Add patch for ONNX 1.16.0 shape inference bug (#20316)

### Description
- Adds a patch that fixes a shape inference bug that caused a segfault:
https://github.com/onnx/onnx/pull/6080
- Fix documentation describing why QLinearMatMul tests are currently
being skipped.



### Motivation and Context
The [PR for integrating with ONNX
1.16.0](https://github.com/microsoft/onnxruntime/pull/19745) disabled
various python quantization tests due to a shape inference bug. This PR
applies the ONNX fix as a patch. We still can't enable the tests because
some of our CIs pip install onnx-1.16.0, which doesn't include the fix.

cmake/patches/onnx/onnx.patch

@@ -1,8 +1,8 @@
-diff --git a/CMakeLists.txt b/CMakeLists.txt
-index 4dd56b6e..018da488 100644
+diff --git a/CMakeLists.txt b/CMakeLists.txt
+index 6d7ca846..69aa622f 100644
 --- a/CMakeLists.txt
 +++ b/CMakeLists.txt
-@@ -397,6 +397,7 @@ if (MSVC)
+@@ -499,6 +499,7 @@ if (MSVC)
    endif()
  else()
    # On non-Windows, hide all symbols we don't need
@@ -10,7 +10,7 @@ index 4dd56b6e..018da488 100644
    set(ONNX_API_DEFINE "-DONNX_API=__attribute__\(\(__visibility__\(\"default\"\)\)\)")
    set_target_properties(onnx_proto PROPERTIES CXX_VISIBILITY_PRESET hidden)
    set_target_properties(onnx_proto PROPERTIES VISIBILITY_INLINES_HIDDEN 1)
-@@ -548,20 +549,9 @@ endif()
+@@ -653,20 +654,9 @@ endif()
  if(MSVC)
    target_compile_options(onnx_proto
                           PRIVATE /MP
@@ -31,14 +31,72 @@ index 4dd56b6e..018da488 100644
                                   ${EXTRA_FLAGS})
    if(ONNX_USE_PROTOBUF_SHARED_LIBS)
        target_compile_options(onnx_proto
+diff --git a/onnx/common/file_utils.h b/onnx/common/file_utils.h
+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);
+-  std::fstream proto_stream(proto_u8_path, std::ios::in | std::ios::binary);
++  std::fstream proto_stream(proto_path, std::ios::in | std::ios::binary);
+   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..0f859267 100644
+index 0aab3e26..398ac2d6 100644
 --- a/onnx/onnx_pb.h
 +++ b/onnx/onnx_pb.h
 @@ -47,10 +47,28 @@
  #define ONNX_API ONNX_IMPORT
  #endif
-
+ 
 +#if defined(__GNUC__)
 +#pragma GCC diagnostic push
 +
@@ -58,34 +116,12 @@ index 0aab3e26..0f859267 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/common/file_utils.h b/onnx/common/file_utils.h
-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);
--  std::fstream proto_stream(proto_u8_path, std::ios::in | std::ios::binary);
-+  std::fstream proto_stream(proto_path, std::ios::in | std::ios::binary);
-   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/shape_inference/implementation.cc b/onnx/shape_inference/implementation.cc
 index fab1faf2..8723dcd4 100644
 --- a/onnx/shape_inference/implementation.cc

onnxruntime/test/python/quantization/test_op_gemm.py

@@ -318,7 +318,7 @@ class TestOpGemm(unittest.TestCase):
             weight_type=QuantType.QUInt8,
         )
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #6049")
+    @unittest.skip(reason="Shape inference bug, see onnx PR #6080")
     def test_quantize_qop_gemm_s8s8(self):
         np.random.seed(1)
         model_fp32_path = "gemm_fp32.onnx"
@@ -366,7 +366,7 @@ class TestOpGemm(unittest.TestCase):
             calibrate_method=CalibrationMethod.Distribution,
         )
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #6049")
+    @unittest.skip(reason="Shape inference bug, see onnx PR #6080")
     def test_quantize_qop_gemm_e4m3fn_same(self):
         np.random.seed(1)
         model_fp32_path = "gemm_fp32.onnx"
@@ -397,7 +397,7 @@ class TestOpGemm(unittest.TestCase):
             calibrate_method=CalibrationMethod.Distribution,
         )
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #6049")
+    @unittest.skip(reason="Shape inference bug, see onnx PR #6080")
     def test_quantize_qop_gemm_e4m3fn_p3(self):
         np.random.seed(1)
         model_fp32_path = "gemm_fp32.onnx"

onnxruntime/test/python/quantization/test_op_matmul.py

@@ -347,7 +347,7 @@ class TestOpMatMul(unittest.TestCase):
     def test_quantize_matmul_u8u8(self):
         self.quantize_matmul_u8u8(onnx.TensorProto.FLOAT, 18, 8)
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #5709")
+    @unittest.skip(reason="QLinearMatMul(21), which supports float16, is not implemented in ORT.")
     @skip_if_new_opset_exception_raised
     def test_quantize_matmul_u8u8_f16(self):
         self.quantize_matmul_u8u8(onnx.TensorProto.FLOAT16, 21, 9)
@@ -393,22 +393,22 @@ class TestOpMatMul(unittest.TestCase):
     def test_quantize_matmul_s8s8_distribution(self):
         self.quantize_matmul_s8s8(onnx.TensorProto.FLOAT, 18, 8, calibrate_method=CalibrationMethod.Distribution)
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #5709")
+    @unittest.skip(reason="QLinearMatMul(21), which supports float16, is not implemented in ORT.")
     @skip_if_new_opset_exception_raised
     def test_quantize_matmul_s8s8_f16(self):
         self.quantize_matmul_s8s8(onnx.TensorProto.FLOAT16, 21, 9)
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #5709")
+    @unittest.skip(reason="QLinearMatMul(21), which supports float16, is not implemented in ORT.")
     @skip_if_new_opset_exception_raised
     def test_quantize_matmul_s8s8_f16_entropy(self):
         self.quantize_matmul_s8s8(onnx.TensorProto.FLOAT16, 21, 9, calibrate_method=CalibrationMethod.Entropy)
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #5709")
+    @unittest.skip(reason="QLinearMatMul(21), which supports float16, is not implemented in ORT.")
     @skip_if_new_opset_exception_raised
     def test_quantize_matmul_s8s8_f16_percentile(self):
         self.quantize_matmul_s8s8(onnx.TensorProto.FLOAT16, 21, 9, calibrate_method=CalibrationMethod.Percentile)
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #5709")
+    @unittest.skip(reason="QLinearMatMul(21), which supports float16, is not implemented in ORT.")
     @skip_if_new_opset_exception_raised
     def test_quantize_matmul_s8s8_f16_distribution(self):
         self.quantize_matmul_s8s8(onnx.TensorProto.FLOAT16, 21, 9, calibrate_method=CalibrationMethod.Distribution)

onnxruntime/test/python/quantization/test_op_relu.py

@@ -194,7 +194,7 @@ class TestOpRelu(unittest.TestCase):
             weight_type=QuantType.QUInt8,
         )
 
-    @unittest.skip(reason="Shape inference bug, see onnx PR #6049")
+    @unittest.skip(reason="Shape inference bug, see onnx PR #6080")
     def test_quantize_qop_relu_s8s8(self):
         np.random.seed(1)
         model_fp32_path = "relu_fp32.onnx"

orttraining/orttraining/test/python/orttraining_test_ort_apis_py_bindings.py

@@ -348,7 +348,7 @@ def test_get_input_output_names():
 
 
 # Fails in ONNX 1.16.0 due to potential shape inference bug for custom ops.
-# Potential ONNX fix: https://github.com/onnx/onnx/pull/6049
+# Potential ONNX fix: https://github.com/onnx/onnx/pull/6080
 # Error log: LookupError: The provided name onnx::linear.output::171 is not a graph value info or a graph output.
 @pytest.mark.skipif(
     pv.Version(onnx.__version__) == pv.Version("1.16.0"), reason="Shape inference bug for custom ops in ONNX 1.16.0"