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Add test case for pre-allocated output

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This commit is contained in:
Changming Sun 2019-01-30 12:06:03 -08:00
parent 925b3f059c
commit 59955da188
1 changed files with 39 additions and 5 deletions
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44
onnxruntime/test/shared_lib/test_inference.cc
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@ -17,7 +17,8 @@ void RunSession(OrtAllocator* env, OrtSession* session_object,
const std::vector<size_t>& dims_x,
const std::vector<float>& values_x,
const std::vector<int64_t>& dims_y,
const std::vector<float>& values_y) {
const std::vector<float>& values_y,
OrtValue* output_tensor) {
std::unique_ptr<OrtValue, decltype(&OrtReleaseValue)> value_x(nullptr, OrtReleaseValue);
std::vector<OrtValue*> inputs(1);
inputs[0] = OrtCreateTensorAsOrtValue(env, dims_x, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);
@ -26,10 +27,13 @@ void RunSession(OrtAllocator* env, OrtSession* session_object,
ORT_THROW_ON_ERROR(OrtGetTensorMutableData(inputs[0], &raw_data));
memcpy(raw_data, values_x.data(), values_x.size() * sizeof(values_x[0]));
std::vector<const char*> input_names{"X"};
OrtValue* output_tensor = nullptr;
const char* output_names[] = {"Y"};
bool is_output_allocated_by_ort = output_tensor == nullptr;
OrtValue* old_output_ptr = output_tensor;
ORT_THROW_ON_ERROR(OrtRun(session_object, NULL, input_names.data(), inputs.data(), inputs.size(), output_names, 1, &output_tensor));
ASSERT_NE(output_tensor, nullptr);
if (!is_output_allocated_by_ort)
ASSERT_EQ(output_tensor, old_output_ptr);
std::unique_ptr<OrtTensorTypeAndShapeInfo> shape_info;
{
OrtTensorTypeAndShapeInfo* shape_info_ptr;
@ -50,7 +54,7 @@ void RunSession(OrtAllocator* env, OrtSession* session_object,
for (size_t i = 0; i != total_len; ++i) {
ASSERT_EQ(values_y[i], f[i]);
}
OrtReleaseValue(output_tensor);
if (is_output_allocated_by_ort) OrtReleaseValue(output_tensor);
}
template <typename T>
@ -89,10 +93,40 @@ void TestInference(OrtEnv* env, T model_uri,
if (custom_op) {
sf.AppendCustomOpLibPath("libonnxruntime_custom_op_shared_lib_test.so");
}
std::unique_ptr<OrtSession, decltype(&OrtReleaseSession)> inference_session(sf.OrtCreateSession(model_uri), OrtReleaseSession);
std::unique_ptr<OrtSession, decltype(&OrtReleaseSession)>
inference_session(sf.OrtCreateSession(model_uri), OrtReleaseSession);
std::unique_ptr<MockedOrtAllocator> default_allocator(std::make_unique<MockedOrtAllocator>());
// Now run
RunSession(default_allocator.get(), inference_session.get(), dims_x, values_x, expected_dims_y, expected_values_y);
//without preallocated output tensor
RunSession(default_allocator.get(),
inference_session.get(),
dims_x,
values_x,
expected_dims_y,
expected_values_y,
nullptr);
//with preallocated output tensor
std::unique_ptr<OrtValue, decltype(&OrtReleaseValue)> value_y(nullptr, OrtReleaseValue);
{
std::vector<OrtValue*> allocated_outputs(1);
std::vector<size_t> dims_y(expected_dims_y.size());
for (size_t i = 0; i != expected_dims_y.size(); ++i) {
dims_y[i] = static_cast<size_t>(expected_dims_y[i]);
}
allocated_outputs[0] =
OrtCreateTensorAsOrtValue(default_allocator.get(), dims_y, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);
value_y.reset(allocated_outputs[0]);
}
//test it twice
for (int i = 0; i != 2; ++i)
RunSession(default_allocator.get(),
inference_session.get(),
dims_x,
values_x,
expected_dims_y,
expected_values_y,
value_y.get());
}
static constexpr PATH_TYPE MODEL_URI = TSTR("testdata/mul_1.pb");