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Merged
snnn merged 2 commits into from
Dec 18, 2018
Merged

update onnx #209

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ba97182
update onnx
Dec 18, 2018
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sync
Dec 18, 2018
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2 changes: 1 addition & 1 deletion cmake/external/onnx
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Submodule onnx updated 19 files
+3 −3 docs/IR.md
+3 −3 onnx/common/ir.h
+3 −3 onnx/common/tensor.h
+9 −10 onnx/defs/data_type_utils.cc
+2 −2 onnx/defs/data_type_utils.h
+1 −1 onnx/defs/shape_inference.h
+13 −13 onnx/examples/Protobufs.ipynb
+2 −2 onnx/examples/check_model.ipynb
+2 −2 onnx/examples/load_model.ipynb
+2 −2 onnx/examples/make_model.ipynb
+2 −2 onnx/examples/np_array_tensorproto.ipynb
+1 −1 onnx/examples/shape_inference.ipynb
+2 −2 onnx/helper.py
+42 −42 onnx/mapping.py
+8 −4 onnx/onnx-ml.proto
+8 −4 onnx/onnx-ml.proto3
+8 −4 onnx/onnx.in.proto
+4 −2 onnx/onnx.proto
+4 −2 onnx/onnx.proto3
2 changes: 1 addition & 1 deletion onnxruntime/core/framework/onnxruntime_typeinfo.cc
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Expand Up @@ -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>();
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4 changes: 2 additions & 2 deletions onnxruntime/core/graph/contrib_ops/range_schema_defs.cc
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Expand Up @@ -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);
Expand Down Expand Up @@ -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);
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8 changes: 4 additions & 4 deletions onnxruntime/core/graph/graph.cc
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Expand Up @@ -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();
Expand All @@ -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();
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6 changes: 3 additions & 3 deletions onnxruntime/core/graph/initializer.h
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Expand Up @@ -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_;
}

Expand Down Expand Up @@ -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_;
Expand Down
14 changes: 7 additions & 7 deletions onnxruntime/core/protobuf/onnx-ml.proto
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Expand Up @@ -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
Expand Down Expand Up @@ -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;
}

Expand All @@ -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;
};
Expand All @@ -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;
}

Expand Down
2 changes: 1 addition & 1 deletion onnxruntime/test/util/compare_mlvalue.cc
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Expand Up @@ -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)
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4 changes: 2 additions & 2 deletions tools/ci_build/github/linux/docker/scripts/install_deps.sh
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Expand Up @@ -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
Expand Down