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author | Chunseok Lee <chunseok.lee@samsung.com> | 2020-08-14 15:19:19 +0900 |
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committer | Chunseok Lee <chunseok.lee@samsung.com> | 2020-08-14 15:19:19 +0900 |
commit | 042b262b3633b6c0f577aed6cb4b980ad0c1dcf3 (patch) | |
tree | e79fb9ffe65b21bdc5863306db2757ab187a3306 /tests/nnfw_api/src/ModelTestDynamicTensor.cc | |
parent | 05e0ec30a632339a8533082476f27bda31ccde16 (diff) | |
download | nnfw-042b262b3633b6c0f577aed6cb4b980ad0c1dcf3.tar.gz nnfw-042b262b3633b6c0f577aed6cb4b980ad0c1dcf3.tar.bz2 nnfw-042b262b3633b6c0f577aed6cb4b980ad0c1dcf3.zip |
Imported Upstream version 1.8.0upstream/1.8.0submit/tizen/20200814.062151
Diffstat (limited to 'tests/nnfw_api/src/ModelTestDynamicTensor.cc')
-rw-r--r-- | tests/nnfw_api/src/ModelTestDynamicTensor.cc | 86 |
1 files changed, 43 insertions, 43 deletions
diff --git a/tests/nnfw_api/src/ModelTestDynamicTensor.cc b/tests/nnfw_api/src/ModelTestDynamicTensor.cc index 2f9ef318c..c1f4369d6 100644 --- a/tests/nnfw_api/src/ModelTestDynamicTensor.cc +++ b/tests/nnfw_api/src/ModelTestDynamicTensor.cc @@ -15,7 +15,7 @@ */ #include <gtest/gtest.h> -#include <nnfw_debug.h> +#include <nnfw_internal.h> #include "common.h" #include "fixtures.h" @@ -67,22 +67,22 @@ protected: { NNFW_STATUS res = nnfw_set_input(_session, 0, NNFW_TYPE_TENSOR_INT32, new_shape.data(), sizeof(int) * new_shape.size()); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); res = nnfw_set_output(_session, 0, NNFW_TYPE_TENSOR_FLOAT32, actual_output->data(), sizeof(float) * actual_output_size); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); } void prepare_and_set_input_output(const std::vector<int> &new_shape, int actual_output_size, std::vector<float> *actual_output) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); NNFW_STATUS res = NNFW_STATUS_ERROR; res = nnfw_prepare(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); set_input_output(new_shape, actual_output_size, actual_output); // real test case should start from calling nnfw_run() @@ -102,11 +102,11 @@ protected: if (no_run_error) { - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); // output shape check nnfw_tensorinfo info; - ASSERT_EQ(nnfw_output_tensorinfo(_session, 0, &info), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(_session, 0, &info)); ASSERT_EQ(info.rank, new_shape.size()); for (uint32_t d = 0; d < info.rank; ++d) ASSERT_EQ(info.dims[d], new_shape[d]); @@ -137,7 +137,7 @@ TEST_F(TestDynamicTensorReshapeModelLoaded, reshape_to_3x2) // Do inference NNFW_STATUS res = nnfw_run(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); // output value check for (int i = 0; i < expected.size(); ++i) @@ -163,10 +163,10 @@ TEST_F(TestDynamicTensorReshapeModelLoaded, neg_reshape_to_wrong_3x3) TEST_F(TestDynamicTensorReshapeModelLoaded, reshape_multiple_executions) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); NNFW_STATUS res = nnfw_prepare(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); std::vector<int> new_shape; std::vector<float> expected = {-1.5, -1.0, -0.5, 0.5, 1.0, 1.5}; @@ -184,10 +184,10 @@ TEST_F(TestDynamicTensorReshapeModelLoaded, reshape_multiple_executions) TEST_F(TestDynamicTensorReshapeModelLoaded, neg_reshape_multiple_executions) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); NNFW_STATUS res = nnfw_prepare(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); std::vector<int> new_shape; std::vector<float> expected = {-1.5, -1.0, -0.5, 0.5, 1.0, 1.5}; @@ -217,8 +217,8 @@ protected: const std::vector<float> &input1, std::vector<float> *actual_output, nnfw_tensorinfo input0_ti) { - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &input0_ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &input0_ti)); ASSERT_EQ(nnfw_set_input(_session, 0, NNFW_TYPE_TENSOR_FLOAT32, input0.data(), sizeof(float) * input0.size()), @@ -250,7 +250,7 @@ protected: */ TEST_F(TestInputUnknownDimInputConcatModelLoaded, concat_input0_to_2x3) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); const std::vector<float> input0 = {1, 2, 3}; // of shape [1, 3] const std::vector<float> input1 = {4, 5, 6, 7, 8, 9}; // of shape [2, 3] @@ -260,14 +260,14 @@ TEST_F(TestInputUnknownDimInputConcatModelLoaded, concat_input0_to_2x3) // input reshaping to [1, 3] nnfw_tensorinfo ti = {NNFW_TYPE_TENSOR_FLOAT32, 2, {1, 3}}; - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &ti)); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); set_input_output(_session, input0, input1, actual_output); // Do inference NNFW_STATUS res = nnfw_run(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); // output value check for (int i = 0; i < expected.size(); ++i) @@ -291,7 +291,7 @@ TEST_F(TestInputUnknownDimInputConcatModelLoaded, concat_input0_to_2x3) */ TEST_F(TestInputUnknownDimInputConcatModelLoaded, neg_concat_input0_to_wrong_shape) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); const std::vector<float> input0 = {1, 2, 3}; // of shape [3, 1], wrong shape const std::vector<float> input1 = {4, 5, 6, 7, 8, 9}; // of shape [2, 3] @@ -300,7 +300,7 @@ TEST_F(TestInputUnknownDimInputConcatModelLoaded, neg_concat_input0_to_wrong_sha // input reshaping to [3, 1] nnfw_tensorinfo ti = {NNFW_TYPE_TENSOR_FLOAT32, 2, {3, 1}}; - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &ti)); ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_ERROR); } @@ -330,7 +330,7 @@ using TestDynamicTensorApplyTensorInfoBinaryOp = TEST_F(TestDynamicTensorApplyTensorInfoBinaryOp, set_input_tensorinfo_after_compilation_add) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); // input reshaping to [2, 2, 3] nnfw_tensorinfo input0_ti = {NNFW_TYPE_TENSOR_FLOAT32, 3, {2, 2, 3}}; @@ -341,15 +341,15 @@ TEST_F(TestDynamicTensorApplyTensorInfoBinaryOp, set_input_tensorinfo_after_comp std::vector<float> expected_output = {1.1 * 2, 2.1 * 2, 3.1 * 2, 4.1 * 2, 5.1 * 2, 6.1 * 2, 7.1 * 2, 8.1 * 2, 9.1 * 2, 10.1 * 2, 11.1 * 2, 12.1 * 2}; - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &input0_ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &input0_ti)); set_input_output(_session, input0, input1, actual_output); // Do inference NNFW_STATUS res = nnfw_run(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); // output value check for (int i = 0; i < expected_output.size(); ++i) @@ -374,7 +374,7 @@ using TestDynamicTensorApplyTensorInfoUnaryOp = ValidationTestModelLoaded<NNPack TEST_F(TestDynamicTensorApplyTensorInfoUnaryOp, set_input_tensorinfo_after_compilation_neg) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); nnfw_tensorinfo input0_ti_original = {NNFW_TYPE_TENSOR_FLOAT32, 2, {4, 4}}; @@ -397,21 +397,21 @@ TEST_F(TestDynamicTensorApplyTensorInfoUnaryOp, set_input_tensorinfo_after_compi expected_output[i] = -1 * input0[i]; } - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); // input shape check { nnfw_tensorinfo ti = {}; - ASSERT_EQ(nnfw_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(_session, 0, &ti)); ASSERT_TRUE(tensorInfoEqual(input0_ti_original, ti)); } - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &input0_ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &input0_ti)); // input shape check { nnfw_tensorinfo ti = {}; - ASSERT_EQ(nnfw_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(_session, 0, &ti)); ASSERT_TRUE(tensorInfoEqual(input0_ti, ti)); } @@ -419,7 +419,7 @@ TEST_F(TestDynamicTensorApplyTensorInfoUnaryOp, set_input_tensorinfo_after_compi // Do inference NNFW_STATUS res = nnfw_run(_session); - ASSERT_EQ(res, NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(res); // output value check for (int i = 0; i < expected_output.size(); ++i) @@ -435,20 +435,20 @@ const static std::vector<float> while_dynamic_output0{ 0.0388205424, 0.042615629 TEST_F(TestWhileDynamicModelLoaded, run_verify) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); std::vector<float> actual_output0(10); nnfw_tensorinfo ti = {NNFW_TYPE_TENSOR_FLOAT32, 3, {1, 28, 28}}; - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &ti)); set_input_output(_session, while_dynamic_input0, actual_output0); - ASSERT_EQ(nnfw_run(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_run(_session)); nnfw_tensorinfo ti_output0_expected = {NNFW_TYPE_TENSOR_FLOAT32, 2, {1, 10}}; - ASSERT_EQ(nnfw_output_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(_session, 0, &ti)); ASSERT_TRUE(tensorInfoEqual(ti, ti_output0_expected)); // output value check @@ -458,11 +458,11 @@ TEST_F(TestWhileDynamicModelLoaded, run_verify) TEST_F(TestWhileDynamicModelLoaded, neg_run_verify) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); nnfw_tensorinfo ti = {NNFW_TYPE_TENSOR_FLOAT32, 3, {1, 28, 28}}; - ASSERT_EQ(nnfw_set_input_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(_session, 0, &ti)); // Insufficient size of output (10 or more is sufficient) std::vector<float> actual_output0(9); @@ -482,27 +482,27 @@ const static std::vector<float> if_dynamic_output0{ 0.0444660522, 0.0271649156, TEST_F(TestIfDynamicModelLoaded, run_verify) { - ASSERT_EQ(nnfw_set_available_backends(_session, "cpu"), NNFW_STATUS_NO_ERROR); - ASSERT_EQ(nnfw_prepare(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(_session, "cpu")); + NNFW_ENSURE_SUCCESS(nnfw_prepare(_session)); nnfw_tensorinfo ti_output0_expected = {NNFW_TYPE_TENSOR_FLOAT32, 2, {1, 10}}; // Output tensor sizes are inferenced after `nnfw_prepare` { nnfw_tensorinfo ti; - ASSERT_EQ(nnfw_output_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(_session, 0, &ti)); ASSERT_TRUE(tensorInfoEqual(ti, ti_output0_expected)); } std::vector<float> actual_output0(10); set_input_output(_session, if_dynamic_input0, actual_output0); - ASSERT_EQ(nnfw_run(_session), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_run(_session)); // Check output tensor sizes again { nnfw_tensorinfo ti; - ASSERT_EQ(nnfw_output_tensorinfo(_session, 0, &ti), NNFW_STATUS_NO_ERROR); + NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(_session, 0, &ti)); ASSERT_TRUE(tensorInfoEqual(ti, ti_output0_expected)); } |