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update onnx (#209)

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* update onnx
This commit is contained in:
Changming Sun 2018-12-18 14:50:28 -08:00 committed by GitHub
parent 37b74c771a
commit dc8b37f4c4
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8 changed files with 21 additions and 21 deletions
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2
cmake/external/onnx vendored

@ -1 +1 @@
Subproject commit 0a4d5abdf4939ab0842a5eadcc16a3bf0738f901
Subproject commit 0c8d857bb162431912b255d5c0e773fb7c131a65

2
onnxruntime/core/framework/onnxruntime_typeinfo.cc
View file

@ -52,7 +52,7 @@ OrtStatus* OrtTypeInfo::FromDataTypeImpl(const onnxruntime::DataTypeImpl* input,
return OrtCreateStatus(ORT_NOT_IMPLEMENTED, "not implemented");
}
const DataTypeImpl* ElementTypeFromProto(ONNX_NAMESPACE::TensorProto_DataType type) {
const DataTypeImpl* ElementTypeFromProto(int type) {
switch (type) {
case ONNX_NAMESPACE::TensorProto_DataType_FLOAT:
return DataTypeImpl::GetType<float>();

4
onnxruntime/core/graph/contrib_ops/range_schema_defs.cc
View file

@ -81,7 +81,7 @@ static int64_t CalcRangeDim(const TensorProto* startShapeInitializer,
static int64_t CalcResultDim(const TensorProto* startShapeInitializer,
const TensorProto* limitShapeInitializer,
const TensorProto* deltaShapeInitializer,
TensorProto_DataType dtype) {
int dtype) {
int64_t dim = -1LL;
if (dtype == TensorProto::FLOAT) {
dim = CalcRangeDim<float>(startShapeInitializer, limitShapeInitializer, deltaShapeInitializer);
@ -146,7 +146,7 @@ OpSchema& RegisterRangeOpSchema(OpSchema&& op_schema){
const TensorProto* limitShapeInitializer = ctx.getInputData(1);
const TensorProto* deltaShapeInitializer = (ctx.getNumInputs() > 2) ? ctx.getInputData(2) : nullptr;
const auto& startTensorType = ctx.getInputType(0)->tensor_type();
TensorProto_DataType dtype = startTensorType.elem_type();
int dtype = startTensorType.elem_type();
int64_t n = CalcResultDim(startShapeInitializer, limitShapeInitializer, deltaShapeInitializer, dtype);
dim.set_dim_value(n);

8
onnxruntime/core/graph/graph.cc
View file

@ -152,8 +152,8 @@ common::Status NodeArg::UpdateTypeAndShape(const ONNX_NAMESPACE::TypeProto& inpu
if (input_tensor_elem_type != current_tensor_elem_type)
return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Tensor element type mismatch. ",
TensorProto_DataType_Name(input_tensor_elem_type), " != ",
TensorProto_DataType_Name(current_tensor_elem_type));
TensorProto_DataType_Name(static_cast<TensorProto_DataType>(input_tensor_elem_type)), " != ",
TensorProto_DataType_Name(static_cast<TensorProto_DataType>(current_tensor_elem_type)));
if (input_tensor_type.has_shape()) {
auto& current_tensor_type = *current_type.mutable_tensor_type();
@ -172,8 +172,8 @@ common::Status NodeArg::UpdateTypeAndShape(const ONNX_NAMESPACE::TypeProto& inpu
const auto current_tensor_elem_type = current_type.sparse_tensor_type().elem_type();
if (input_tensor_elem_type != current_tensor_elem_type) {
return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "SparseTensor element type mismatch. ",
TensorProto_DataType_Name(input_tensor_elem_type), " != ",
TensorProto_DataType_Name(current_tensor_elem_type));
TensorProto_DataType_Name(static_cast<TensorProto_DataType>(input_tensor_elem_type)), " != ",
TensorProto_DataType_Name(static_cast<TensorProto_DataType>(current_tensor_elem_type)));
}
if (input_tensor_type.has_shape()) {
auto& current_tensor_type = *current_type.mutable_sparse_tensor_type();

6
onnxruntime/core/graph/initializer.h
View file

@ -128,11 +128,11 @@ class Initializer final {
}
}
ONNX_NAMESPACE::TensorProto_DataType data_type() const {
int data_type() const {
return data_type_;
}
ONNX_NAMESPACE::TensorProto_DataType& data_type() {
int& data_type() {
return data_type_;
}
@ -372,7 +372,7 @@ class Initializer final {
}
private:
ONNX_NAMESPACE::TensorProto_DataType data_type_;
int data_type_;
std::string name_;
std::vector<int64_t> dims_;
int64_t size_;

14
onnxruntime/core/protobuf/onnx-ml.proto
View file

@ -330,7 +330,7 @@ message TensorProto {
repeated int64 dims = 1;
// The data type of the tensor.
optional DataType data_type = 2;
optional int32 data_type = 2;
// For very large tensors, we may want to store them in chunks, in which
// case the following fields will specify the segment that is stored in
@ -438,7 +438,7 @@ message TypeProto {
message Tensor {
// This field MUST NOT have the value of UNDEFINED
// This field MUST be present for this version of the IR.
optional TensorProto.DataType elem_type = 1;
optional int32 elem_type = 1;
optional TensorShapeProto shape = 2;
}
@ -454,7 +454,7 @@ message TypeProto {
message Map {
// This field MUST be present for this version of the IR.
// This field MUST refer to an integral type ([U]INT{8|16|32|64}) or STRING
optional TensorProto.DataType key_type = 1;
optional int32 key_type = 1;
// This field MUST be present for this version of the IR.
optional TypeProto value_type = 2;
};
@ -469,10 +469,10 @@ message TypeProto {
// repeated TypeProto parameters = 3;
}
message SparseTensor {
// This field MUST NOT have the value of UNDEFINED
// This field MUST be present for this version of the IR.
optional TensorProto.DataType elem_type = 1;
message SparseTensor {
// This field MUST NOT have the value of UNDEFINED
// This field MUST be present for this version of the IR.
optional int32 elem_type = 1;
optional TensorShapeProto shape = 2;
}

2
onnxruntime/test/util/compare_mlvalue.cc
View file

@ -26,7 +26,7 @@ using namespace onnxruntime;
namespace {
ONNXTensorElementDataType CApiElementTypeFromProto(ONNX_NAMESPACE::TensorProto_DataType type) {
ONNXTensorElementDataType CApiElementTypeFromProto(int type) {
switch (type) {
CASE_TYPE(FLOAT)
CASE_TYPE(UINT8)

4
tools/ci_build/github/linux/docker/scripts/install_deps.sh
View file

@ -33,8 +33,8 @@ else
#Install ONNX
#5af210ca8a1c73aa6bae8754c9346ec54d0a756e is v1.2.3
#bae6333e149a59a3faa9c4d9c44974373dcf5256 is v1.3.0
#0a4d5abdf4939ab0842a5eadcc16a3bf0738f901 is v1.3.0 latest
for onnx_version in "5af210ca8a1c73aa6bae8754c9346ec54d0a756e" "bae6333e149a59a3faa9c4d9c44974373dcf5256" "0a4d5abdf4939ab0842a5eadcc16a3bf0738f901"; do
#0c8d857bb162431912b255d5c0e773fb7c131a65 is v1.3.0 latest
for onnx_version in "5af210ca8a1c73aa6bae8754c9346ec54d0a756e" "bae6333e149a59a3faa9c4d9c44974373dcf5256" "0c8d857bb162431912b255d5c0e773fb7c131a65"; do
if [ -z ${lastest_onnx_version+x} ]; then
echo "first pass";
else