1 files changed, 82 insertions, 0 deletions
diff --git a/tests/nnapi/nnapi_test_generator/android-q-beta/tests/P_backward_compatibility_quant8/stdout.txt.expect b/tests/nnapi/nnapi_test_generator/android-q-beta/tests/P_backward_compatibility_quant8/stdout.txt.expect
new file mode 100644
index 000000000..9c54412de
--- /dev/null
+++ b/tests/nnapi/nnapi_test_generator/android-q-beta/tests/P_backward_compatibility_quant8/stdout.txt.expect
@@ -0,0 +1,82 @@
+// clang-format off
+// Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit
+// clang-format off
+// Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit
+// clang-format off
+// Generated file (from: depthwise_conv2d_quant8.mod.py). Do not edit
+#include "../../TestGenerated.h"
+
+namespace depthwise_conv2d_quant8 {
+// Generated depthwise_conv2d_quant8 test
+#include "-"
+// Generated model constructor
+#include "-"
+} // namespace depthwise_conv2d_quant8
+
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 2}, 0.5f, 0);
+  OperandType type1(Type::TENSOR_INT32, {2}, 0.25f, 0);
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_QUANT8_ASYMM, {1, 1, 1, 2}, 1.0f, 0);
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto op3 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type2);
+  auto stride = model->addOperand(&type2);
+  auto channelMultiplier = model->addOperand(&type2);
+  auto act = 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);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {1};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
+
+std::vector<MixedTypedExample> examples = {
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {{2, {0, 0}}},
+  // int -> QUANT8_ASYMM map
+  {{0, {4, 16, 4, 32, 4, 64, 4, 128}}, {1, {2, 4, 2, 0, 2, 2, 2, 0}}}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {{0, {8, 48}}}
+}
+}, // End of an example
+};
+
+TEST_F(GeneratedTests, depthwise_conv2d_quant8) {
+    execute(depthwise_conv2d_quant8::CreateModel,
+            depthwise_conv2d_quant8::is_ignored,
+            depthwise_conv2d_quant8::examples);
+}
+
+#include "../generated/tests/depthwise_conv2d_quant8.mod.py.cpp"