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Make GetTensorShapeFromTensorShapeProto return TensorShape and not it's internal representation. (#1353)

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Pranav Sharma 2019-07-08 11:45:55 -07:00 committed by GitHub
parent 5b93b02c69
commit e9ce51ead4
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GPG key ID: 4AEE18F83AFDEB23
9 changed files with 20 additions and 15 deletions
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1
include/onnxruntime/core/framework/tensor_shape.h
View file

@ -37,6 +37,7 @@ class TensorShape : private std::vector<int64_t> {
TensorShape(const int64_t* dimension_sizes, size_t dimension_count);
TensorShape(const std::vector<int64_t>& dims);
TensorShape(std::vector<int64_t>&& dims);
TensorShape(const std::initializer_list<int64_t>& dims);

14
onnxruntime/core/framework/tensor_shape.cc
View file

@ -11,6 +11,9 @@ namespace onnxruntime {
TensorShape::TensorShape(const std::vector<int64_t>& dims) : std::vector<int64_t>(dims) {
}
TensorShape::TensorShape(std::vector<int64_t>&& dims) : std::vector<int64_t>(dims) {
}
TensorShape::TensorShape(const std::initializer_list<int64_t>& dims) : std::vector<int64_t>(dims) {
}
@ -20,7 +23,6 @@ TensorShape::TensorShape(const int64_t* dimension_sizes, size_t dimension_count)
}
}
TensorShape::TensorShape(const std::vector<int64_t>& dims, size_t start, size_t end) {
assign(dims.begin() + start, dims.begin() + end);
}
@ -38,8 +40,8 @@ int64_t TensorShape::Size() const {
int64_t TensorShape::SizeToDimension(size_t dimension) const {
const size_t num_dims = size();
ORT_ENFORCE(dimension <= num_dims,
"Invalid dimension of ", dimension, " for SizeFromDimension. Tensor has ",
num_dims, " dimensions.");
"Invalid dimension of ", dimension, " for SizeFromDimension. Tensor has ",
num_dims, " dimensions.");
int64_t size = SizeHelper(0, dimension);
return size;
@ -48,8 +50,8 @@ int64_t TensorShape::SizeToDimension(size_t dimension) const {
int64_t TensorShape::SizeFromDimension(size_t dimension) const {
const size_t num_dims = size();
ORT_ENFORCE(dimension <= num_dims,
"Invalid dimension of ", dimension, " for SizeFromDimension. Tensor has ",
num_dims, " dimensions.");
"Invalid dimension of ", dimension, " for SizeFromDimension. Tensor has ",
num_dims, " dimensions.");
int64_t size = SizeHelper(dimension, num_dims);
return size;
@ -57,7 +59,7 @@ int64_t TensorShape::SizeFromDimension(size_t dimension) const {
TensorShape TensorShape::Slice(size_t dimstart, size_t dimend) const {
ORT_ENFORCE(dimstart <= dimend && dimend <= size(),
"Invalid tensor shape slice argument.");
"Invalid tensor shape slice argument.");
return TensorShape(*this, dimstart, dimend);
}

4
onnxruntime/core/framework/tensorprotoutils.cc
View file

@ -274,14 +274,14 @@ common::Status GetSizeInBytesFromTensorProto(const ONNX_NAMESPACE::TensorProto&
return Status::OK();
}
std::vector<int64_t> GetTensorShapeFromTensorShapeProto(const ONNX_NAMESPACE::TensorShapeProto& tensor_shape_proto) {
TensorShape GetTensorShapeFromTensorShapeProto(const ONNX_NAMESPACE::TensorShapeProto& tensor_shape_proto) {
const auto& dims = tensor_shape_proto.dim();
std::vector<int64_t> tensor_shape_vec(static_cast<size_t>(dims.size()));
for (int i = 0; i < dims.size(); ++i) {
tensor_shape_vec[i] = dims[i].has_dim_param() ? -1 /* symbolic dimensions are represented as -1 in onnxruntime*/
: dims[i].dim_value();
}
return tensor_shape_vec;
return TensorShape(std::move(tensor_shape_vec));
}
struct UnInitializeParam {

2
onnxruntime/core/framework/tensorprotoutils.h
View file

@ -24,7 +24,7 @@ class TensorShapeProto;
namespace onnxruntime {
class Tensor;
namespace utils {
std::vector<int64_t> GetTensorShapeFromTensorShapeProto(const ONNX_NAMESPACE::TensorShapeProto& tensor_shape_proto);
TensorShape GetTensorShapeFromTensorShapeProto(const ONNX_NAMESPACE::TensorShapeProto& tensor_shape_proto);
/**
* deserialize a TensorProto into a preallocated memory buffer.
* \param tensor_proto_path A local file path of where the 'input' was loaded from. Can be NULL if the tensor proto doesn't

2
onnxruntime/core/providers/cpu/controlflow/if.cc
View file

@ -156,7 +156,7 @@ Status IfImpl::AllocateOutputTensors() {
graph_output->Name(), " did not.");
}
TensorShape output_shape{onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape)};
TensorShape output_shape = onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape);
// if size < 0 we have a symbolic dimension and need to use a temporary OrtValue in the subgraph execution
if (output_shape.Size() < 0) {

3
onnxruntime/core/providers/cpu/controlflow/loop.cc
View file

@ -422,7 +422,8 @@ Status LoopImpl::Execute(FeedsFetchesManager* ffm, const FeedsFetchesManager* ca
if (graph_output_shape) {
output_dims.reserve(graph_output_shape->dim_size() + 1);
auto dims = onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape);
const auto& tensor_shape = onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape);
const auto& dims = tensor_shape.GetDims();
std::copy(dims.cbegin(), dims.cend(), std::back_inserter(output_dims));
} else {
// TODO: We could try and call ExecuteGraph to get the output shape from fetches so the rank is correct,

2
onnxruntime/core/providers/cpu/controlflow/scan_utils.cc
View file

@ -61,7 +61,7 @@ Status AllocateOutput(OpKernelContextInternal& context, const GraphViewer& subgr
graph_output->Name(), " did not.");
}
TensorShape output_shape{onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape)};
TensorShape output_shape = onnxruntime::utils::GetTensorShapeFromTensorShapeProto(*graph_output_shape);
auto& graph_output_dims{output_shape.GetDims()};
std::vector<int64_t> scan_output_dims;

4
onnxruntime/test/framework/inference_session_test.cc
View file

@ -348,8 +348,8 @@ static bool Compare(const InputDefList& f_arg, const InputDefList& s_arg) {
if (!x->Shape()) {
continue;
}
vector<int64_t> x_shape = utils::GetTensorShapeFromTensorShapeProto(*x->Shape());
vector<int64_t> y_shape = utils::GetTensorShapeFromTensorShapeProto(*y->Shape());
auto x_shape = utils::GetTensorShapeFromTensorShapeProto(*x->Shape());
auto y_shape = utils::GetTensorShapeFromTensorShapeProto(*y->Shape());
if (x->Name() == y->Name() && x_shape == y_shape && *x->Type() == *y->Type()) {
continue;
}

3
onnxruntime/test/providers/provider_test_utils.cc
View file

@ -338,7 +338,8 @@ void OpTester::ExecuteModel(Model& model, InferenceSession& session_object, Expe
if (add_shape_to_tensor_data_) {
auto out_shape_proto = expected_data.def_.Shape();
EXPECT_TRUE(out_shape_proto != nullptr);
auto inferred_dims = utils::GetTensorShapeFromTensorShapeProto(*out_shape_proto);
const auto& tensor_shape = utils::GetTensorShapeFromTensorShapeProto(*out_shape_proto);
const auto& inferred_dims = tensor_shape.GetDims();
const auto& expected_shape = expected_data.data_.Get<Tensor>().Shape();
EXPECT_TRUE(inferred_dims.size() == expected_shape.NumDimensions());
for (size_t d = 0; d < inferred_dims.size(); ++d) {