Generated depthwise_conv2d_quant8_large_weights_as_inputs test +#include "generated/examples/depthwise_conv2d_quant8_large_weights_as_inputs.example.cpp" +}; +// Generated model constructor +#include "generated/models/depthwise_conv2d_quant8_large_weights_as_inputs.model.cpp" +} // namespace depthwise_conv2d_quant8_large_weights_as_inputs +TEST_F(GeneratedTests, depthwise_conv2d_quant8_large_weights_as_inputs) { + execute(depthwise_conv2d_quant8_large_weights_as_inputs::CreateModel, + depthwise_conv2d_quant8_large_weights_as_inputs::is_ignored, + depthwise_conv2d_quant8_large_weights_as_inputs::examples); +} + +namespace depthwise_conv2d_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated depthwise_conv2d_quant8 test +#include "generated/examples/depthwise_conv2d_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/depthwise_conv2d_quant8.model.cpp" +} // namespace depthwise_conv2d_quant8 +TEST_F(GeneratedTests, depthwise_conv2d_quant8) { + execute(depthwise_conv2d_quant8::CreateModel, + depthwise_conv2d_quant8::is_ignored, + depthwise_conv2d_quant8::examples); +} + +namespace depthwise_conv2d_quant8_weights_as_inputs { +std::vector<MixedTypedExample> examples = { +// Generated depthwise_conv2d_quant8_weights_as_inputs test +#include "generated/examples/depthwise_conv2d_quant8_weights_as_inputs.example.cpp" +}; +// Generated model constructor +#include "generated/models/depthwise_conv2d_quant8_weights_as_inputs.model.cpp" +} // namespace depthwise_conv2d_quant8_weights_as_inputs +TEST_F(GeneratedTests, depthwise_conv2d_quant8_weights_as_inputs) { + execute(depthwise_conv2d_quant8_weights_as_inputs::CreateModel, + depthwise_conv2d_quant8_weights_as_inputs::is_ignored, + depthwise_conv2d_quant8_weights_as_inputs::examples); +} + namespace depthwise_conv { std::vector<MixedTypedExample> examples = { // Generated depthwise_conv test @@ -589,6 +813,90 @@ TEST_F(GeneratedTests, depthwise_conv) { depthwise_conv::examples); } +namespace dequantize { +std::vector<MixedTypedExample> examples = { +// Generated dequantize test +#include "generated/examples/dequantize.example.cpp" +}; +// Generated model constructor +#include "generated/models/dequantize.model.cpp" +} // namespace dequantize +TEST_F(GeneratedTests, dequantize) { + execute(dequantize::CreateModel, + dequantize::is_ignored, + dequantize::examples); +} + +namespace embedding_lookup_2d_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated embedding_lookup_2d_nnfw test +#include "generated/examples/embedding_lookup_2d_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/embedding_lookup_2d_nnfw.model.cpp" +} // namespace embedding_lookup_2d_nnfw +TEST_F(GeneratedTests, embedding_lookup_2d_nnfw) { + execute(embedding_lookup_2d_nnfw::CreateModel, + embedding_lookup_2d_nnfw::is_ignored, + embedding_lookup_2d_nnfw::examples); +} + +namespace embedding_lookup_4d_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated embedding_lookup_4d_nnfw test +#include "generated/examples/embedding_lookup_4d_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/embedding_lookup_4d_nnfw.model.cpp" +} // namespace embedding_lookup_4d_nnfw +TEST_F(GeneratedTests, embedding_lookup_4d_nnfw) { + execute(embedding_lookup_4d_nnfw::CreateModel, + embedding_lookup_4d_nnfw::is_ignored, + embedding_lookup_4d_nnfw::examples); +} + +namespace embedding_lookup { +std::vector<MixedTypedExample> examples = { +// Generated embedding_lookup test +#include "generated/examples/embedding_lookup.example.cpp" +}; +// Generated model constructor +#include "generated/models/embedding_lookup.model.cpp" +} // namespace embedding_lookup +TEST_F(GeneratedTests, embedding_lookup) { + execute(embedding_lookup::CreateModel, + embedding_lookup::is_ignored, + embedding_lookup::examples); +} + +namespace floor_ { +std::vector<MixedTypedExample> examples = { +// Generated floor_ test +#include "generated/examples/floor_.example.cpp" +}; +// Generated model constructor +#include "generated/models/floor_.model.cpp" +} // namespace floor_ +TEST_F(GeneratedTests, floor_) { + execute(floor_::CreateModel, + floor_::is_ignored, + floor_::examples); +} + +namespace fully_connected_float_1_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated fully_connected_float_1_nnfw test +#include "generated/examples/fully_connected_float_1_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/fully_connected_float_1_nnfw.model.cpp" +} // namespace fully_connected_float_1_nnfw +TEST_F(GeneratedTests, fully_connected_float_1_nnfw) { + execute(fully_connected_float_1_nnfw::CreateModel, + fully_connected_float_1_nnfw::is_ignored, + fully_connected_float_1_nnfw::examples); +} + namespace fully_connected_float_2 { std::vector<MixedTypedExample> examples = { // Generated fully_connected_float_2 test @@ -603,6 +911,20 @@ TEST_F(GeneratedTests, fully_connected_float_2) { fully_connected_float_2::examples); } +namespace fully_connected_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated fully_connected_float_3 test +#include "generated/examples/fully_connected_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/fully_connected_float_3.model.cpp" +} // namespace fully_connected_float_3 +TEST_F(GeneratedTests, fully_connected_float_3) { + execute(fully_connected_float_3::CreateModel, + fully_connected_float_3::is_ignored, + fully_connected_float_3::examples); +} + namespace fully_connected_float_large { std::vector<MixedTypedExample> examples = { // Generated fully_connected_float_large test @@ -729,6 +1051,412 @@ TEST_F(GeneratedTests, fully_connected_quant8_weights_as_inputs) { fully_connected_quant8_weights_as_inputs::examples); } +namespace hashtable_lookup_float { +std::vector<MixedTypedExample> examples = { +// Generated hashtable_lookup_float test +#include "generated/examples/hashtable_lookup_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/hashtable_lookup_float.model.cpp" +} // namespace hashtable_lookup_float +TEST_F(GeneratedTests, hashtable_lookup_float) { + execute(hashtable_lookup_float::CreateModel, + hashtable_lookup_float::is_ignored, + hashtable_lookup_float::examples); +} + +namespace hashtable_lookup_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated hashtable_lookup_quant8 test +#include "generated/examples/hashtable_lookup_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/hashtable_lookup_quant8.model.cpp" +} // namespace hashtable_lookup_quant8 +TEST_F(GeneratedTests, hashtable_lookup_quant8) { + execute(hashtable_lookup_quant8::CreateModel, + hashtable_lookup_quant8::is_ignored, + hashtable_lookup_quant8::examples); +} + +namespace l2_normalization_2 { +std::vector<MixedTypedExample> examples = { +// Generated l2_normalization_2 test +#include "generated/examples/l2_normalization_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_normalization_2.model.cpp" +} // namespace l2_normalization_2 +TEST_F(GeneratedTests, l2_normalization_2) { + execute(l2_normalization_2::CreateModel, + l2_normalization_2::is_ignored, + l2_normalization_2::examples); +} + +namespace l2_normalization_large { +std::vector<MixedTypedExample> examples = { +// Generated l2_normalization_large test +#include "generated/examples/l2_normalization_large.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_normalization_large.model.cpp" +} // namespace l2_normalization_large +TEST_F(GeneratedTests, l2_normalization_large) { + execute(l2_normalization_large::CreateModel, + l2_normalization_large::is_ignored, + l2_normalization_large::examples); +} + +namespace l2_normalization { +std::vector<MixedTypedExample> examples = { +// Generated l2_normalization test +#include "generated/examples/l2_normalization.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_normalization.model.cpp" +} // namespace l2_normalization +TEST_F(GeneratedTests, l2_normalization) { + execute(l2_normalization::CreateModel, + l2_normalization::is_ignored, + l2_normalization::examples); +} + +namespace l2_pool_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated l2_pool_float_2 test +#include "generated/examples/l2_pool_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_pool_float_2.model.cpp" +} // namespace l2_pool_float_2 +TEST_F(GeneratedTests, l2_pool_float_2) { + execute(l2_pool_float_2::CreateModel, + l2_pool_float_2::is_ignored, + l2_pool_float_2::examples); +} + +namespace l2_pool_float_large { +std::vector<MixedTypedExample> examples = { +// Generated l2_pool_float_large test +#include "generated/examples/l2_pool_float_large.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_pool_float_large.model.cpp" +} // namespace l2_pool_float_large +TEST_F(GeneratedTests, l2_pool_float_large) { + execute(l2_pool_float_large::CreateModel, + l2_pool_float_large::is_ignored, + l2_pool_float_large::examples); +} + +namespace l2_pool_float { +std::vector<MixedTypedExample> examples = { +// Generated l2_pool_float test +#include "generated/examples/l2_pool_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/l2_pool_float.model.cpp" +} // namespace l2_pool_float +TEST_F(GeneratedTests, l2_pool_float) { + execute(l2_pool_float::CreateModel, + l2_pool_float::is_ignored, + l2_pool_float::examples); +} + +namespace local_response_norm_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated local_response_norm_float_1 test +#include "generated/examples/local_response_norm_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/local_response_norm_float_1.model.cpp" +} // namespace local_response_norm_float_1 +TEST_F(GeneratedTests, local_response_norm_float_1) { + execute(local_response_norm_float_1::CreateModel, + local_response_norm_float_1::is_ignored, + local_response_norm_float_1::examples); +} + +namespace local_response_norm_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated local_response_norm_float_2 test +#include "generated/examples/local_response_norm_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/local_response_norm_float_2.model.cpp" +} // namespace local_response_norm_float_2 +TEST_F(GeneratedTests, local_response_norm_float_2) { + execute(local_response_norm_float_2::CreateModel, + local_response_norm_float_2::is_ignored, + local_response_norm_float_2::examples); +} + +namespace local_response_norm_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated local_response_norm_float_3 test +#include "generated/examples/local_response_norm_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/local_response_norm_float_3.model.cpp" +} // namespace local_response_norm_float_3 +TEST_F(GeneratedTests, local_response_norm_float_3) { + execute(local_response_norm_float_3::CreateModel, + local_response_norm_float_3::is_ignored, + local_response_norm_float_3::examples); +} + +namespace local_response_norm_float_4 { +std::vector<MixedTypedExample> examples = { +// Generated local_response_norm_float_4 test +#include "generated/examples/local_response_norm_float_4.example.cpp" +}; +// Generated model constructor +#include "generated/models/local_response_norm_float_4.model.cpp" +} // namespace local_response_norm_float_4 +TEST_F(GeneratedTests, local_response_norm_float_4) { + execute(local_response_norm_float_4::CreateModel, + local_response_norm_float_4::is_ignored, + local_response_norm_float_4::examples); +} + +namespace logistic_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated logistic_float_1 test +#include "generated/examples/logistic_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/logistic_float_1.model.cpp" +} // namespace logistic_float_1 +TEST_F(GeneratedTests, logistic_float_1) { + execute(logistic_float_1::CreateModel, + logistic_float_1::is_ignored, + logistic_float_1::examples); +} + +namespace logistic_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated logistic_float_2 test +#include "generated/examples/logistic_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/logistic_float_2.model.cpp" +} // namespace logistic_float_2 +TEST_F(GeneratedTests, logistic_float_2) { + execute(logistic_float_2::CreateModel, + logistic_float_2::is_ignored, + logistic_float_2::examples); +} + +namespace logistic_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated logistic_quant8_1 test +#include "generated/examples/logistic_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/logistic_quant8_1.model.cpp" +} // namespace logistic_quant8_1 +TEST_F(GeneratedTests, logistic_quant8_1) { + execute(logistic_quant8_1::CreateModel, + logistic_quant8_1::is_ignored, + logistic_quant8_1::examples); +} + +namespace logistic_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated logistic_quant8_2 test +#include "generated/examples/logistic_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/logistic_quant8_2.model.cpp" +} // namespace logistic_quant8_2 +TEST_F(GeneratedTests, logistic_quant8_2) { + execute(logistic_quant8_2::CreateModel, + logistic_quant8_2::is_ignored, + logistic_quant8_2::examples); +} + +namespace lsh_projection_2 { +std::vector<MixedTypedExample> examples = { +// Generated lsh_projection_2 test +#include "generated/examples/lsh_projection_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/lsh_projection_2.model.cpp" +} // namespace lsh_projection_2 +TEST_F(GeneratedTests, lsh_projection_2) { + execute(lsh_projection_2::CreateModel, + lsh_projection_2::is_ignored, + lsh_projection_2::examples); +} + +namespace lsh_projection { +std::vector<MixedTypedExample> examples = { +// Generated lsh_projection test +#include "generated/examples/lsh_projection.example.cpp" +}; +// Generated model constructor +#include "generated/models/lsh_projection.model.cpp" +} // namespace lsh_projection +TEST_F(GeneratedTests, lsh_projection) { + execute(lsh_projection::CreateModel, + lsh_projection::is_ignored, + lsh_projection::examples); +} + +namespace lsh_projection_weights_as_inputs { +std::vector<MixedTypedExample> examples = { +// Generated lsh_projection_weights_as_inputs test +#include "generated/examples/lsh_projection_weights_as_inputs.example.cpp" +}; +// Generated model constructor +#include "generated/models/lsh_projection_weights_as_inputs.model.cpp" +} // namespace lsh_projection_weights_as_inputs +TEST_F(GeneratedTests, lsh_projection_weights_as_inputs) { + execute(lsh_projection_weights_as_inputs::CreateModel, + lsh_projection_weights_as_inputs::is_ignored, + lsh_projection_weights_as_inputs::examples); +} + +namespace lstm2 { +std::vector<MixedTypedExample> examples = { +// Generated lstm2 test +#include "generated/examples/lstm2.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm2.model.cpp" +} // namespace lstm2 +TEST_F(GeneratedTests, lstm2) { + execute(lstm2::CreateModel, + lstm2::is_ignored, + lstm2::examples); +} + +namespace lstm2_state2 { +std::vector<MixedTypedExample> examples = { +// Generated lstm2_state2 test +#include "generated/examples/lstm2_state2.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm2_state2.model.cpp" +} // namespace lstm2_state2 +TEST_F(GeneratedTests, lstm2_state2) { + execute(lstm2_state2::CreateModel, + lstm2_state2::is_ignored, + lstm2_state2::examples); +} + +namespace lstm2_state { +std::vector<MixedTypedExample> examples = { +// Generated lstm2_state test +#include "generated/examples/lstm2_state.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm2_state.model.cpp" +} // namespace lstm2_state +TEST_F(GeneratedTests, lstm2_state) { + execute(lstm2_state::CreateModel, + lstm2_state::is_ignored, + lstm2_state::examples); +} + +namespace lstm3 { +std::vector<MixedTypedExample> examples = { +// Generated lstm3 test +#include "generated/examples/lstm3.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm3.model.cpp" +} // namespace lstm3 +TEST_F(GeneratedTests, lstm3) { + execute(lstm3::CreateModel, + lstm3::is_ignored, + lstm3::examples); +} + +namespace lstm3_state2 { +std::vector<MixedTypedExample> examples = { +// Generated lstm3_state2 test +#include "generated/examples/lstm3_state2.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm3_state2.model.cpp" +} // namespace lstm3_state2 +TEST_F(GeneratedTests, lstm3_state2) { + execute(lstm3_state2::CreateModel, + lstm3_state2::is_ignored, + lstm3_state2::examples); +} + +namespace lstm3_state3 { +std::vector<MixedTypedExample> examples = { +// Generated lstm3_state3 test +#include "generated/examples/lstm3_state3.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm3_state3.model.cpp" +} // namespace lstm3_state3 +TEST_F(GeneratedTests, lstm3_state3) { + execute(lstm3_state3::CreateModel, + lstm3_state3::is_ignored, + lstm3_state3::examples); +} + +namespace lstm3_state { +std::vector<MixedTypedExample> examples = { +// Generated lstm3_state test +#include "generated/examples/lstm3_state.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm3_state.model.cpp" +} // namespace lstm3_state +TEST_F(GeneratedTests, lstm3_state) { + execute(lstm3_state::CreateModel, + lstm3_state::is_ignored, + lstm3_state::examples); +} + +namespace lstm { +std::vector<MixedTypedExample> examples = { +// Generated lstm test +#include "generated/examples/lstm.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm.model.cpp" +} // namespace lstm +TEST_F(GeneratedTests, lstm) { + execute(lstm::CreateModel, + lstm::is_ignored, + lstm::examples); +} + +namespace lstm_state2 { +std::vector<MixedTypedExample> examples = { +// Generated lstm_state2 test +#include "generated/examples/lstm_state2.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm_state2.model.cpp" +} // namespace lstm_state2 +TEST_F(GeneratedTests, lstm_state2) { + execute(lstm_state2::CreateModel, + lstm_state2::is_ignored, + lstm_state2::examples); +} + +namespace lstm_state { +std::vector<MixedTypedExample> examples = { +// Generated lstm_state test +#include "generated/examples/lstm_state.example.cpp" +}; +// Generated model constructor +#include "generated/models/lstm_state.model.cpp" +} // namespace lstm_state +TEST_F(GeneratedTests, lstm_state) { + execute(lstm_state::CreateModel, + lstm_state::is_ignored, + lstm_state::examples); +} + namespace max_pool_float_1 { std::vector<MixedTypedExample> examples = { // Generated max_pool_float_1 test @@ -743,6 +1471,34 @@ TEST_F(GeneratedTests, max_pool_float_1) { max_pool_float_1::examples); } +namespace max_pool_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated max_pool_float_2 test +#include "generated/examples/max_pool_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/max_pool_float_2.model.cpp" +} // namespace max_pool_float_2 +TEST_F(GeneratedTests, max_pool_float_2) { + execute(max_pool_float_2::CreateModel, + max_pool_float_2::is_ignored, + max_pool_float_2::examples); +} + +namespace max_pool_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated max_pool_float_3 test +#include "generated/examples/max_pool_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/max_pool_float_3.model.cpp" +} // namespace max_pool_float_3 +TEST_F(GeneratedTests, max_pool_float_3) { + execute(max_pool_float_3::CreateModel, + max_pool_float_3::is_ignored, + max_pool_float_3::examples); +} + namespace max_pool_float_4 { std::vector<MixedTypedExample> examples = { // Generated max_pool_float_4 test @@ -813,6 +1569,62 @@ TEST_F(GeneratedTests, max_pool_quant8_4) { max_pool_quant8_4::examples); } +namespace mobilenet_224_gender_basic_fixed { +std::vector<MixedTypedExample> examples = { +// Generated mobilenet_224_gender_basic_fixed test +#include "generated/examples/mobilenet_224_gender_basic_fixed.example.cpp" +}; +// Generated model constructor +#include "generated/models/mobilenet_224_gender_basic_fixed.model.cpp" +} // namespace mobilenet_224_gender_basic_fixed +TEST_F(GeneratedTests, mobilenet_224_gender_basic_fixed) { + execute(mobilenet_224_gender_basic_fixed::CreateModel, + mobilenet_224_gender_basic_fixed::is_ignored, + mobilenet_224_gender_basic_fixed::examples); +} + +namespace mobilenet_quantized { +std::vector<MixedTypedExample> examples = { +// Generated mobilenet_quantized test +#include "generated/examples/mobilenet_quantized.example.cpp" +}; +// Generated model constructor +#include "generated/models/mobilenet_quantized.model.cpp" +} // namespace mobilenet_quantized +TEST_F(GeneratedTests, mobilenet_quantized) { + execute(mobilenet_quantized::CreateModel, + mobilenet_quantized::is_ignored, + mobilenet_quantized::examples); +} + +namespace mul_broadcast_3D_1D_1_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated mul_broadcast_3D_1D_1_nnfw test +#include "generated/examples/mul_broadcast_3D_1D_1_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp" +} // namespace mul_broadcast_3D_1D_1_nnfw +TEST_F(GeneratedTests, mul_broadcast_3D_1D_1_nnfw) { + execute(mul_broadcast_3D_1D_1_nnfw::CreateModel, + mul_broadcast_3D_1D_1_nnfw::is_ignored, + mul_broadcast_3D_1D_1_nnfw::examples); +} + +namespace mul_broadcast_3D_1D_2_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated mul_broadcast_3D_1D_2_nnfw test +#include "generated/examples/mul_broadcast_3D_1D_2_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp" +} // namespace mul_broadcast_3D_1D_2_nnfw +TEST_F(GeneratedTests, mul_broadcast_3D_1D_2_nnfw) { + execute(mul_broadcast_3D_1D_2_nnfw::CreateModel, + mul_broadcast_3D_1D_2_nnfw::is_ignored, + mul_broadcast_3D_1D_2_nnfw::examples); +} + namespace mul_broadcast_quant8 { std::vector<MixedTypedExample> examples = { // Generated mul_broadcast_quant8 test @@ -869,6 +1681,62 @@ TEST_F(GeneratedTests, mul_relu) { mul_relu::examples); } +namespace relu1_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated relu1_float_1 test +#include "generated/examples/relu1_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu1_float_1.model.cpp" +} // namespace relu1_float_1 +TEST_F(GeneratedTests, relu1_float_1) { + execute(relu1_float_1::CreateModel, + relu1_float_1::is_ignored, + relu1_float_1::examples); +} + +namespace relu1_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated relu1_float_2 test +#include "generated/examples/relu1_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu1_float_2.model.cpp" +} // namespace relu1_float_2 +TEST_F(GeneratedTests, relu1_float_2) { + execute(relu1_float_2::CreateModel, + relu1_float_2::is_ignored, + relu1_float_2::examples); +} + +namespace relu1_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated relu1_quant8_1 test +#include "generated/examples/relu1_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu1_quant8_1.model.cpp" +} // namespace relu1_quant8_1 +TEST_F(GeneratedTests, relu1_quant8_1) { + execute(relu1_quant8_1::CreateModel, + relu1_quant8_1::is_ignored, + relu1_quant8_1::examples); +} + +namespace relu1_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated relu1_quant8_2 test +#include "generated/examples/relu1_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu1_quant8_2.model.cpp" +} // namespace relu1_quant8_2 +TEST_F(GeneratedTests, relu1_quant8_2) { + execute(relu1_quant8_2::CreateModel, + relu1_quant8_2::is_ignored, + relu1_quant8_2::examples); +} + namespace relu6_float_1 { std::vector<MixedTypedExample> examples = { // Generated relu6_float_1 test @@ -925,6 +1793,62 @@ TEST_F(GeneratedTests, relu6_quant8_2) { relu6_quant8_2::examples); } +namespace relu_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated relu_float_1 test +#include "generated/examples/relu_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu_float_1.model.cpp" +} // namespace relu_float_1 +TEST_F(GeneratedTests, relu_float_1) { + execute(relu_float_1::CreateModel, + relu_float_1::is_ignored, + relu_float_1::examples); +} + +namespace relu_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated relu_float_2 test +#include "generated/examples/relu_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu_float_2.model.cpp" +} // namespace relu_float_2 +TEST_F(GeneratedTests, relu_float_2) { + execute(relu_float_2::CreateModel, + relu_float_2::is_ignored, + relu_float_2::examples); +} + +namespace relu_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated relu_quant8_1 test +#include "generated/examples/relu_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu_quant8_1.model.cpp" +} // namespace relu_quant8_1 +TEST_F(GeneratedTests, relu_quant8_1) { + execute(relu_quant8_1::CreateModel, + relu_quant8_1::is_ignored, + relu_quant8_1::examples); +} + +namespace relu_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated relu_quant8_2 test +#include "generated/examples/relu_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/relu_quant8_2.model.cpp" +} // namespace relu_quant8_2 +TEST_F(GeneratedTests, relu_quant8_2) { + execute(relu_quant8_2::CreateModel, + relu_quant8_2::is_ignored, + relu_quant8_2::examples); +} + namespace reshape { std::vector<MixedTypedExample> examples = { // Generated reshape test @@ -981,6 +1905,62 @@ TEST_F(GeneratedTests, reshape_weights_as_inputs) { reshape_weights_as_inputs::examples); } +namespace resize_bilinear_2 { +std::vector<MixedTypedExample> examples = { +// Generated resize_bilinear_2 test +#include "generated/examples/resize_bilinear_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/resize_bilinear_2.model.cpp" +} // namespace resize_bilinear_2 +TEST_F(GeneratedTests, resize_bilinear_2) { + execute(resize_bilinear_2::CreateModel, + resize_bilinear_2::is_ignored, + resize_bilinear_2::examples); +} + +namespace resize_bilinear { +std::vector<MixedTypedExample> examples = { +// Generated resize_bilinear test +#include "generated/examples/resize_bilinear.example.cpp" +}; +// Generated model constructor +#include "generated/models/resize_bilinear.model.cpp" +} // namespace resize_bilinear +TEST_F(GeneratedTests, resize_bilinear) { + execute(resize_bilinear::CreateModel, + resize_bilinear::is_ignored, + resize_bilinear::examples); +} + +namespace rnn { +std::vector<MixedTypedExample> examples = { +// Generated rnn test +#include "generated/examples/rnn.example.cpp" +}; +// Generated model constructor +#include "generated/models/rnn.model.cpp" +} // namespace rnn +TEST_F(GeneratedTests, rnn) { + execute(rnn::CreateModel, + rnn::is_ignored, + rnn::examples); +} + +namespace rnn_state { +std::vector<MixedTypedExample> examples = { +// Generated rnn_state test +#include "generated/examples/rnn_state.example.cpp" +}; +// Generated model constructor +#include "generated/models/rnn_state.model.cpp" +} // namespace rnn_state +TEST_F(GeneratedTests, rnn_state) { + execute(rnn_state::CreateModel, + rnn_state::is_ignored, + rnn_state::examples); +} + namespace softmax_float_1 { std::vector<MixedTypedExample> examples = { // Generated softmax_float_1 test @@ -995,6 +1975,20 @@ TEST_F(GeneratedTests, softmax_float_1) { softmax_float_1::examples); } +namespace softmax_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated softmax_float_2 test +#include "generated/examples/softmax_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/softmax_float_2.model.cpp" +} // namespace softmax_float_2 +TEST_F(GeneratedTests, softmax_float_2) { + execute(softmax_float_2::CreateModel, + softmax_float_2::is_ignored, + softmax_float_2::examples); +} + namespace softmax_quant8_1 { std::vector<MixedTypedExample> examples = { // Generated softmax_quant8_1 test @@ -1023,3 +2017,1108 @@ TEST_F(GeneratedTests, softmax_quant8_2) { softmax_quant8_2::examples); } +namespace space_to_depth_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_depth_float_1 test +#include "generated/examples/space_to_depth_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_depth_float_1.model.cpp" +} // namespace space_to_depth_float_1 +TEST_F(GeneratedTests, space_to_depth_float_1) { + execute(space_to_depth_float_1::CreateModel, + space_to_depth_float_1::is_ignored, + space_to_depth_float_1::examples); +} + +namespace space_to_depth_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_depth_float_2 test +#include "generated/examples/space_to_depth_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_depth_float_2.model.cpp" +} // namespace space_to_depth_float_2 +TEST_F(GeneratedTests, space_to_depth_float_2) { + execute(space_to_depth_float_2::CreateModel, + space_to_depth_float_2::is_ignored, + space_to_depth_float_2::examples); +} + +namespace space_to_depth_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_depth_float_3 test +#include "generated/examples/space_to_depth_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_depth_float_3.model.cpp" +} // namespace space_to_depth_float_3 +TEST_F(GeneratedTests, space_to_depth_float_3) { + execute(space_to_depth_float_3::CreateModel, + space_to_depth_float_3::is_ignored, + space_to_depth_float_3::examples); +} + +namespace space_to_depth_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_depth_quant8_1 test +#include "generated/examples/space_to_depth_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_depth_quant8_1.model.cpp" +} // namespace space_to_depth_quant8_1 +TEST_F(GeneratedTests, space_to_depth_quant8_1) { + execute(space_to_depth_quant8_1::CreateModel, + space_to_depth_quant8_1::is_ignored, + space_to_depth_quant8_1::examples); +} + +namespace space_to_depth_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_depth_quant8_2 test +#include "generated/examples/space_to_depth_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_depth_quant8_2.model.cpp" +} // namespace space_to_depth_quant8_2 +TEST_F(GeneratedTests, space_to_depth_quant8_2) { + execute(space_to_depth_quant8_2::CreateModel, + space_to_depth_quant8_2::is_ignored, + space_to_depth_quant8_2::examples); +} + +namespace svdf2 { +std::vector<MixedTypedExample> examples = { +// Generated svdf2 test +#include "generated/examples/svdf2.example.cpp" +}; +// Generated model constructor +#include "generated/models/svdf2.model.cpp" +} // namespace svdf2 +TEST_F(GeneratedTests, svdf2) { + execute(svdf2::CreateModel, + svdf2::is_ignored, + svdf2::examples); +} + +namespace svdf { +std::vector<MixedTypedExample> examples = { +// Generated svdf test +#include "generated/examples/svdf.example.cpp" +}; +// Generated model constructor +#include "generated/models/svdf.model.cpp" +} // namespace svdf +TEST_F(GeneratedTests, svdf) { + execute(svdf::CreateModel, + svdf::is_ignored, + svdf::examples); +} + +namespace svdf_state { +std::vector<MixedTypedExample> examples = { +// Generated svdf_state test +#include "generated/examples/svdf_state.example.cpp" +}; +// Generated model constructor +#include "generated/models/svdf_state.model.cpp" +} // namespace svdf_state +TEST_F(GeneratedTests, svdf_state) { + execute(svdf_state::CreateModel, + svdf_state::is_ignored, + svdf_state::examples); +} + +namespace tanh_ { +std::vector<MixedTypedExample> examples = { +// Generated tanh_ test +#include "generated/examples/tanh_.example.cpp" +}; +// Generated model constructor +#include "generated/models/tanh_.model.cpp" +} // namespace tanh_ +TEST_F(GeneratedTests, tanh_) { + execute(tanh_::CreateModel, + tanh_::is_ignored, + tanh_::examples); +} + +namespace batch_to_space_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated batch_to_space_float_1 test +#include "generated/examples/batch_to_space_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space_float_1.model.cpp" +} // namespace batch_to_space_float_1 +TEST_F(GeneratedTests, batch_to_space_float_1) { + execute(batch_to_space_float_1::CreateModel, + batch_to_space_float_1::is_ignored, + batch_to_space_float_1::examples); +} + +namespace batch_to_space { +std::vector<MixedTypedExample> examples = { +// Generated batch_to_space test +#include "generated/examples/batch_to_space.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space.model.cpp" +} // namespace batch_to_space +TEST_F(GeneratedTests, batch_to_space) { + execute(batch_to_space::CreateModel, + batch_to_space::is_ignored, + batch_to_space::examples); +} + +namespace batch_to_space_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated batch_to_space_quant8_1 test +#include "generated/examples/batch_to_space_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/batch_to_space_quant8_1.model.cpp" +} // namespace batch_to_space_quant8_1 +TEST_F(GeneratedTests, batch_to_space_quant8_1) { + execute(batch_to_space_quant8_1::CreateModel, + batch_to_space_quant8_1::is_ignored, + batch_to_space_quant8_1::examples); +} + +namespace div_broadcast_float { +std::vector<MixedTypedExample> examples = { +// Generated div_broadcast_float test +#include "generated/examples/div_broadcast_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/div_broadcast_float.model.cpp" +} // namespace div_broadcast_float +TEST_F(GeneratedTests, div_broadcast_float) { + execute(div_broadcast_float::CreateModel, + div_broadcast_float::is_ignored, + div_broadcast_float::examples); +} + +namespace div_ { +std::vector<MixedTypedExample> examples = { +// Generated div_ test +#include "generated/examples/div_.example.cpp" +}; +// Generated model constructor +#include "generated/models/div_.model.cpp" +} // namespace div_ +TEST_F(GeneratedTests, div_) { + execute(div_::CreateModel, + div_::is_ignored, + div_::examples); +} + +namespace fully_connected_float_4d_simple { +std::vector<MixedTypedExample> examples = { +// Generated fully_connected_float_4d_simple test +#include "generated/examples/fully_connected_float_4d_simple.example.cpp" +}; +// Generated model constructor +#include "generated/models/fully_connected_float_4d_simple.model.cpp" +} // namespace fully_connected_float_4d_simple +TEST_F(GeneratedTests, fully_connected_float_4d_simple) { + execute(fully_connected_float_4d_simple::CreateModel, + fully_connected_float_4d_simple::is_ignored, + fully_connected_float_4d_simple::examples); +} + +namespace mean_axis01_1_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated mean_axis01_1_nnfw test +#include "generated/examples/mean_axis01_1_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_axis01_1_nnfw.model.cpp" +} // namespace mean_axis01_1_nnfw +TEST_F(GeneratedTests, mean_axis01_1_nnfw) { + execute(mean_axis01_1_nnfw::CreateModel, + mean_axis01_1_nnfw::is_ignored, + mean_axis01_1_nnfw::examples); +} + +namespace mean_axis01_2_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated mean_axis01_2_nnfw test +#include "generated/examples/mean_axis01_2_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_axis01_2_nnfw.model.cpp" +} // namespace mean_axis01_2_nnfw +TEST_F(GeneratedTests, mean_axis01_2_nnfw) { + execute(mean_axis01_2_nnfw::CreateModel, + mean_axis01_2_nnfw::is_ignored, + mean_axis01_2_nnfw::examples); +} + +namespace mean_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated mean_float_1 test +#include "generated/examples/mean_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_float_1.model.cpp" +} // namespace mean_float_1 +TEST_F(GeneratedTests, mean_float_1) { + execute(mean_float_1::CreateModel, + mean_float_1::is_ignored, + mean_float_1::examples); +} + +namespace mean_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated mean_float_2 test +#include "generated/examples/mean_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_float_2.model.cpp" +} // namespace mean_float_2 +TEST_F(GeneratedTests, mean_float_2) { + execute(mean_float_2::CreateModel, + mean_float_2::is_ignored, + mean_float_2::examples); +} + +namespace mean { +std::vector<MixedTypedExample> examples = { +// Generated mean test +#include "generated/examples/mean.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean.model.cpp" +} // namespace mean +TEST_F(GeneratedTests, mean) { + execute(mean::CreateModel, + mean::is_ignored, + mean::examples); +} + +namespace mean_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated mean_quant8_1 test +#include "generated/examples/mean_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_quant8_1.model.cpp" +} // namespace mean_quant8_1 +TEST_F(GeneratedTests, mean_quant8_1) { + execute(mean_quant8_1::CreateModel, + mean_quant8_1::is_ignored, + mean_quant8_1::examples); +} + +namespace mean_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated mean_quant8_2 test +#include "generated/examples/mean_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/mean_quant8_2.model.cpp" +} // namespace mean_quant8_2 +TEST_F(GeneratedTests, mean_quant8_2) { + execute(mean_quant8_2::CreateModel, + mean_quant8_2::is_ignored, + mean_quant8_2::examples); +} + +namespace pad_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated pad_float_1 test +#include "generated/examples/pad_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/pad_float_1.model.cpp" +} // namespace pad_float_1 +TEST_F(GeneratedTests, pad_float_1) { + execute(pad_float_1::CreateModel, + pad_float_1::is_ignored, + pad_float_1::examples); +} + +namespace pad { +std::vector<MixedTypedExample> examples = { +// Generated pad test +#include "generated/examples/pad.example.cpp" +}; +// Generated model constructor +#include "generated/models/pad.model.cpp" +} // namespace pad +TEST_F(GeneratedTests, pad) { + execute(pad::CreateModel, + pad::is_ignored, + pad::examples); +} + +namespace space_to_batch_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_float_1 test +#include "generated/examples/space_to_batch_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_1.model.cpp" +} // namespace space_to_batch_float_1 +TEST_F(GeneratedTests, space_to_batch_float_1) { + execute(space_to_batch_float_1::CreateModel, + space_to_batch_float_1::is_ignored, + space_to_batch_float_1::examples); +} + +namespace space_to_batch_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_float_2 test +#include "generated/examples/space_to_batch_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_2.model.cpp" +} // namespace space_to_batch_float_2 +TEST_F(GeneratedTests, space_to_batch_float_2) { + execute(space_to_batch_float_2::CreateModel, + space_to_batch_float_2::is_ignored, + space_to_batch_float_2::examples); +} + +namespace space_to_batch_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_float_3 test +#include "generated/examples/space_to_batch_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_float_3.model.cpp" +} // namespace space_to_batch_float_3 +TEST_F(GeneratedTests, space_to_batch_float_3) { + execute(space_to_batch_float_3::CreateModel, + space_to_batch_float_3::is_ignored, + space_to_batch_float_3::examples); +} + +namespace space_to_batch { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch test +#include "generated/examples/space_to_batch.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch.model.cpp" +} // namespace space_to_batch +TEST_F(GeneratedTests, space_to_batch) { + execute(space_to_batch::CreateModel, + space_to_batch::is_ignored, + space_to_batch::examples); +} + +namespace space_to_batch_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_quant8_1 test +#include "generated/examples/space_to_batch_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_1.model.cpp" +} // namespace space_to_batch_quant8_1 +TEST_F(GeneratedTests, space_to_batch_quant8_1) { + execute(space_to_batch_quant8_1::CreateModel, + space_to_batch_quant8_1::is_ignored, + space_to_batch_quant8_1::examples); +} + +namespace space_to_batch_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_quant8_2 test +#include "generated/examples/space_to_batch_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_2.model.cpp" +} // namespace space_to_batch_quant8_2 +TEST_F(GeneratedTests, space_to_batch_quant8_2) { + execute(space_to_batch_quant8_2::CreateModel, + space_to_batch_quant8_2::is_ignored, + space_to_batch_quant8_2::examples); +} + +namespace space_to_batch_quant8_3 { +std::vector<MixedTypedExample> examples = { +// Generated space_to_batch_quant8_3 test +#include "generated/examples/space_to_batch_quant8_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/space_to_batch_quant8_3.model.cpp" +} // namespace space_to_batch_quant8_3 +TEST_F(GeneratedTests, space_to_batch_quant8_3) { + execute(space_to_batch_quant8_3::CreateModel, + space_to_batch_quant8_3::is_ignored, + space_to_batch_quant8_3::examples); +} + +namespace squeeze_2D_float_1_nnfw { +std::vector<MixedTypedExample> examples = { +// Generated squeeze_2D_float_1_nnfw test +#include "generated/examples/squeeze_2D_float_1_nnfw.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze_2D_float_1_nnfw.model.cpp" +} // namespace squeeze_2D_float_1_nnfw +TEST_F(GeneratedTests, squeeze_2D_float_1_nnfw) { + execute(squeeze_2D_float_1_nnfw::CreateModel, + squeeze_2D_float_1_nnfw::is_ignored, + squeeze_2D_float_1_nnfw::examples); +} + +namespace squeeze_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated squeeze_float_1 test +#include "generated/examples/squeeze_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze_float_1.model.cpp" +} // namespace squeeze_float_1 +TEST_F(GeneratedTests, squeeze_float_1) { + execute(squeeze_float_1::CreateModel, + squeeze_float_1::is_ignored, + squeeze_float_1::examples); +} + +namespace squeeze { +std::vector<MixedTypedExample> examples = { +// Generated squeeze test +#include "generated/examples/squeeze.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze.model.cpp" +} // namespace squeeze +TEST_F(GeneratedTests, squeeze) { + execute(squeeze::CreateModel, + squeeze::is_ignored, + squeeze::examples); +} + +namespace squeeze_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated squeeze_quant8_1 test +#include "generated/examples/squeeze_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/squeeze_quant8_1.model.cpp" +} // namespace squeeze_quant8_1 +TEST_F(GeneratedTests, squeeze_quant8_1) { + execute(squeeze_quant8_1::CreateModel, + squeeze_quant8_1::is_ignored, + squeeze_quant8_1::examples); +} + +namespace strided_slice_float_10 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_10 test +#include "generated/examples/strided_slice_float_10.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_10.model.cpp" +} // namespace strided_slice_float_10 +TEST_F(GeneratedTests, strided_slice_float_10) { + execute(strided_slice_float_10::CreateModel, + strided_slice_float_10::is_ignored, + strided_slice_float_10::examples); +} + +namespace strided_slice_float_11 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_11 test +#include "generated/examples/strided_slice_float_11.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_11.model.cpp" +} // namespace strided_slice_float_11 +TEST_F(GeneratedTests, strided_slice_float_11) { + execute(strided_slice_float_11::CreateModel, + strided_slice_float_11::is_ignored, + strided_slice_float_11::examples); +} + +namespace strided_slice_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_1 test +#include "generated/examples/strided_slice_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_1.model.cpp" +} // namespace strided_slice_float_1 +TEST_F(GeneratedTests, strided_slice_float_1) { + execute(strided_slice_float_1::CreateModel, + strided_slice_float_1::is_ignored, + strided_slice_float_1::examples); +} + +namespace strided_slice_float_2 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_2 test +#include "generated/examples/strided_slice_float_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_2.model.cpp" +} // namespace strided_slice_float_2 +TEST_F(GeneratedTests, strided_slice_float_2) { + execute(strided_slice_float_2::CreateModel, + strided_slice_float_2::is_ignored, + strided_slice_float_2::examples); +} + +namespace strided_slice_float_3 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_3 test +#include "generated/examples/strided_slice_float_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_3.model.cpp" +} // namespace strided_slice_float_3 +TEST_F(GeneratedTests, strided_slice_float_3) { + execute(strided_slice_float_3::CreateModel, + strided_slice_float_3::is_ignored, + strided_slice_float_3::examples); +} + +namespace strided_slice_float_4 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_4 test +#include "generated/examples/strided_slice_float_4.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_4.model.cpp" +} // namespace strided_slice_float_4 +TEST_F(GeneratedTests, strided_slice_float_4) { + execute(strided_slice_float_4::CreateModel, + strided_slice_float_4::is_ignored, + strided_slice_float_4::examples); +} + +namespace strided_slice_float_5 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_5 test +#include "generated/examples/strided_slice_float_5.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_5.model.cpp" +} // namespace strided_slice_float_5 +TEST_F(GeneratedTests, strided_slice_float_5) { + execute(strided_slice_float_5::CreateModel, + strided_slice_float_5::is_ignored, + strided_slice_float_5::examples); +} + +namespace strided_slice_float_6 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_6 test +#include "generated/examples/strided_slice_float_6.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_6.model.cpp" +} // namespace strided_slice_float_6 +TEST_F(GeneratedTests, strided_slice_float_6) { + execute(strided_slice_float_6::CreateModel, + strided_slice_float_6::is_ignored, + strided_slice_float_6::examples); +} + +namespace strided_slice_float_7 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_7 test +#include "generated/examples/strided_slice_float_7.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_7.model.cpp" +} // namespace strided_slice_float_7 +TEST_F(GeneratedTests, strided_slice_float_7) { + execute(strided_slice_float_7::CreateModel, + strided_slice_float_7::is_ignored, + strided_slice_float_7::examples); +} + +namespace strided_slice_float_8 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_8 test +#include "generated/examples/strided_slice_float_8.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_8.model.cpp" +} // namespace strided_slice_float_8 +TEST_F(GeneratedTests, strided_slice_float_8) { + execute(strided_slice_float_8::CreateModel, + strided_slice_float_8::is_ignored, + strided_slice_float_8::examples); +} + +namespace strided_slice_float_9 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_float_9 test +#include "generated/examples/strided_slice_float_9.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_float_9.model.cpp" +} // namespace strided_slice_float_9 +TEST_F(GeneratedTests, strided_slice_float_9) { + execute(strided_slice_float_9::CreateModel, + strided_slice_float_9::is_ignored, + strided_slice_float_9::examples); +} + +namespace strided_slice { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice test +#include "generated/examples/strided_slice.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice.model.cpp" +} // namespace strided_slice +TEST_F(GeneratedTests, strided_slice) { + execute(strided_slice::CreateModel, + strided_slice::is_ignored, + strided_slice::examples); +} + +namespace strided_slice_qaunt8_10 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_qaunt8_10 test +#include "generated/examples/strided_slice_qaunt8_10.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_qaunt8_10.model.cpp" +} // namespace strided_slice_qaunt8_10 +TEST_F(GeneratedTests, strided_slice_qaunt8_10) { + execute(strided_slice_qaunt8_10::CreateModel, + strided_slice_qaunt8_10::is_ignored, + strided_slice_qaunt8_10::examples); +} + +namespace strided_slice_qaunt8_11 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_qaunt8_11 test +#include "generated/examples/strided_slice_qaunt8_11.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_qaunt8_11.model.cpp" +} // namespace strided_slice_qaunt8_11 +TEST_F(GeneratedTests, strided_slice_qaunt8_11) { + execute(strided_slice_qaunt8_11::CreateModel, + strided_slice_qaunt8_11::is_ignored, + strided_slice_qaunt8_11::examples); +} + +namespace strided_slice_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_1 test +#include "generated/examples/strided_slice_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_1.model.cpp" +} // namespace strided_slice_quant8_1 +TEST_F(GeneratedTests, strided_slice_quant8_1) { + execute(strided_slice_quant8_1::CreateModel, + strided_slice_quant8_1::is_ignored, + strided_slice_quant8_1::examples); +} + +namespace strided_slice_quant8_2 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_2 test +#include "generated/examples/strided_slice_quant8_2.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_2.model.cpp" +} // namespace strided_slice_quant8_2 +TEST_F(GeneratedTests, strided_slice_quant8_2) { + execute(strided_slice_quant8_2::CreateModel, + strided_slice_quant8_2::is_ignored, + strided_slice_quant8_2::examples); +} + +namespace strided_slice_quant8_3 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_3 test +#include "generated/examples/strided_slice_quant8_3.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_3.model.cpp" +} // namespace strided_slice_quant8_3 +TEST_F(GeneratedTests, strided_slice_quant8_3) { + execute(strided_slice_quant8_3::CreateModel, + strided_slice_quant8_3::is_ignored, + strided_slice_quant8_3::examples); +} + +namespace strided_slice_quant8_4 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_4 test +#include "generated/examples/strided_slice_quant8_4.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_4.model.cpp" +} // namespace strided_slice_quant8_4 +TEST_F(GeneratedTests, strided_slice_quant8_4) { + execute(strided_slice_quant8_4::CreateModel, + strided_slice_quant8_4::is_ignored, + strided_slice_quant8_4::examples); +} + +namespace strided_slice_quant8_5 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_5 test +#include "generated/examples/strided_slice_quant8_5.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_5.model.cpp" +} // namespace strided_slice_quant8_5 +TEST_F(GeneratedTests, strided_slice_quant8_5) { + execute(strided_slice_quant8_5::CreateModel, + strided_slice_quant8_5::is_ignored, + strided_slice_quant8_5::examples); +} + +namespace strided_slice_quant8_6 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_6 test +#include "generated/examples/strided_slice_quant8_6.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_6.model.cpp" +} // namespace strided_slice_quant8_6 +TEST_F(GeneratedTests, strided_slice_quant8_6) { + execute(strided_slice_quant8_6::CreateModel, + strided_slice_quant8_6::is_ignored, + strided_slice_quant8_6::examples); +} + +namespace strided_slice_quant8_7 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_7 test +#include "generated/examples/strided_slice_quant8_7.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_7.model.cpp" +} // namespace strided_slice_quant8_7 +TEST_F(GeneratedTests, strided_slice_quant8_7) { + execute(strided_slice_quant8_7::CreateModel, + strided_slice_quant8_7::is_ignored, + strided_slice_quant8_7::examples); +} + +namespace strided_slice_quant8_8 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_8 test +#include "generated/examples/strided_slice_quant8_8.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_8.model.cpp" +} // namespace strided_slice_quant8_8 +TEST_F(GeneratedTests, strided_slice_quant8_8) { + execute(strided_slice_quant8_8::CreateModel, + strided_slice_quant8_8::is_ignored, + strided_slice_quant8_8::examples); +} + +namespace strided_slice_quant8_9 { +std::vector<MixedTypedExample> examples = { +// Generated strided_slice_quant8_9 test +#include "generated/examples/strided_slice_quant8_9.example.cpp" +}; +// Generated model constructor +#include "generated/models/strided_slice_quant8_9.model.cpp" +} // namespace strided_slice_quant8_9 +TEST_F(GeneratedTests, strided_slice_quant8_9) { + execute(strided_slice_quant8_9::CreateModel, + strided_slice_quant8_9::is_ignored, + strided_slice_quant8_9::examples); +} + +namespace sub_broadcast_float { +std::vector<MixedTypedExample> examples = { +// Generated sub_broadcast_float test +#include "generated/examples/sub_broadcast_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/sub_broadcast_float.model.cpp" +} // namespace sub_broadcast_float +TEST_F(GeneratedTests, sub_broadcast_float) { + execute(sub_broadcast_float::CreateModel, + sub_broadcast_float::is_ignored, + sub_broadcast_float::examples); +} + +namespace sub { +std::vector<MixedTypedExample> examples = { +// Generated sub test +#include "generated/examples/sub.example.cpp" +}; +// Generated model constructor +#include "generated/models/sub.model.cpp" +} // namespace sub +TEST_F(GeneratedTests, sub) { + execute(sub::CreateModel, + sub::is_ignored, + sub::examples); +} + +namespace transpose_float_1 { +std::vector<MixedTypedExample> examples = { +// Generated transpose_float_1 test +#include "generated/examples/transpose_float_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose_float_1.model.cpp" +} // namespace transpose_float_1 +TEST_F(GeneratedTests, transpose_float_1) { + execute(transpose_float_1::CreateModel, + transpose_float_1::is_ignored, + transpose_float_1::examples); +} + +namespace transpose { +std::vector<MixedTypedExample> examples = { +// Generated transpose test +#include "generated/examples/transpose.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose.model.cpp" +} // namespace transpose +TEST_F(GeneratedTests, transpose) { + execute(transpose::CreateModel, + transpose::is_ignored, + transpose::examples); +} + +namespace transpose_quant8_1 { +std::vector<MixedTypedExample> examples = { +// Generated transpose_quant8_1 test +#include "generated/examples/transpose_quant8_1.example.cpp" +}; +// Generated model constructor +#include "generated/models/transpose_quant8_1.model.cpp" +} // namespace transpose_quant8_1 +TEST_F(GeneratedTests, transpose_quant8_1) { + execute(transpose_quant8_1::CreateModel, + transpose_quant8_1::is_ignored, + transpose_quant8_1::examples); +} + +namespace cast_ex_float32_to_int32 { +std::vector<MixedTypedExample> examples = { +// Generated cast_ex_float32_to_int32 test +#include "generated/examples/cast_ex_float32_to_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/cast_ex_float32_to_int32.model.cpp" +} // namespace cast_ex_float32_to_int32 +TEST_F(GeneratedTests, cast_ex_float32_to_int32) { + execute(cast_ex_float32_to_int32::CreateModel, + cast_ex_float32_to_int32::is_ignored, + cast_ex_float32_to_int32::examples); +} + +namespace cast_ex_int32_to_float32 { +std::vector<MixedTypedExample> examples = { +// Generated cast_ex_int32_to_float32 test +#include "generated/examples/cast_ex_int32_to_float32.example.cpp" +}; +// Generated model constructor +#include "generated/models/cast_ex_int32_to_float32.model.cpp" +} // namespace cast_ex_int32_to_float32 +TEST_F(GeneratedTests, cast_ex_int32_to_float32) { + execute(cast_ex_int32_to_float32::CreateModel, + cast_ex_int32_to_float32::is_ignored, + cast_ex_int32_to_float32::examples); +} + +namespace gather_1D_float { +std::vector<MixedTypedExample> examples = { +// Generated gather_1D_float test +#include "generated/examples/gather_1D_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_1D_float.model.cpp" +} // namespace gather_1D_float +TEST_F(GeneratedTests, gather_1D_float) { + execute(gather_1D_float::CreateModel, + gather_1D_float::is_ignored, + gather_1D_float::examples); +} + +namespace gather_1D_int32 { +std::vector<MixedTypedExample> examples = { +// Generated gather_1D_int32 test +#include "generated/examples/gather_1D_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_1D_int32.model.cpp" +} // namespace gather_1D_int32 +TEST_F(GeneratedTests, gather_1D_int32) { + execute(gather_1D_int32::CreateModel, + gather_1D_int32::is_ignored, + gather_1D_int32::examples); +} + +namespace gather_1D_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated gather_1D_quant8 test +#include "generated/examples/gather_1D_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_1D_quant8.model.cpp" +} // namespace gather_1D_quant8 +TEST_F(GeneratedTests, gather_1D_quant8) { + execute(gather_1D_quant8::CreateModel, + gather_1D_quant8::is_ignored, + gather_1D_quant8::examples); +} + +namespace gather_2D_float { +std::vector<MixedTypedExample> examples = { +// Generated gather_2D_float test +#include "generated/examples/gather_2D_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_2D_float.model.cpp" +} // namespace gather_2D_float +TEST_F(GeneratedTests, gather_2D_float) { + execute(gather_2D_float::CreateModel, + gather_2D_float::is_ignored, + gather_2D_float::examples); +} + +namespace gather_2D_int32 { +std::vector<MixedTypedExample> examples = { +// Generated gather_2D_int32 test +#include "generated/examples/gather_2D_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_2D_int32.model.cpp" +} // namespace gather_2D_int32 +TEST_F(GeneratedTests, gather_2D_int32) { + execute(gather_2D_int32::CreateModel, + gather_2D_int32::is_ignored, + gather_2D_int32::examples); +} + +namespace gather_2D_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated gather_2D_quant8 test +#include "generated/examples/gather_2D_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/gather_2D_quant8.model.cpp" +} // namespace gather_2D_quant8 +TEST_F(GeneratedTests, gather_2D_quant8) { + execute(gather_2D_quant8::CreateModel, + gather_2D_quant8::is_ignored, + gather_2D_quant8::examples); +} + +namespace tensorflowmax_ex_2D_float { +std::vector<MixedTypedExample> examples = { +// Generated tensorflowmax_ex_2D_float test +#include "generated/examples/tensorflowmax_ex_2D_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/tensorflowmax_ex_2D_float.model.cpp" +} // namespace tensorflowmax_ex_2D_float +TEST_F(GeneratedTests, tensorflowmax_ex_2D_float) { + execute(tensorflowmax_ex_2D_float::CreateModel, + tensorflowmax_ex_2D_float::is_ignored, + tensorflowmax_ex_2D_float::examples); +} + +namespace tensorflowmax_ex_2D_int32 { +std::vector<MixedTypedExample> examples = { +// Generated tensorflowmax_ex_2D_int32 test +#include "generated/examples/tensorflowmax_ex_2D_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/tensorflowmax_ex_2D_int32.model.cpp" +} // namespace tensorflowmax_ex_2D_int32 +TEST_F(GeneratedTests, tensorflowmax_ex_2D_int32) { + execute(tensorflowmax_ex_2D_int32::CreateModel, + tensorflowmax_ex_2D_int32::is_ignored, + tensorflowmax_ex_2D_int32::examples); +} + +namespace topk_v2_1D_float { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_1D_float test +#include "generated/examples/topk_v2_1D_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_1D_float.model.cpp" +} // namespace topk_v2_1D_float +TEST_F(GeneratedTests, topk_v2_1D_float) { + execute(topk_v2_1D_float::CreateModel, + topk_v2_1D_float::is_ignored, + topk_v2_1D_float::examples); +} + +namespace topk_v2_1D_int32 { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_1D_int32 test +#include "generated/examples/topk_v2_1D_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_1D_int32.model.cpp" +} // namespace topk_v2_1D_int32 +TEST_F(GeneratedTests, topk_v2_1D_int32) { + execute(topk_v2_1D_int32::CreateModel, + topk_v2_1D_int32::is_ignored, + topk_v2_1D_int32::examples); +} + +namespace topk_v2_1D_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_1D_quant8 test +#include "generated/examples/topk_v2_1D_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_1D_quant8.model.cpp" +} // namespace topk_v2_1D_quant8 +TEST_F(GeneratedTests, topk_v2_1D_quant8) { + execute(topk_v2_1D_quant8::CreateModel, + topk_v2_1D_quant8::is_ignored, + topk_v2_1D_quant8::examples); +} + +namespace topk_v2_2D_float { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_2D_float test +#include "generated/examples/topk_v2_2D_float.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_2D_float.model.cpp" +} // namespace topk_v2_2D_float +TEST_F(GeneratedTests, topk_v2_2D_float) { + execute(topk_v2_2D_float::CreateModel, + topk_v2_2D_float::is_ignored, + topk_v2_2D_float::examples); +} + +namespace topk_v2_2D_int32 { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_2D_int32 test +#include "generated/examples/topk_v2_2D_int32.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_2D_int32.model.cpp" +} // namespace topk_v2_2D_int32 +TEST_F(GeneratedTests, topk_v2_2D_int32) { + execute(topk_v2_2D_int32::CreateModel, + topk_v2_2D_int32::is_ignored, + topk_v2_2D_int32::examples); +} + +namespace topk_v2_2D_quant8 { +std::vector<MixedTypedExample> examples = { +// Generated topk_v2_2D_quant8 test +#include "generated/examples/topk_v2_2D_quant8.example.cpp" +}; +// Generated model constructor +#include "generated/models/topk_v2_2D_quant8.model.cpp" +} // namespace topk_v2_2D_quant8 +TEST_F(GeneratedTests, topk_v2_2D_quant8) { + execute(topk_v2_2D_quant8::CreateModel, + topk_v2_2D_quant8::is_ignored, + topk_v2_2D_quant8::examples); +} diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp new file mode 100644 index 000000000..111326298 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp new file mode 100644 index 000000000..45a758041 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp new file mode 100644 index 000000000..6d1d6f760 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/batch_to_space_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: batch_to_space_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/cast_ex_float32_to_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/cast_ex_float32_to_int32.example.cpp new file mode 100644 index 000000000..bf931adee --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/cast_ex_float32_to_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: cast_ex_float32_to_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {100.0f, 20.0f, 3.0f, 0.4f, 0.999f, 1.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {100, 20, 3, 0, 0, 1}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/cast_ex_int32_to_float32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/cast_ex_int32_to_float32.example.cpp new file mode 100644 index 000000000..7a076e19c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/cast_ex_int32_to_float32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: cast_ex_int32_to_float32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {100, 200, 300, 400, 500, 600}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {100.0f, 200.0f, 300.0f, 400.0f, 500.0f, 600.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/concat_float_4D_axis3_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/concat_float_4D_axis3_1_nnfw.example.cpp new file mode 100644 index 000000000..63ec5c1a8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/concat_float_4D_axis3_1_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: concat_float_4D_axis3_1_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-0.03203143f, -0.0334147f, -0.02527265f, 0.04576106f, 0.08869292f, 0.06428383f, -0.06473722f, -0.21933985f, -0.05541003f, -0.24157837f, -0.16328812f, -0.04581105f}}, {1, {-0.0569439f, -0.15872048f, 0.02965238f, -0.12761882f, -0.00185435f, -0.03297619f, 0.03581043f, -0.12603407f, 0.05999133f, 0.00290503f, 0.1727029f, 0.03342071f}}, {2, {0.10992613f, 0.09185287f, 0.16433905f, -0.00059073f, -0.01480746f, 0.0135175f, 0.07129054f, -0.15095694f, -0.04579685f, -0.13260484f, -0.10045543f, 0.0647094f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-0.03203143f, -0.0334147f, -0.0569439f, -0.15872048f, 0.10992613f, 0.09185287f, -0.02527265f, 0.04576106f, 0.02965238f, -0.12761882f, 0.16433905f, -0.00059073f, 0.08869292f, 0.06428383f, -0.00185435f, -0.03297619f, -0.01480746f, 0.0135175f, -0.06473722f, -0.21933985f, 0.03581043f, -0.12603407f, 0.07129054f, -0.15095694f, -0.05541003f, -0.24157837f, 0.05999133f, 0.00290503f, -0.04579685f, -0.13260484f, -0.16328812f, -0.04581105f, 0.1727029f, 0.03342071f, -0.10045543f, 0.0647094f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp index 9b097ac2d..1840bc9cf 100644 --- a/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp +++ b/runtimes/tests/neural_networks_test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs.example.cpp @@ -4,7 +4,7 @@ //Input(s) { // See tools/test_generator/include/TestHarness.h:MixedTyped // int -> FLOAT32 map - {{0, {10, 21, 100, 10, 22, 200, 10, 23, 300, 10, 24, 400}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}}, + {{0, {10, 21, 100, 0, 10, 22, 200, 0, 10, 23, 300, 0, 10, 24, 400, 0}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}}, // int -> INT32 map {}, // int -> QUANT8_ASYMM map diff --git a/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp new file mode 100644 index 000000000..23ad4b05d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/div.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: div.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, -2.0f, -4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/div_.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/div_.example.cpp new file mode 100644 index 000000000..cd96fd77c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/div_.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: div_.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, -2.0f, -4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp new file mode 100644 index 000000000..ccbb571e2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/div_broadcast_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: div_broadcast_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2}}, {1, {1, 1, 2, 2}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 0.5f, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_2d_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_2d_nnfw.example.cpp new file mode 100644 index 000000000..14211f5cd --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_2d_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: embedding_lookup_2d_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{1, {0.0f, 0.1f, 1.0f, 1.1f, 2.0f, 2.1f}}}, + // int -> INT32 map + {{0, {1, 0, 2}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 1.1f, 0.0f, 0.1f, 2.0f, 2.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_4d_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_4d_nnfw.example.cpp new file mode 100644 index 000000000..8b144a165 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/embedding_lookup_4d_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: embedding_lookup_4d_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {4, 0, 2}}, {1, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/floor_.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/floor_.example.cpp new file mode 100644 index 000000000..7481d112e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/floor_.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: floor_.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-1.5f, -1.0f, -0.5f, 0.0f, 0.5f, 1.0f, 1.5f, 10.2f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-2.0f, -1.0f, -1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_1_nnfw.example.cpp new file mode 100644 index 000000000..1a46ccd34 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_1_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: fully_connected_float_1_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4910057783f, 3.4019672871f, -0.0598693565f, -0.0065411143f, -0.646147728f, 1.9235717058f, 1.0784962177f, 0.176592201f, -2.2495496273f, -1.6010370255f, -2.4747757912f, -0.3825767934f, 2.305898428f, 0.7288306952f, -0.8964791894f, -2.7584488392f, -0.287591964f, 0.1335377693f, 1.8338065147f, -2.6112849712f, 0.9390821457f, 1.984385252f, -1.2190681696f, 1.0274435282f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.0375289917f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp new file mode 100644 index 000000000..14ee46d5f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: fully_connected_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 2, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {11, 9}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp new file mode 100644 index 000000000..4086bc559 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/fully_connected_float_4d_simple.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, -9, -10, 1, 2, 3, 4, 5, 6, 7, -8, 9, -10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {24, 25, 26, 58, 59, 60}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_1D_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_float.example.cpp new file mode 100644 index 000000000..494968cf0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_1D_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3.0f, 4.0f, 5.0f, 6.0f}}}, + // int -> INT32 map + {{1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {5.0f, 3.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_1D_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_int32.example.cpp new file mode 100644 index 000000000..305018add --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_1D_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {40000, 41000, 50000, 60000}}, {1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {50000, 40000}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_1D_quant8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_quant8.example.cpp new file mode 100644 index 000000000..d633f0c25 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_1D_quant8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_1D_uint8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {{0, {7, 9, 11, 13}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {11, 7}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_2D_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_float.example.cpp new file mode 100644 index 000000000..0bf46fd4d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_2D_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3.123456789123457f, 4.123456789123456f, 5.123456789123456f, 6.123456789123456f, 7.123456789123456f, 8.123456789123457f, 9.123456789123457f, 1.1234567891234568f, 2.123456789123457f, 18.123456789123455f, 19.123456789123455f, 11.123456789123457f}}}, + // int -> INT32 map + {{1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.123456789123457f, 18.123456789123455f, 19.123456789123455f, 11.123456789123457f, 3.123456789123457f, 4.123456789123456f, 5.123456789123456f, 6.123456789123456f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_2D_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_int32.example.cpp new file mode 100644 index 000000000..052eff5ee --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_2D_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {40000, 41000, 50000, 60000, 70000, 80000, 90000, 79000, 170000, 180000, 190000, 110000}}, {1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {170000, 180000, 190000, 110000, 40000, 41000, 50000, 60000}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/gather_2D_quant8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_quant8.example.cpp new file mode 100644 index 000000000..b232d917b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/gather_2D_quant8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: gather_2D_uint8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{1, {2, 0}}}, + // int -> QUANT8_ASYMM map + {{0, {7, 9, 11, 13, 15, 17, 19, 3, 5, 37, 39, 23}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {5, 37, 39, 23, 7, 9, 11, 13}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp new file mode 100644 index 000000000..27b8258a9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.5f, 3.5f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp new file mode 100644 index 000000000..99d196f17 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_1_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_axis01_1_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 1.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp new file mode 100644 index 000000000..4ea323074 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_axis01_2_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_axis01_2_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {12.0f, 13.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp new file mode 100644 index 000000000..4c53d77df --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {12.0f, 13.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp new file mode 100644 index 000000000..844dd2a7b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {10.5f, 12.5f, 14.5f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp new file mode 100644 index 000000000..652c84733 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {12, 13}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp new file mode 100644 index 000000000..56dec24aa --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mean_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mean_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {10, 12, 14}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_1_nnfw.example.cpp new file mode 100644 index 000000000..c8cd5fdad --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_1_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mul_broadcast_3D_1D_1_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0.8364028931f, 0.6620308161f, 1.1811592579f, 0.4827561378f, -0.384627074f, -1.7236120701f, 3.5318591595f, 0.2959995866f, 1.6260499954f, -0.7885181308f, -0.8246002197f, -1.1367146969f}}, {1, {0.8364028931f, -0.384627074f, 1.6260499954f, 0.6620308161f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0.6995698214f, -0.2546349764f, 1.9206240177f, 0.3195994496f, -0.3217031956f, 0.6629478931f, 5.7429795265f, 0.1959608495f, 1.3600329161f, 0.3032854199f, -1.3408411741f, -0.7525401711f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_2_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_2_nnfw.example.cpp new file mode 100644 index 000000000..8488edd4f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/mul_broadcast_3D_1D_2_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: mul_broadcast_3D_1D_2_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.2774236202f, -2.4773113728f, -0.4044751823f, -0.8101355433f, -1.9691983461f, 2.2676842213f, -2.2757787704f, -0.8289190531f, 0.0121828541f, -1.7484937906f, -0.5269883871f, -0.6346995831f, 2.4886128902f, -1.5107979774f, -0.7372134924f, -0.5374289751f, -1.2039715052f, 1.527836442f, 0.8248311877f, -2.4172706604f, 0.6997106671f, -0.8929677606f, 0.3650484681f, 1.3652951717f}}, {1, {2.2774236202f, 0.0121828541f, -1.2039715052f, -1.9691983461f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {5.1866583824f, -0.0301807225f, 0.4869765937f, 1.5953176022f, -4.4846987724f, 0.0276268665f, 2.7399728298f, 1.6323059797f, 0.0277455188f, -0.0213016439f, 0.6344789863f, 1.2498493195f, 5.6676259041f, -0.0184058305f, 0.8875840306f, 1.0583041906f, -2.7419531345f, 0.0186134093f, -0.993073225f, 4.7600855827f, 1.593537569f, -0.0108788963f, -0.4395079613f, -2.6885368824f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp new file mode 100644 index 000000000..dbec43395 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/pad.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: pad.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 2.0f, 0.0f, 0.0f, 3.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp new file mode 100644 index 000000000..873149b7f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/pad_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: pad_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp new file mode 100644 index 000000000..e226e3634 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp new file mode 100644 index 000000000..06d0ff34d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp new file mode 100644 index 000000000..a7b001022 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp new file mode 100644 index 000000000..5198bae1e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp new file mode 100644 index 000000000..1c86710b0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp new file mode 100644 index 000000000..4e615d0e5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp new file mode 100644 index 000000000..13745acdd --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/space_to_batch_quant8_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: space_to_batch_quant8_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp new file mode 100644 index 000000000..bcbc54f6c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze_2D_float_1_nnfw.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze_2D_float_1_nnfw.example.cpp new file mode 100644 index 000000000..31a82efa8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze_2D_float_1_nnfw.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze_2D_float_1_nnfw.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.4f, 2.3f, 3.2f, 4.1f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp new file mode 100644 index 000000000..2616d6587 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp new file mode 100644 index 000000000..53bb0a832 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/squeeze_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: squeeze_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice.example.cpp new file mode 100644 index 000000000..6f93529e2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 3.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_1.example.cpp new file mode 100644 index 000000000..fe389a455 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_10.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_10.example.cpp new file mode 100644 index 000000000..cbd0a4911 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_10.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_10.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_2.example.cpp new file mode 100644 index 000000000..91dfc5f07 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_3.example.cpp new file mode 100644 index 000000000..1a12e90f0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_4.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_4.example.cpp new file mode 100644 index 000000000..1e1d0005d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_4.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_4.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_5.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_5.example.cpp new file mode 100644 index 000000000..d3aa972f7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_5.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_5.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_6.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_6.example.cpp new file mode 100644 index 000000000..958e561a8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_6.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_6.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_7.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_7.example.cpp new file mode 100644 index 000000000..2a2861ae2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_7.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_7.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3, 2, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_8.example.cpp new file mode 100644 index 000000000..63a9b4ce1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {6, 5, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_9.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_9.example.cpp new file mode 100644 index 000000000..ae7f829bd --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_ex_float_9.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_ex_float_9.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 4, 5}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_1.example.cpp new file mode 100644 index 000000000..9e996dd6c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_10.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_10.example.cpp new file mode 100644 index 000000000..5350c61cf --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_10.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_10.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp new file mode 100644 index 000000000..19bb573a6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_11.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_11.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_2.example.cpp new file mode 100644 index 000000000..b1c0011f5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_3.example.cpp new file mode 100644 index 000000000..fbd8616b1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_4.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_4.example.cpp new file mode 100644 index 000000000..0ec32c310 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_4.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_4.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_5.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_5.example.cpp new file mode 100644 index 000000000..a2b8b66bc --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_5.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_5.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_6.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_6.example.cpp new file mode 100644 index 000000000..0a318b0d2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_6.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_6.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_7.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_7.example.cpp new file mode 100644 index 000000000..72cdcd373 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_7.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_7.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3, 2, 1}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_8.example.cpp new file mode 100644 index 000000000..528e2d607 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {6, 5, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_9.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_9.example.cpp new file mode 100644 index 000000000..2920d8e56 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_float_9.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_float_9.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 3, 4, 5, 6}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2, 4, 5}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp new file mode 100644 index 000000000..091aa0623 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_10.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_qaunt8_10.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {4, 5, 6}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp new file mode 100644 index 000000000..8e8c23eb8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_qaunt8_11.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_qaunt8_11.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp new file mode 100644 index 000000000..6eb2d951a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp new file mode 100644 index 000000000..481fe2e12 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_2.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_2.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp new file mode 100644 index 000000000..a68e88219 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_3.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_3.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp new file mode 100644 index 000000000..aa486a4e3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_4.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_4.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp new file mode 100644 index 000000000..db8458096 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_5.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_5.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp new file mode 100644 index 000000000..232e8c4b0 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_6.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_6.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {2, 3, 4}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp new file mode 100644 index 000000000..86f32fea2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_7.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_7.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {3, 2, 1}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp new file mode 100644 index 000000000..fe5026d1e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {6, 5, 4}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp new file mode 100644 index 000000000..dd590e482 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/strided_slice_quant8_9.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: strided_slice_quant8_9.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 3, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {1, 2, 4, 5}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/sub.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/sub.example.cpp new file mode 100644 index 000000000..282dbe941 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/sub.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: sub.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0.0f, -2.0f, 12.0f, -20.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp new file mode 100644 index 000000000..4888c76ee --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/sub_broadcast_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: sub_broadcast_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1, 2}}, {1, {1, 2, 3, 4}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 0, -2, -2}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/tanh_.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/tanh_.example.cpp new file mode 100644 index 000000000..36fbb3715 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/tanh_.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: tanh_.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-1, 0, 1, 10}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {-0.761594156f, 0, 0.761594156f, 0.999999996f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_float.example.cpp new file mode 100644 index 000000000..650eecd78 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: tensorflowmax_ex_2D_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3.2f, 11.47f, 3.8f, 5.76f, 28.2f, 0.999f, -1.3f, -13.5f, -3.4f, -22.1f, -2.2f, -49.7f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {11.47f, 28.2f, -2.2f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_int32.example.cpp new file mode 100644 index 000000000..3ce040497 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/tensorflowmax_ex_2D_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: tensorflowmax_ex_2D_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {3, 11, 3, 5, 28, 0, -1, -13, -4, -22, -2, -49}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {11, 28, -2}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_float.example.cpp new file mode 100644 index 000000000..44d438cf5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_1D_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {5.123456789123456f, 3.123456789123457f, 4.123456789123456f, 6.123456789123456f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {6.123456789123456f, 5.123456789123456f}}}, + // int -> INT32 map + {{1, {3, 0}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_int32.example.cpp new file mode 100644 index 000000000..3702e5a82 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_1D_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {50000, 40000, 41000, 60000}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {60000, 50000}}, {1, {3, 0}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_quant8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_quant8.example.cpp new file mode 100644 index 000000000..ce173e97d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_1D_quant8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_1D_quant8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {7, 4, 5, 6}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{1, {0, 3}}}, + // int -> QUANT8_ASYMM map + {{0, {7, 6}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_float.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_float.example.cpp new file mode 100644 index 000000000..393a7a8b3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_float.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_2D_float.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {3.123456789123457f, 4.123456789123456f, 5.123456789123456f, 6.123456789123456f, 7.123456789123456f, 8.123456789123457f, 9.123456789123457f, 1.1234567891234568f, 2.123456789123457f, 18.123456789123455f, 19.123456789123455f, 11.123456789123457f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {6.123456789123456f, 5.123456789123456f, 9.123456789123457f, 8.123456789123457f, 19.123456789123455f, 18.123456789123455f}}}, + // int -> INT32 map + {{1, {3, 2, 2, 1, 2, 1}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_int32.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_int32.example.cpp new file mode 100644 index 000000000..62045728b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_int32.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_2D_int32.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {40000, 41000, 50000, 60000, 70000, 80000, 90000, 79000, 170000, 180000, 190000, 110000}}}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{0, {60000, 50000, 90000, 80000, 190000, 180000}}, {1, {3, 2, 2, 1, 2, 1}}}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_quant8.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_quant8.example.cpp new file mode 100644 index 000000000..5a192ce8f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/topk_v2_2D_quant8.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: topk_v2_2D_quant8.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {3, 4, 5, 6, 7, 8, 9, 1, 2, 18, 19, 11}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {{1, {3, 2, 2, 1, 2, 1}}}, + // int -> QUANT8_ASYMM map + {{0, {6, 5, 9, 8, 19, 18}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp new file mode 100644 index 000000000..790923cc2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 2.0f, 3.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {1.0f, 3.0f, 2.0f, 4.0f}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp new file mode 100644 index 000000000..31f67994c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose_float_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose_float_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {{0, {0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119}}}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp b/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp new file mode 100644 index 000000000..f1bb2fa16 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/examples/transpose_quant8_1.example.cpp @@ -0,0 +1,22 @@ +// Generated file (from: transpose_quant8_1.mod.py). Do not edit +// Begin of an example +{ +//Input(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}}} +}, +//Output(s) +{ // See tools/test_generator/include/TestHarness.h:MixedTyped + // int -> FLOAT32 map + {}, + // int -> INT32 map + {}, + // int -> QUANT8_ASYMM map + {{0, {0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119}}} +} +}, // End of an example diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp new file mode 100644 index 000000000..6c6d5900c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp new file mode 100644 index 000000000..e074783e5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp new file mode 100644 index 000000000..892274029 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/batch_to_space_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: batch_to_space_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp new file mode 100644 index 000000000..d28671b22 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/cast_ex_float32_to_int32.model.cpp @@ -0,0 +1,20 @@ +// Generated file (from: cast_ex_float32_to_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2, 3}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + // Phase 2, operations + model->addOperationEx(ANEURALNETWORKS_CAST_EX, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp new file mode 100644 index 000000000..af435bff8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/cast_ex_int32_to_float32.model.cpp @@ -0,0 +1,20 @@ +// Generated file (from: cast_ex_int32_to_float32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type0(Type::TENSOR_INT32, {2, 3}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + // Phase 2, operations + model->addOperationEx(ANEURALNETWORKS_CAST_EX, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp new file mode 100644 index 000000000..82ef41dc9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/concat_float_4D_axis3_1_nnfw.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: concat_float_4D_axis3_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 3, 6}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto op3 = model->addOperand(&type0); + auto axis0 = model->addOperand(&type1); + auto result = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis0_init[] = {3}; + model->setOperandValue(axis0, axis0_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_CONCATENATION, {op1, op2, op3, axis0}, {result}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2, op3}, + {result}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp index 19de70509..38e56eaad 100644 --- a/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp +++ b/runtimes/tests/neural_networks_test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs.model.cpp @@ -1,19 +1,18 @@ // Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs.mod.py). Do not edit void CreateModel(Model *model) { - OperandType type3(Type::INT32, {}); - OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4}); - OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3}); - OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4}); - OperandType type2(Type::TENSOR_FLOAT32, {4}); + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 4}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); // Phase 1, operands auto op1 = model->addOperand(&type0); - auto op2 = model->addOperand(&type1); - auto op3 = model->addOperand(&type2); - auto pad0 = model->addOperand(&type3); - auto act = model->addOperand(&type3); - auto stride = model->addOperand(&type3); - auto channelMultiplier = model->addOperand(&type3); - auto op4 = model->addOperand(&type4); + auto op2 = model->addOperand(&type0); + auto op3 = model->addOperand(&type1); + auto pad0 = model->addOperand(&type2); + auto act = model->addOperand(&type2); + auto stride = model->addOperand(&type2); + auto channelMultiplier = model->addOperand(&type2); + auto op4 = model->addOperand(&type3); // Phase 2, operations static int32_t pad0_init[] = {0}; model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1); diff --git a/runtimes/tests/neural_networks_test/generated/models/div.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp new file mode 100644 index 000000000..31213de0f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: div.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp new file mode 100644 index 000000000..137a8b90b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div_.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: div_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp new file mode 100644 index 000000000..e6f442d09 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/div_broadcast_float.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: div_broadcast_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp new file mode 100644 index 000000000..0234e403f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_2d_nnfw.model.cpp @@ -0,0 +1,21 @@ +// Generated file (from: embedding_lookup_2d_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_FLOAT32, {3, 2}); + OperandType type0(Type::TENSOR_INT32, {3}); + // Phase 1, operands + auto index = model->addOperand(&type0); + auto value = model->addOperand(&type1); + auto output = model->addOperand(&type1); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_EMBEDDING_LOOKUP, {index, value}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {index, value}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp new file mode 100644 index 000000000..2acd291ae --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/embedding_lookup_4d_nnfw.model.cpp @@ -0,0 +1,22 @@ +// Generated file (from: embedding_lookup_4d_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {3, 2, 4, 2}); + OperandType type0(Type::TENSOR_INT32, {3}); + OperandType type1(Type::TENSOR_INT32, {5, 2, 4, 2}); + // Phase 1, operands + auto index = model->addOperand(&type0); + auto value = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_EMBEDDING_LOOKUP, {index, value}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {index, value}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp new file mode 100644 index 000000000..b54e9fc8f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/floor_.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: floor_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_FLOOR, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp new file mode 100644 index 000000000..04c4efece --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_1_nnfw.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1}); + OperandType type1(Type::TENSOR_FLOAT32, {1, 24}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 4, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto b0 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + auto act_relu = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {-0.25449711f, 0.0f, -2.1247749f, 0.0f, -1.143796f, 0.0f, -1.0299346f, 0.0f, -2.2373879f, 0.0f, -0.083096743f, 0.0f, -1.3230739f, 0.0f, 0.15294921f, 0.0f, -0.53045893f, 0.0f, -0.46075189f, 0.0f, -1.4482396f, 0.0f, -1.609534f, 0.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 24); + static float b0_init[] = {0.70098364f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 1); + static int32_t act_relu_init[] = {0}; + model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act_relu}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp new file mode 100644 index 000000000..15275251f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_3.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type1(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {1}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto b0 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + auto act = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {2.0f, 4.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 2); + static float b0_init[] = {1.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 1); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp new file mode 100644 index 000000000..aa645d966 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/fully_connected_float_4d_simple.model.cpp @@ -0,0 +1,32 @@ +// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type4(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_FLOAT32, {3, 10}); + OperandType type2(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 5, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto b0 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + auto act = model->addOperand(&type4); + // Phase 2, operations + static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f}; + model->setOperandValue(op2, op2_init, sizeof(float) * 30); + static float b0_init[] = {1.0f, 2.0f, 3.0f}; + model->setOperandValue(b0, b0_init, sizeof(float) * 3); + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp new file mode 100644 index 000000000..8ad160990 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_1D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp new file mode 100644 index 000000000..ae7fa6685 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: gather_1D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp new file mode 100644 index 000000000..4984c167b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_1D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_1D_uint8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp new file mode 100644 index 000000000..3d80c4496 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2,4}); + OperandType type0(Type::TENSOR_FLOAT32, {3,4}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp new file mode 100644 index 000000000..50411d5a7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_int32.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {2,4}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {3,4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp new file mode 100644 index 000000000..d7aa0aba7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/gather_2D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: gather_2D_uint8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2,4}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3,4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto axis = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_GATHER_EX, {op1, op2, axis}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp new file mode 100644 index 000000000..7d26f9fa8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 2, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp new file mode 100644 index 000000000..e14f6888a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_1_nnfw.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_axis01_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp new file mode 100644 index 000000000..26afa5aa5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_axis01_2_nnfw.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_axis01_2_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 2, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp new file mode 100644 index 000000000..7a3ce25a5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp new file mode 100644 index 000000000..9838db48b --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 1}); + OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp new file mode 100644 index 000000000..bbc6c101e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {1, 0, -3, -3}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4); + static int32_t keepDims_init[] = {0}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp new file mode 100644 index 000000000..dec9d81ca --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mean_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: mean_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3, 1}, 0.8, 5); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 3, 2}, 0.8, 5); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto keepDims = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t axis_init[] = {0, 2}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2); + static int32_t keepDims_init[] = {1}; + model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp new file mode 100644 index 000000000..b8a4120f1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_1_nnfw.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: mul_broadcast_3D_1D_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 1, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp new file mode 100644 index 000000000..c5d215fb8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/mul_broadcast_3D_1D_2_nnfw.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: mul_broadcast_3D_1D_2_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 2, 4}); + OperandType type1(Type::TENSOR_FLOAT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_MUL, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp new file mode 100644 index 000000000..97e173e21 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp new file mode 100644 index 000000000..61ae0b766 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/pad_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: pad_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 7, 1}); + OperandType type1(Type::TENSOR_INT32, {4, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t op2_init[] = {0, 0, 0, 2, 1, 3, 0, 0}; + model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8); + model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp new file mode 100644 index 000000000..4064c94a9 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp new file mode 100644 index 000000000..f4dfab99f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {4, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp new file mode 100644 index 000000000..44dee00ce --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 5, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 2, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp new file mode 100644 index 000000000..f2fa99042 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_float_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 2, 1}); + OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 4, 1}); + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp new file mode 100644 index 000000000..cfd56c2e7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_1.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 4, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {4, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {2, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {0, 0, 0, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp new file mode 100644 index 000000000..8ab61a116 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_2.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 5, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 2, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 0, 2, 0}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp new file mode 100644 index 000000000..7ee388441 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/space_to_batch_quant8_3.model.cpp @@ -0,0 +1,28 @@ +// Generated file (from: space_to_batch_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::TENSOR_INT32, {2, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 4, 2, 1}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {6, 2, 4, 1}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto block_size = model->addOperand(&type1); + auto paddings = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t block_size_init[] = {3, 2}; + model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2); + static int32_t paddings_init[] = {1, 1, 2, 4}; + model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp new file mode 100644 index 000000000..806a10c61 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {1, 2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp new file mode 100644 index 000000000..4d6621e21 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_2D_float_1_nnfw.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_2D_float_1_nnfw.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {4, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {1}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp new file mode 100644 index 000000000..2277e38e6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 24, 1}); + OperandType type2(Type::TENSOR_FLOAT32, {1, 24}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp new file mode 100644 index 000000000..f122d43f5 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/squeeze_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: squeeze_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 24, 1}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {1, 24}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto squeezeDims = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t squeezeDims_init[] = {2}; + model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp new file mode 100644 index 000000000..5f1b875c2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, 2}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp new file mode 100644 index 000000000..1385693c8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp new file mode 100644 index 000000000..5da568959 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp new file mode 100644 index 000000000..84c3fe65d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp new file mode 100644 index 000000000..a6067409d --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp new file mode 100644 index 000000000..497ed4ba7 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp new file mode 100644 index 000000000..568e03013 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp new file mode 100644 index 000000000..8333a4334 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp new file mode 100644 index 000000000..34f2d13fa --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_ex_float_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp new file mode 100644 index 000000000..6027abb1c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp new file mode 100644 index 000000000..de18b9d76 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_ex_float_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_ex_float_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_STRIDED_SLICE_EX, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp new file mode 100644 index 000000000..fcd2f6dac --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp new file mode 100644 index 000000000..1463f13ab --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp new file mode 100644 index 000000000..2197b502a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp new file mode 100644 index 000000000..47179ca53 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp new file mode 100644 index 000000000..113c775a3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp new file mode 100644 index 000000000..af5ffa891 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp new file mode 100644 index 000000000..a0280d3a8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp new file mode 100644 index 000000000..cb40c8527 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {3}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp new file mode 100644 index 000000000..1580128a1 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_float_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3}); + OperandType type1(Type::TENSOR_INT32, {1}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp new file mode 100644 index 000000000..0dd388435 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {1, 3}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp new file mode 100644 index 000000000..22e0e7028 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_float_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_float_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type3(Type::TENSOR_FLOAT32, {2, 2}); + OperandType type0(Type::TENSOR_FLOAT32, {2, 3}); + OperandType type1(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp new file mode 100644 index 000000000..a6eec78a4 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_10.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_10.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {2}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp new file mode 100644 index 000000000..170dc7e0f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_qaunt8_11.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_qaunt8_11.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {0, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {1, 3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {1}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp new file mode 100644 index 000000000..7f8e602eb --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_1.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp new file mode 100644 index 000000000..e6042147e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_2.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_2.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-3}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp new file mode 100644 index 000000000..2cc75a461 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_3.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_3.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {-5}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp new file mode 100644 index 000000000..2fe2277d6 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_4.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_4.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp new file mode 100644 index 000000000..1ed3ed107 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_5.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_5.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp new file mode 100644 index 000000000..73da2fc3a --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_6.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_6.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {3}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {1}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp new file mode 100644 index 000000000..089388bf2 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_7.model.cpp @@ -0,0 +1,39 @@ +// Generated file (from: strided_slice_quant8_7.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {1}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t begins_init[] = {-1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1); + static int32_t ends_init[] = {-4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1); + static int32_t strides_init[] = {-1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp new file mode 100644 index 000000000..ef55fc15f --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_8.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 3}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, -1}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, -4}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {2, -1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {0}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp new file mode 100644 index 000000000..37bb2898e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/strided_slice_quant8_9.model.cpp @@ -0,0 +1,40 @@ +// Generated file (from: strided_slice_quant8_9.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type1(Type::TENSOR_INT32, {2}); + OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 2}, 1.0, 0); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto begins = model->addOperand(&type1); + auto ends = model->addOperand(&type1); + auto strides = model->addOperand(&type1); + auto beginMask = model->addOperand(&type2); + auto endMask = model->addOperand(&type2); + auto shrinkAxisMask = model->addOperand(&type2); + auto output = model->addOperand(&type3); + // Phase 2, operations + static int32_t begins_init[] = {1, 0}; + model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2); + static int32_t ends_init[] = {2, 2}; + model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2); + static int32_t strides_init[] = {1, 1}; + model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2); + static int32_t beginMask_init[] = {1}; + model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1); + static int32_t endMask_init[] = {0}; + model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1); + static int32_t shrinkAxisMask_init[] = {0}; + model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp b/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp new file mode 100644 index 000000000..40a0247c8 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/sub.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: sub.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + auto act = model->addOperand(&type1); + auto op3 = model->addOperand(&type0); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp new file mode 100644 index 000000000..cf1f61a85 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/sub_broadcast_float.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: sub_broadcast_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type2(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {1, 2}); + OperandType type1(Type::TENSOR_FLOAT32, {2, 2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type1); + auto act = model->addOperand(&type2); + auto op3 = model->addOperand(&type1); + // Phase 2, operations + static int32_t act_init[] = {0}; + model->setOperandValue(act, act_init, sizeof(int32_t) * 1); + model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1, op2}, + {op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp new file mode 100644 index 000000000..c221ea627 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tanh_.model.cpp @@ -0,0 +1,19 @@ +// Generated file (from: tanh_.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto op2 = model->addOperand(&type0); + // Phase 2, operations + model->addOperation(ANEURALNETWORKS_TANH, {op1}, {op2}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp new file mode 100644 index 000000000..7d365de9e --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_float.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: tensorflowmax_ex_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_FLOAT32, {3, 4}); + OperandType type2(Type::TENSOR_FLOAT32, {3}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis_init[] = {1}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TENSORFLOW_MAX_EX, {input, axis}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp new file mode 100644 index 000000000..efb5923ae --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/tensorflowmax_ex_2D_int32.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: tensorflowmax_ex_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type0(Type::TENSOR_INT32, {3, 4}); + OperandType type2(Type::TENSOR_INT32, {3}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto axis = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t axis_init[] = {1}; + model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TENSORFLOW_MAX_EX, {input, axis}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp new file mode 100644 index 000000000..23168320c --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_1D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_FLOAT32, {2}); + OperandType type0(Type::TENSOR_FLOAT32, {4}); + OperandType type3(Type::TENSOR_INT32, {2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp new file mode 100644 index 000000000..5d11fed89 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: topk_v2_1D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_INT32, {2}); + OperandType type0(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp new file mode 100644 index 000000000..ff60c1d74 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_1D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_1D_quant8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp new file mode 100644 index 000000000..17097cd11 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_float.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_2D_float.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_FLOAT32, {3,2}); + OperandType type0(Type::TENSOR_FLOAT32, {3,4}); + OperandType type3(Type::TENSOR_INT32, {3,2}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp new file mode 100644 index 000000000..36e137e46 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_int32.model.cpp @@ -0,0 +1,25 @@ +// Generated file (from: topk_v2_2D_int32.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type2(Type::TENSOR_INT32, {3,2}); + OperandType type0(Type::TENSOR_INT32, {3,4}); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type2); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp new file mode 100644 index 000000000..a0ffc8946 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/topk_v2_2D_quant8.model.cpp @@ -0,0 +1,26 @@ +// Generated file (from: topk_v2_2D_quant8.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::INT32, {}); + OperandType type3(Type::TENSOR_INT32, {3,2}); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {3,2}, 0.5f, 1); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {3,4}, 0.5f, 1); + // Phase 1, operands + auto op1 = model->addOperand(&type0); + auto k = model->addOperand(&type1); + auto op2 = model->addOperand(&type2); + auto op3 = model->addOperand(&type3); + // Phase 2, operations + static int32_t k_init[] = {2}; + model->setOperandValue(k, k_init, sizeof(int32_t) * 1); + model->addOperationEx(ANEURALNETWORKS_TOPK_V2_EX, {op1, k}, {op2, op3}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {op1}, + {op2, op3}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp new file mode 100644 index 000000000..e4c741456 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose.model.cpp @@ -0,0 +1,23 @@ +// Generated file (from: transpose.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type0); + // Phase 2, operations + static int32_t perms_init[] = {0, 2, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp new file mode 100644 index 000000000..f6d0d08e3 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_float_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_float_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type0(Type::TENSOR_FLOAT32, {2, 3, 4, 5}); + OperandType type2(Type::TENSOR_FLOAT32, {4, 2, 3, 5}); + OperandType type1(Type::TENSOR_INT32, {4}); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} diff --git a/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp new file mode 100644 index 000000000..808ad2b38 --- /dev/null +++ b/runtimes/tests/neural_networks_test/generated/models/transpose_quant8_1.model.cpp @@ -0,0 +1,24 @@ +// Generated file (from: transpose_quant8_1.mod.py). Do not edit +void CreateModel(Model *model) { + OperandType type1(Type::TENSOR_INT32, {4}); + OperandType type0(Type::TENSOR_QUANT8_ASYMM, {2, 3, 4, 5}, 1.0, 0); + OperandType type2(Type::TENSOR_QUANT8_ASYMM, {4, 2, 3, 5}, 1.0, 0); + // Phase 1, operands + auto input = model->addOperand(&type0); + auto perms = model->addOperand(&type1); + auto output = model->addOperand(&type2); + // Phase 2, operations + static int32_t perms_init[] = {2, 0, 1, 3}; + model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4); + model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output}); + // Phase 3, inputs and outputs + model->identifyInputsAndOutputs( + {input}, + {output}); + assert(model->isValid()); +} + +bool is_ignored(int i) { + static std::set<int> ignore = {}; + return ignore.find(i) != ignore.end(); +} |