Update to onnx 1.16.1 (#20702)

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liqun Fu 2024-06-04 11:06:28 -07:00 committed by GitHub
parent 3dd6fcc089
commit 51bc53580d
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14 changed files with 22 additions and 110 deletions

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@ -26,7 +26,7 @@
"component": {
"type": "git",
"git": {
"commitHash": "990217f043af7222348ca8f0301e17fa7b841781",
"commitHash": "595228d99e3977ac27cb79d5963adda262af99ad",
"repositoryUrl": "https://github.com/onnx/onnx.git"
},
"comments": "git submodule at cmake/external/onnx"
@ -216,7 +216,7 @@
"component": {
"type": "git",
"git": {
"commitHash": "eb43908b02a296ea0594432f06e9d3fac288d672",
"commitHash": "06adf4461ac84035bee658c6cf5df39f7ab6071d",
"repositoryUrl": "https://github.com/onnx/onnx-tensorrt.git"
},
"comments": "onnx_tensorrt"

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@ -36,7 +36,7 @@ microsoft_wil;https://github.com/microsoft/wil/archive/refs/tags/v1.0.230629.1.z
mimalloc;https://github.com/microsoft/mimalloc/archive/refs/tags/v2.1.1.zip;d5ee7d34223d0567892db5179849939c8769dc41
mp11;https://github.com/boostorg/mp11/archive/refs/tags/boost-1.82.0.zip;9bc9e01dffb64d9e0773b2e44d2f22c51aace063
neural_speed;https://github.com/intel/neural-speed/archive/refs/tags/v0.3.zip;5ec64e3071edc7347ebd8a81679cf06e2bb9b851
onnx;https://github.com/onnx/onnx/archive/refs/tags/v1.16.0.zip;a6d8b619459fb4657f8bec7d1c6d95ad6d4c069d
onnx;https://github.com/onnx/onnx/archive/refs/tags/v1.16.1.zip;2eb9198bb352757d5ff13977cbe0634898e0837c
#use the latest commit of 10.0-GA
onnx_tensorrt;https://github.com/onnx/onnx-tensorrt/archive/06adf4461ac84035bee658c6cf5df39f7ab6071d.zip;46dceef659d75d276e7914a8057c2282269d5e7b
protobuf;https://github.com/protocolbuffers/protobuf/archive/refs/tags/v21.12.zip;7cf2733949036c7d52fda017badcab093fe73bfa

2
cmake/external/onnx vendored

@ -1 +1 @@
Subproject commit 990217f043af7222348ca8f0301e17fa7b841781
Subproject commit 595228d99e3977ac27cb79d5963adda262af99ad

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@ -36,15 +36,15 @@ index b847798e..a6c31904 100644
--- a/onnx/common/file_utils.h
+++ b/onnx/common/file_utils.h
@@ -6,7 +6,6 @@
#pragma once
-#include <filesystem>
#include <fstream>
#include <string>
@@ -17,8 +16,7 @@ namespace ONNX_NAMESPACE {
template <typename T>
void LoadProtoFromPath(const std::string proto_path, T& proto) {
- std::filesystem::path proto_u8_path = std::filesystem::u8path(proto_path);
@ -53,42 +53,6 @@ index b847798e..a6c31904 100644
if (!proto_stream.good()) {
fail_check("Unable to open proto file: ", proto_path, ". Please check if it is a valid proto. ");
}
diff --git a/onnx/defs/quantization/defs.cc b/onnx/defs/quantization/defs.cc
index 70b4a4db..98c11545 100644
--- a/onnx/defs/quantization/defs.cc
+++ b/onnx/defs/quantization/defs.cc
@@ -200,6 +200,9 @@ ONNX_OPERATOR_SET_SCHEMA(
.SetDoc(DequantizeLinear_ver21_doc)
.TypeAndShapeInferenceFunction([](ONNX_NAMESPACE::InferenceContext& ctx) {
propagateElemTypeFromInputToOutput(ctx, 1, 0);
+ if (!hasInputShape(ctx, 0)) {
+ return;
+ }
auto& input_shape = getInputShape(ctx, 0);
updateOutputShape(ctx, 0, input_shape);
}));
diff --git a/onnx/defs/quantization/old.cc b/onnx/defs/quantization/old.cc
index 3f2d6384..d2f7cfd8 100644
--- a/onnx/defs/quantization/old.cc
+++ b/onnx/defs/quantization/old.cc
@@ -130,6 +130,9 @@ ONNX_OPERATOR_SET_SCHEMA(
.SetDoc(DequantizeLinear_ver19_doc)
.TypeAndShapeInferenceFunction([](ONNX_NAMESPACE::InferenceContext& ctx) {
propagateElemTypeFromInputToOutput(ctx, 1, 0);
+ if (!hasInputShape(ctx, 0)) {
+ return;
+ }
auto& input_shape = getInputShape(ctx, 0);
updateOutputShape(ctx, 0, input_shape);
}));
@@ -181,7 +184,6 @@ ONNX_OPERATOR_SET_SCHEMA(
if (!hasInputShape(ctx, 0)) {
return;
}
-
auto& input_shape = getInputShape(ctx, 0);
updateOutputShape(ctx, 0, input_shape);
}));
diff --git a/onnx/onnx_pb.h b/onnx/onnx_pb.h
index 0aab3e26..398ac2d6 100644
--- a/onnx/onnx_pb.h
@ -96,7 +60,7 @@ index 0aab3e26..398ac2d6 100644
@@ -47,10 +47,28 @@
#define ONNX_API ONNX_IMPORT
#endif
+#if defined(__GNUC__)
+#pragma GCC diagnostic push
+
@ -116,61 +80,9 @@ index 0aab3e26..398ac2d6 100644
#else
#include "onnx/onnx.pb.h"
#endif
+#if defined(__GNUC__)
+#pragma GCC diagnostic pop
+#endif
+
#endif // ! ONNX_ONNX_PB_H
diff --git a/onnx/shape_inference/implementation.cc b/onnx/shape_inference/implementation.cc
index fab1faf2..8723dcd4 100644
--- a/onnx/shape_inference/implementation.cc
+++ b/onnx/shape_inference/implementation.cc
@@ -488,29 +488,29 @@ class ShapeInferenceImplBase {
ProcessCall(n, *(iter->second), ctx);
} else {
has_unsupported_op = true;
+ return;
}
} else {
has_unsupported_op = true;
+ return;
}
- if (!has_unsupported_op) {
- for (int i = 0; i < n.output_size(); ++i) {
- // skip type and shape propagation for missing optional outputs.
- if (!n.output(i).empty())
- UpdateType(n.output(i), ctx.getOutputType(i));
- }
- // Constant values are tracked to improve inference/checking for subsequent nodes.
- ProcessConstant(n);
- // If data-propagation is enabled, partial-evaluation (aka data-propagation) is performed
- // to improve inference/checking for subsequent nodes.
- if (options.enable_data_propagation && schema && schema->has_data_propagation_function()) {
- if (generated_shape_data_by_name == nullptr) {
- fail_shape_inference(
- "Container for generated shape data cannot be nullptr when enable_data_propagation option is set.");
- }
- DataPropagationContextImpl data_propagation_ctx(
- n, value_types_by_name, input_data_by_name, *generated_shape_data_by_name);
- schema->GetDataPropagationFunction()(data_propagation_ctx);
+ for (int i = 0; i < n.output_size(); ++i) {
+ // skip type and shape propagation for missing optional outputs.
+ if (!n.output(i).empty())
+ UpdateType(n.output(i), ctx.getOutputType(i));
+ }
+ // Constant values are tracked to improve inference/checking for subsequent nodes.
+ ProcessConstant(n);
+ // If data-propagation is enabled, partial-evaluation (aka data-propagation) is performed
+ // to improve inference/checking for subsequent nodes.
+ if (options.enable_data_propagation && schema && schema->has_data_propagation_function()) {
+ if (generated_shape_data_by_name == nullptr) {
+ fail_shape_inference(
+ "Container for generated shape data cannot be nullptr when enable_data_propagation option is set.");
}
+ DataPropagationContextImpl data_propagation_ctx(
+ n, value_types_by_name, input_data_by_name, *generated_shape_data_by_name);
+ schema->GetDataPropagationFunction()(data_propagation_ctx);
}
}
ONNX_CATCH(const ONNX_NAMESPACE::InferenceError& ex) {

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@ -1,7 +1,7 @@
optimum>=1.14.1
transformers>=4.33.2,<= 4.37.2
torch>=2.2.0
onnx==1.16.0
onnx==1.16.1
datasets>=2.8.0
protobuf==3.20.2
psutil
psutil

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@ -1,3 +1,3 @@
onnx==1.16.0
onnx==1.16.1
transformers>=4.36.2
onnxscript>=0.1.0.dev20240126

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@ -7,7 +7,7 @@ soundfile
librosa
optimum
onnxruntime-extensions>=0.9.0
onnx==1.16.0
onnx==1.16.1
protobuf==3.20.2
numpy==1.23.3
psutil

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@ -1,2 +1,2 @@
onnx==1.16.0
onnx==1.16.1
pytest

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@ -11,7 +11,7 @@ steps:
packageType: upack
feed: '/7424c8e4-5c62-490e-95c4-79446f31017c'
definition: '517c4f6f-5437-4392-a70d-4f15ec5be2f0'
version: 1.0.155
version: 1.0.156
downloadPath: $(Build.BinariesDirectory)/deps
# The private ADO project
@ -22,7 +22,7 @@ steps:
packageType: upack
feed: '/4c7631f5-24c0-4307-8822-1aa8f180c325'
definition: 'fd9dd5ad-b73e-4678-890e-edcf680dbc1a'
version: 1.0.155
version: 1.0.156
downloadPath: $(Build.BinariesDirectory)/deps
# You can add more ADO accounts at here.

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@ -5,7 +5,7 @@ mypy
pytest
setuptools>=68.2.2
wheel
onnx==1.16.0
onnx==1.16.1
protobuf==4.21.12
sympy==1.12
flatbuffers

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@ -5,7 +5,7 @@ mypy
pytest
setuptools>=68.2.2
wheel
onnx==1.16.0
onnx==1.16.1
protobuf==4.21.12
sympy==1.12
flatbuffers

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@ -5,7 +5,7 @@ mypy
pytest
setuptools>=68.2.2
wheel
onnx==1.16.0
onnx==1.16.1
protobuf==4.21.12
sympy==1.12
flatbuffers

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@ -5,7 +5,7 @@ mypy
pytest
setuptools>=68.2.2
wheel
onnx==1.16.0
onnx==1.16.1
protobuf==4.21.12
sympy==1.12
flatbuffers

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@ -6,7 +6,7 @@ mypy
pytest
setuptools==69.0.3
wheel==0.42.0
onnx==1.16.0
onnx==1.16.1
argparse
sympy==1.12
flatbuffers