mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
Remove Caffe2/onnx (#127991)
Remove Caffe2/onnx since it is not used. Other tiny fixes are also applied. Pull Request resolved: https://github.com/pytorch/pytorch/pull/127991 Approved by: https://github.com/ezyang
This commit is contained in:
cyy
PyTorch MergeBot
@ -1,23 +0,0 @@
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""" build mode definitions for caffe2/caffe2 """
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load("@fbcode//:BUILD_MODE.bzl", get_parent_modes = "all_modes_keep_gpu_sections_all_modes_use_lld")
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load("@fbcode_macros//build_defs:create_build_mode.bzl", "extend_build_mode")
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def update_mode_struct(name, mode_struct):
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if name == "dev":
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return extend_build_mode(
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mode_struct,
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# TODO(ipbrady): Modules introduce floating point inaccuracies (T43879333)
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cxx_modules = False,
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)
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else:
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return mode_struct
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_modes = {
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mode_name: update_mode_struct(mode_name, mode_struct)
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for mode_name, mode_struct in get_parent_modes().items()
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}
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def get_modes():
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""" Return modes for this file """
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return _modes
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@ -1930,7 +1930,6 @@ if(BUILD_PYTHON)
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if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
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if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
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# Workaround for https://gcc.gnu.org/bugzilla/show_bug.cgi?id=80947 in EmbeddingBag.cpp
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# Workaround for https://gcc.gnu.org/bugzilla/show_bug.cgi?id=80947 in EmbeddingBag.cpp
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set_source_files_properties(../aten/src/ATen/native/EmbeddingBag.cpp PROPERTIES COMPILE_FLAGS -Wno-attributes)
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set_source_files_properties(../aten/src/ATen/native/EmbeddingBag.cpp PROPERTIES COMPILE_FLAGS -Wno-attributes)
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set_source_files_properties(${TORCH_SRC_DIR}/../caffe2/operators/box_with_nms_limit_op.cc PROPERTIES COMPILE_FLAGS -Wno-attributes)
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endif()
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endif()
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set(build_files)
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set(build_files)
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@ -1950,10 +1949,4 @@ if(BUILD_PYTHON)
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# Pick up static python files
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# Pick up static python files
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install(DIRECTORY ${CMAKE_BINARY_DIR}/caffe2 DESTINATION ${PYTHON_LIB_REL_PATH}
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install(DIRECTORY ${CMAKE_BINARY_DIR}/caffe2 DESTINATION ${PYTHON_LIB_REL_PATH}
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FILES_MATCHING PATTERN "*.py")
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FILES_MATCHING PATTERN "*.py")
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# Caffe proto files
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install(DIRECTORY ${CMAKE_BINARY_DIR}/caffe DESTINATION ${PYTHON_LIB_REL_PATH}
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FILES_MATCHING PATTERN "*.py")
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# Caffe2 proto files
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install(DIRECTORY ${CMAKE_BINARY_DIR}/caffe2 DESTINATION ${PYTHON_LIB_REL_PATH}
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FILES_MATCHING PATTERN "*.py")
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endif()
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endif()
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@ -1,5 +0,0 @@
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import warnings
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from torch.onnx import _CAFFE2_ATEN_FALLBACK
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if not _CAFFE2_ATEN_FALLBACK:
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warnings.warn("Caffe2 support is no longer present in PyTorch.")
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@ -1,5 +0,0 @@
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# ---[ Extra onnx files.
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file(GLOB ONNX_SRCS *.cc)
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# ---[ Send the lists to the parent scope.
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set(ONNX_SRCS ${ONNX_SRCS} PARENT_SCOPE)
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@ -1,7 +0,0 @@
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namespace ONNX_NAMESPACE {
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const int AI_ONNX_PYTORCH_DOMAIN_MIN_OPSET = 1;
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const int AI_ONNX_PYTORCH_DOMAIN_MAX_OPSET = 1;
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constexpr const char* AI_ONNX_PYTORCH_DOMAIN = "ai.onnx.pytorch";
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} // namespace ONNX_NAMESPACE
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@ -1,168 +0,0 @@
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// Copyright (c) Facebook Inc. and Microsoft Corporation.
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// Licensed under the MIT license.
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#include "./schema.h"
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namespace ONNX_NAMESPACE {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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SparseLengthsSumFused8BitRowwise,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 SparseLengthsSumFused8BitRowwise operator")
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.Input(0, "DATA", "data tensor", "T1")
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.Input(1, "INDICES", "indices tensor", "T2")
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.Input(2, "LENGTHS", "lengths tensor", "T2")
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.Output(0, "output", "Output tensor", "T2")
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.TypeConstraint(
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"T1",
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{"tensor(uint8)"},
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"Constrain input data to uint8 tensors.")
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.TypeConstraint(
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"T2",
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{"tensor(int8)",
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"tensor(int16)",
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"tensor(int32)",
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"tensor(int64)",
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"tensor(uint8)",
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"tensor(uint16)",
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"tensor(uint32)",
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"tensor(uint64)"},
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"Constrain index and length to integral tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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SparseLengthsSum,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 SparseLengthsSum operator")
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.Input(0, "DATA", "data tensor", "T1")
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.Input(1, "INDICES", "indices tensor", "T2")
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.Input(2, "LENGTHS", "lengths tensor", "T2")
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.Output(0, "output", "Output tensor", "T1")
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.TypeConstraint(
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"T1",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors.")
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.TypeConstraint(
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"T2",
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{"tensor(int8)",
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"tensor(int16)",
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"tensor(int32)",
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"tensor(int64)",
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"tensor(uint8)",
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"tensor(uint16)",
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"tensor(uint32)",
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"tensor(uint64)"},
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"Constrain index and length to integral tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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SparseLengthsWeightedSum,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 SparseLengthsWeightedSum operator")
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.Input(0, "DATA", "data tensor", "T1")
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.Input(1, "WEIGHTS", "data tensor", "T1")
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.Input(2, "INDICES", "indices tensor", "T2")
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.Input(3, "LENGTHS", "lengths tensor", "T2")
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.Output(0, "output", "Output tensor", "T1")
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.TypeConstraint(
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"T1",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors.")
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.TypeConstraint(
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"T2",
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{"tensor(int8)",
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"tensor(int16)",
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"tensor(int32)",
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"tensor(int64)",
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"tensor(uint8)",
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"tensor(uint16)",
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"tensor(uint32)",
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"tensor(uint64)"},
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"Constrain index and length to integral tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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BatchGather,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 BatchGather operator")
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.Input(0, "DATA", "data tensor", "T1")
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.Input(1, "INDICES", "indices tensor", "T2")
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.Output(0, "output", "Output tensor", "T1")
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.TypeConstraint(
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"T1",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors.")
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.TypeConstraint(
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"T2",
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{"tensor(int8)",
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"tensor(int16)",
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"tensor(int32)",
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"tensor(int64)",
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"tensor(uint8)",
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"tensor(uint16)",
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"tensor(uint32)",
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"tensor(uint64)"},
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"Constrain index and length to integral tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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DotProduct,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 DotProduct operator")
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.Input(0, "X", "Input 1 tensor", "T")
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.Input(1, "Y", "Input 2 tensor", "T")
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.Output(0, "Z", "Output tensor", "T")
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.TypeConstraint(
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"T",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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FCTransposed,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 FCTransposed operator")
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.Input(0, "X", "Input tensor", "T")
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.Input(1, "W", "Weight tensor", "T")
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.Input(2, "B", "Bias tensor", "T")
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.Output(0, "Z", "Output tensor", "T")
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.TypeConstraint(
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"T",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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BatchMatMul,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 BatchMatMul operator")
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.Input(0, "X", "tensor of shape (dim0, dim1 ... M, K)", "T")
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.Input(1, "Y", "tensor of shape (dim0, dim2 ... K, N)", "T")
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.Output(0, "Z", "tensor of shape (dim0, dim1 ... M, N)", "T")
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.TypeConstraint(
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"T",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors."));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,bugprone-branch-clone)
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ONNX_PYTORCH_OPERATOR_SET_SCHEMA(
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ExpandDims,
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1,
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OpSchema()
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.SetDoc("Mirror Caffe2 ExpandDims operator")
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.Input(0, "X", "Input tensor", "T")
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.Output(0, "Y", "Output tensor", "T")
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.TypeConstraint(
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"T",
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{"tensor(float16)", "tensor(float)", "tensor(double)"},
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"Constrain input and output types to float tensors."));
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} // namespace ONNX_NAMESPACE
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@ -1,46 +0,0 @@
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#pragma once
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#include "onnx/defs/schema.h"
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namespace ONNX_NAMESPACE {
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch,
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1,
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SparseLengthsSumFused8BitRowwise);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, SparseLengthsSum);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, SparseLengthsWeightedSum);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, BatchGather);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, DotProduct);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, FCTransposed);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, BatchMatMul);
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class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, ExpandDims);
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// Iterate over schema from ai.onnx.pytorch domain opset 1
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class OpSet_PyTorch_ver1 {
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public:
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static void ForEachSchema(std::function<void(OpSchema&&)> fn) {
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, SparseLengthsSumFused8BitRowwise)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, SparseLengthsSum)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, SparseLengthsWeightedSum)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, BatchGather)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, DotProduct)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, FCTransposed)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, BatchMatMul)>());
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fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
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PyTorch, 1, ExpandDims)>());
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}
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};
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inline void RegisterPyTorchOperatorSetSchema() {
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RegisterOpSetSchema<OpSet_PyTorch_ver1>();
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}
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} // namespace ONNX_NAMESPACE
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@ -1,17 +0,0 @@
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#include "./schema.h"
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#include "./operator_sets.h"
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namespace {
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using namespace ONNX_NAMESPACE;
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class PyTorchSchemasRegisterer {
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public:
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PyTorchSchemasRegisterer() {
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OpSchemaRegistry::DomainToVersionRange::Instance().AddDomainToVersion(
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AI_ONNX_PYTORCH_DOMAIN,
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AI_ONNX_PYTORCH_DOMAIN_MIN_OPSET,
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AI_ONNX_PYTORCH_DOMAIN_MAX_OPSET);
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RegisterPyTorchOperatorSetSchema();
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}
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};
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static PyTorchSchemasRegisterer registerer{};
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} // namespace
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@ -1,8 +0,0 @@
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#pragma once
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#include "./constants.h"
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#include "onnx/defs/schema.h"
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#define ONNX_PYTORCH_OPERATOR_SET_SCHEMA(name, ver, impl) \
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ONNX_OPERATOR_SET_SCHEMA_EX( \
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name, PyTorch, AI_ONNX_PYTORCH_DOMAIN, ver, false, impl)
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@ -1282,8 +1282,6 @@ if(CAFFE2_CMAKE_BUILDING_WITH_MAIN_REPO AND NOT INTERN_DISABLE_ONNX)
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add_definitions(-DONNX_ML=1)
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add_definitions(-DONNX_ML=1)
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endif()
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endif()
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add_definitions(-DONNXIFI_ENABLE_EXT=1)
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add_definitions(-DONNXIFI_ENABLE_EXT=1)
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# Add op schemas in "ai.onnx.pytorch" domain
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add_subdirectory("${CMAKE_CURRENT_LIST_DIR}/../caffe2/onnx/torch_ops")
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if(NOT USE_SYSTEM_ONNX)
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if(NOT USE_SYSTEM_ONNX)
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add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/../third_party/onnx EXCLUDE_FROM_ALL)
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add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/../third_party/onnx EXCLUDE_FROM_ALL)
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if(NOT MSVC)
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if(NOT MSVC)
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||||||
|
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Reference in New Issue
Block a user