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Re-enable custom op support #1139

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Aug 16, 2022
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20 changes: 9 additions & 11 deletions build_tools/update_shape_lib.sh
Original file line number Diff line number Diff line change
Expand Up @@ -16,19 +16,17 @@ build_dir="$(realpath "${TORCH_MLIR_BUILD_DIR:-$src_dir/build}")"
torch_transforms_cpp_dir="${src_dir}/lib/Dialect/Torch/Transforms"
python_packages_dir="${build_dir}/tools/torch-mlir/python_packages"

TORCH_MLIR_EXT_PYTHONPATH="${TORCH_MLIR_EXT_PYTHONPATH:-""}"
pypath="${python_packages_dir}/torch_mlir"
# TODO: Re-enable once custom op support is back.
#if [ ! -z ${TORCH_MLIR_EXT_PYTHONPATH} ]; then
# pypath="${pypath}:${TORCH_MLIR_EXT_PYTHONPATH}"
#fi
#ext_module="torch_mlir._torch_mlir_custom_op_example"
#if [ ! -z ${TORCH_MLIR_EXT_MODULES} ]; then
# ext_module="${ext_module},${TORCH_MLIR_EXT_MODULES} "
#fi
if [ ! -z ${TORCH_MLIR_EXT_PYTHONPATH} ]; then
pypath="${pypath}:${TORCH_MLIR_EXT_PYTHONPATH}"
fi
TORCH_MLIR_EXT_MODULES="${TORCH_MLIR_EXT_MODULES:-""}"
if [ ! -z ${TORCH_MLIR_EXT_MODULES} ]; then
ext_module="${TORCH_MLIR_EXT_MODULES} "
fi

PYTHONPATH="${pypath}" python \
-m torch_mlir.dialects.torch.importer.jit_ir.build_tools.shape_lib_gen \
--pytorch_op_extensions=${ext_module} \
--torch_transforms_cpp_dir="${torch_transforms_cpp_dir}"

# TODO: Add back to shape_lib_gen invocation once custom op support is back.
# --pytorch_op_extensions=${ext_module} \
21 changes: 10 additions & 11 deletions build_tools/update_torch_ods.sh
Original file line number Diff line number Diff line change
Expand Up @@ -16,20 +16,19 @@ build_dir="$(realpath "${TORCH_MLIR_BUILD_DIR:-$src_dir/build}")"
torch_ir_include_dir="${src_dir}/include/torch-mlir/Dialect/Torch/IR"
python_packages_dir="${build_dir}/tools/torch-mlir/python_packages"

TORCH_MLIR_EXT_PYTHONPATH="${TORCH_MLIR_EXT_PYTHONPATH:-""}"
pypath="${python_packages_dir}/torch_mlir"
# TODO: Re-enable once custom op support is back.
#if [ ! -z ${TORCH_MLIR_EXT_PYTHONPATH} ]; then
# pypath="${pypath}:${TORCH_MLIR_EXT_PYTHONPATH}"
#fi
#ext_module="torch_mlir._torch_mlir_custom_op_example"
#if [ ! -z ${TORCH_MLIR_EXT_MODULES} ]; then
# ext_module="${ext_module},${TORCH_MLIR_EXT_MODULES}"
#fi
if [ ! -z ${TORCH_MLIR_EXT_PYTHONPATH} ]; then
pypath="${pypath}:${TORCH_MLIR_EXT_PYTHONPATH}"
fi
TORCH_MLIR_EXT_MODULES="${TORCH_MLIR_EXT_MODULES:-""}"
ext_module="${ext_module:-""}"
if [ ! -z ${TORCH_MLIR_EXT_MODULES} ]; then
ext_module="${TORCH_MLIR_EXT_MODULES}"
fi

PYTHONPATH="${pypath}" python \
-m torch_mlir.dialects.torch.importer.jit_ir.build_tools.torch_ods_gen \
--torch_ir_include_dir="${torch_ir_include_dir}" \
--pytorch_op_extensions="${ext_module}" \
--debug_registry_dump="${torch_ir_include_dir}/JITOperatorRegistryDump.txt"

# TODO: Add back to torch_ods_gen invocation once custom op support is back.
# --pytorch_op_extensions="${ext_module}" \
2 changes: 0 additions & 2 deletions lib/Conversion/TorchToLinalg/CMakeLists.txt
Original file line number Diff line number Diff line change
@@ -1,6 +1,4 @@
add_mlir_conversion_library(TorchMLIRTorchToLinalg
# TODO: Re-enable after MacOS support is fixed for the custom op extension.
# CustomOpExample.cpp
DataMovement.cpp
IndirectDataMovement.cpp
Linear.cpp
Expand Down
3 changes: 0 additions & 3 deletions lib/Conversion/TorchToLinalg/PopulatePatterns.h
Original file line number Diff line number Diff line change
Expand Up @@ -63,9 +63,6 @@ void populateIndirectDataMovementPatternsAndLegality(
void populateTensorConstructorsPatternsAndLegality(TypeConverter &typeConverter,
RewritePatternSet &patterns,
ConversionTarget &target);
//void populateCustomOpExamplePatternsAndLegality(TypeConverter &typeConverter,
// RewritePatternSet &patterns,
// ConversionTarget &target);

} // namespace torch_to_linalg
} // namespace torch
Expand Down
2 changes: 0 additions & 2 deletions lib/Conversion/TorchToLinalg/TorchToLinalg.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -62,8 +62,6 @@ class ConvertTorchToLinalg

RewritePatternSet patterns(context);

//torch_to_linalg::populateCustomOpExamplePatternsAndLegality(
// typeConverter, patterns, target);
torch_to_linalg::populateTensorScalarInteropPatternsAndLegality(
typeConverter, patterns, target);
torch_to_linalg::populateLinearPatternsAndLegality(typeConverter, patterns,
Expand Down
6 changes: 1 addition & 5 deletions python/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -111,8 +111,7 @@ add_subdirectory(torch_mlir/eager_mode)
# Required for running the update_torch_ods.sh and update_shape_lib.sh scripts.
################################################################################

# TODO: renable once it build on macOS Intel / M1
#add_subdirectory(torch_mlir/_torch_mlir_custom_op_example)
# add_subdirectory(torch_mlir/_torch_mlir_custom_op_example)
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################################################################################
# Generate packages and shared library
Expand Down Expand Up @@ -160,9 +159,6 @@ if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
add_dependencies(TorchMLIRPythonModules TorchMLIRE2ETestPythonModules)
endif()

# TODO: Add after macOS builds are fixed
#add_dependencies(TorchMLIRPythonModules torch_mlir_custom_op_example)

if(TORCH_MLIR_ENABLE_LTC)
# Add Torch-MLIR LTC backend as dependency
add_dependencies(TorchMLIRPythonModules torch_mlir_ltc_backend)
Expand Down
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# Setup PyTorch
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../dialects/torch/importer/jit_ir/cmake/modules")
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../cmake/modules")
include(TorchMLIRPyTorch)
TorchMLIRProbeForPyTorchInstall()
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find_package(Torch 1.8 REQUIRED)
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -1164,10 +1164,6 @@ def aten〇linalg_vector_norm(self: List[int], ord: float = 2, dim: Optional[Lis
dim = list(range(len(self)))
return upstream_shape_functions.mean_dim(self, dim, keepdim, dtype)

# TODO: Re-enable after MacOS support is fixed for the extension.
#def _torch_mlir_custom_op_example〇identity(t: List[int]) -> List[int]:
# return upstream_shape_functions.unary(t)

# ==============================================================================
# Shape library generator main().
# ==============================================================================
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -629,16 +629,6 @@ def emit_with_mutating_variants(key, **kwargs):
"quantized::linear : (Tensor, __torch__.torch.classes.quantized.LinearPackedParamsBase, float, int) -> (Tensor)",
traits=["HasValueSemantics"])

# ==========================================================================
# `_torch_mlir_custom_op_example::` namespace.
#
# This is a demonstration of supporting an operation defined in a PyTorch
# extension.
# ==========================================================================

# TODO: Re-enable after MacOS support is fixed for the extension.
#emit("_torch_mlir_custom_op_example::identity : (Tensor) -> (Tensor)")


def dump_registered_ops(outfile: TextIO, registry: Registry):
for _, v in sorted(registry.by_unique_key.items()):
Expand Down
2 changes: 0 additions & 2 deletions python/torch_mlir_e2e_test/test_suite/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -51,5 +51,3 @@ def register_all_tests():
from . import return_types
from . import control_flow
from . import stats
# TODO: Re-enable after MacOS support is fixed for the extension.
#from . import custom_op_example