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Update find_optimizer_opset_version_updates_required.py to use the ONNX headers to determine the latest opset. (#12484)

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**Description**: 
Use the onnx headers to find the latest opset for each operator. This
allows the script to detect optimizers with
`graph_utils::IsSupportedOptypeVersionAndDomain` calls that need
updating when run during the update of the onnx commit id. Without this
change issues are not detected until a new kernel is registered.

**Motivation and Context**
Detect optimizers that need updates as part of the ONNX update process.
This commit is contained in:
Scott McKay 2022-09-29 16:55:22 +10:00 committed by GitHub
parent 6c63c1c9ee
commit 4d8510611b
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GPG key ID: 4AEE18F83AFDEB23
1 changed files with 46 additions and 5 deletions
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51
tools/python/find_optimizer_opset_version_updates_required.py
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@ -96,13 +96,22 @@ def get_multiline_call_args_from_file(filename: str, function_or_declaration: st
return results
def get_latest_op_versions(root_dir):
def _add_if_newer(domain: str, op: str, opset: int, op_to_opset: typing.Dict[str, int]):
key = domain + "." + op
if key not in op_to_opset or op_to_opset[key] < opset:
op_to_opset[key] = opset
def get_latest_ort_op_versions(root_dir):
"""Find the entries for the latest opset for each operator."""
op_to_opset = {}
files = [
os.path.join(root_dir, "onnxruntime/core/providers/cpu/cpu_execution_provider.cc"),
# for ONNX operators we use get_latest_onnx_op_versions
# os.path.join(root_dir, "onnxruntime/core/providers/cpu/cpu_execution_provider.cc"),
# for internal kernels we use the current registrations
os.path.join(root_dir, "onnxruntime/contrib_ops/cpu/cpu_contrib_kernels.cc"),
os.path.join(root_dir, "onnxruntime/contrib_ops/cuda/cuda_contrib_kernels.cc"),
]
for file in files:
@ -113,7 +122,7 @@ def get_latest_op_versions(root_dir):
domain = args[1].strip()
opset = args[2].strip()
op = args[3].strip()
op_to_opset[domain + "." + op] = opset
_add_if_newer(domain, op, int(opset), op_to_opset)
# e.g. class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, float, ArgMax);
calls = get_multiline_call_args_from_file(file, "ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME")
@ -122,7 +131,34 @@ def get_latest_op_versions(root_dir):
domain = args[1].strip()
opset = args[2].strip()
op = args[4].strip()
op_to_opset[domain + "." + op] = opset
_add_if_newer(domain, op, int(opset), op_to_opset)
return op_to_opset
def get_latest_onnx_op_versions(root_dir):
"""Get the latest versions of the ONNX operators from the ONNX headers."""
op_to_opset = {}
files = [
# operators with domain of 'Onnx'
os.path.join(root_dir, "cmake/external/onnx/onnx/defs/operator_sets.h"),
# ML operators with domain of 'OnnxML'
os.path.join(root_dir, "cmake/external/onnx/onnx/defs/operator_sets_ml.h"),
]
for file in files:
# e.g. fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(Onnx, 17, LayerNormalization)>());
# fn(GetOpSchema<ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(OnnxML, 3, TreeEnsembleClassifier)>());
calls = get_multiline_call_args_from_file(file, "ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME")
for call in calls:
args = call.split(",")
orig_domain = args[0].strip()
# convert domain to the ORT constants
domain = "kMLDomain" if orig_domain == "OnnxML" else "kOnnxDomain"
opset = args[1].strip()
op = args[2].strip()
_add_if_newer(domain, op, int(opset), op_to_opset)
return op_to_opset
@ -174,5 +210,10 @@ def find_potential_issues(root_dir, op_to_opset):
if __name__ == "__main__":
arguments = parse_args()
op_to_opset_map = get_latest_op_versions(arguments.ort_root)
ort_to_opset_map = get_latest_ort_op_versions(arguments.ort_root)
onnx_op_to_opset_map = get_latest_onnx_op_versions(arguments.ort_root)
# merge the two maps
op_to_opset_map = {**ort_to_opset_map, **onnx_op_to_opset_map}
find_potential_issues(arguments.ort_root, op_to_opset_map)