onnxruntime/tools/python/find_optimizer_opset_version_updates_required.py
Ashrit Shetty 4b5b5f7101
Update win-ort-main to tip main 250123 (#23473)
### Description
This PR is to update the win-ort-main branch to the tip main branch as
of 2025-01-23.

### PR List
ddf0d377a7 [QNN EP] Add LoggingManager::HasDefaultLogger() to provider
bridge API (#23467)
05fbbdf91f [QNN EP] Make QNN EP a shared library (#23120)
1336566d7f Add custom vcpkg ports (#23456)
2e1173c411 Update the compile flags for vcpkg packages (#23455)
1f628a9858 [Mobile] Add BrowserStack Android MAUI Test (#23383)
009cae0ec8 [js/webgpu] Optimize ConvTranspose (Continue) (#23429)
04a4a694cb Use onnx_protobuf.h to suppress some GCC warnings (#23453)
2e3b62b4b0 Suppress some strict-aliasing related warnings in WebGPU EP
(#23454)
b708f9b1dc Bump ruff from 0.9.1 to 0.9.2 (#23427)
c0afc66b2a [WebNN] Remove workarounds for TFLite backend (#23406)
8a821ff7f9 Bump vite from 6.0.7 to 6.0.11 in
/js/web/test/e2e/exports/testcases/vite-default (#23446)
220c1a203e Make ORT and Dawn use the same protobuf/abseil source code
(#23447)
b7b5792147 Change MacOS-13 to ubuntu on for
android-java-api-aar-test.yml. (#23444)
19d0d2a30f WIP: Dp4MatMulNBits accuracy level 4 matmul for WebGPU EP
(#23365)
95b8effbc4 [QNN EP]: Clean up QNN logging resources if an error occurs
during initialization (#23435)
626134c5b5 Bump clang-format from 19.1.6 to 19.1.7 (#23428)
0cf975301f Fix eigen external deps (#23439)
f9440aedce Moving RN_CI Android Testing to Linux (#23422)
1aa5902ff4 [QNN EP] workaround for QNN validation bug for Tanh with
uint16 quantized output (#23432)
7f5582a0e2 Seperate RN andriod and IOS into 2 separated Stages. (#23400)
73deac2e7f Implement some missing element wise Add/Sub/Mul/Div/Neg
operations for CPU and CUDA EPs (#23090)
949fe42af4 Upgrade Java version from react-native/android to Java 17
(#23066)
0892c23463 Update Qnn SDK default version to 2.30 (#23411)
94c099bcec Fix type cast build error (#23423)
d633e571d1 [WebNN EP] Fix AddInitializersToSkip issues (#23354)
e988ef00e2 [QNN EP] Fix regression for MatMul with two quantized/dynamic
uint16 inputs (#23419)
7538795f6b Update onnxruntime binary size checks ci pipeline's docker
image (#23405)
6c5ea41cad Revert "[QNN EP] Clean up correctly from a partial setup
(#23320)" (#23420)
e866804bbe Enable comprehension simplification in ruff rules (#23414)
0a5f1f392c bugfix: string_view of invalid memory (#23417)
4cc38e0277 fix crash when first input of BatchNormalization is 1-D
(#23387)
033441487f Target py310 and modernize codebase with ruff (#23401)
87341ac010 [QNN EP] Fix segfault when unregistering HTP shared memory
handles (#23402)

### Motivation and Context
This update includes the change to make QNN-EP a shared library.

---------

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com>
Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Peishen Yan <peishen.yan@intel.com>
Co-authored-by: Tianlei Wu <tlwu@microsoft.com>
Co-authored-by: Hector Li <hecli@microsoft.com>
Co-authored-by: Jian Chen <cjian@microsoft.com>
Co-authored-by: Alexis Tsogias <1114095+Zyrin@users.noreply.github.com>
Co-authored-by: junchao-zhao <68935141+junchao-loongson@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: sushraja-msft <44513542+sushraja-msft@users.noreply.github.com>
Co-authored-by: Wanming Lin <wanming.lin@intel.com>
Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com>
Co-authored-by: Caroline Zhu <wolfivyaura@gmail.com>
2025-01-23 09:12:03 -08:00

215 lines
8.2 KiB
Python

#!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import argparse
import glob
import logging
import os
import re
logging.basicConfig(format="[%(levelname)s] - %(message)s", level=logging.DEBUG)
log = logging.getLogger()
def parse_args():
parser = argparse.ArgumentParser(
description="Find optimizers that involve operators which may need an update to the supported opset versions."
)
root_arg = parser.add_argument(
"--ort-root", "-o", required=True, type=str, help="The root directory of the ONNX Runtime repository to search."
)
args = parser.parse_args()
if not os.path.isdir(args.ort_root):
raise argparse.ArgumentError(root_arg, f"{args.ort_root} is not a valid directory")
return args
def get_call_args_from_file(filename: str, function_or_declaration: str) -> list[str]:
"""
Search a file for all function calls or declarations that match the provided name.
Requires both the opening '(' and closing ')' to be on the same line.
Handles multiple calls being on the same line.
"""
results = []
with open(filename) as f:
line_num = 0
for line in f:
for match in re.finditer(function_or_declaration, line):
# check we have both the opening and closing brackets for the function call/declaration.
# if we do we have all the arguments
start = line.find("(", match.end())
end = line.find(")", match.end())
have_all_args = start != -1 and end != -1
if have_all_args:
results.append(line[start + 1 : end])
else:
# TODO: handle automatically by merging lines
log.error(
"Call/Declaration is split over multiple lines. Please check manually."
f"File:{filename} Line:{line_num}"
)
continue
line_num += 1
return results
def get_multiline_call_args_from_file(filename: str, function_or_declaration: str) -> list[str]:
"""
Search a file for all function calls or declarations that match the provided name.
Allows the opening '(' and closing ')' to be split across multiple lines.
Supports a single call per line.
"""
results = []
with open(filename) as f:
function_and_args = None
for line in f:
if not function_and_args:
# look for new match
start = line.find(function_or_declaration)
if start != -1:
function_and_args = line[start:].strip()
else:
# append to existing line and look for closing ')'
start = len(function_and_args)
function_and_args += line.strip()
if function_and_args:
end = function_and_args.find(")", start)
if end != -1:
start_args = function_and_args.find("(")
results.append(function_and_args[start_args + 1 : end])
function_and_args = None
return results
def _add_if_newer(domain: str, op: str, opset: int, op_to_opset: 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 = [
# 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:
# e.g. class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Clip);
calls = get_multiline_call_args_from_file(file, "ONNX_OPERATOR_KERNEL_CLASS_NAME")
for call in calls:
args = call.split(",")
domain = args[1].strip()
opset = args[2].strip()
op = args[3].strip()
_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")
for call in calls:
args = call.split(",")
domain = args[1].strip()
opset = args[2].strip()
op = args[4].strip()
_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
def find_potential_issues(root_dir, op_to_opset):
optimizer_dir = os.path.join(root_dir, "onnxruntime/core/optimizer")
files = glob.glob(optimizer_dir + "/**/*.cc", recursive=True)
files += glob.glob(optimizer_dir + "/**/*.h", recursive=True)
for file in files:
calls = get_call_args_from_file(file, "graph_utils::IsSupportedOptypeVersionAndDomain")
for call in calls:
# Need to handle multiple comma separated version numbers, and the optional domain argument.
# e.g. IsSupportedOptypeVersionAndDomain(node, "MaxPool", {1, 8, 10})
# IsSupportedOptypeVersionAndDomain(node, "FusedConv", {1}, kMSDomain)
args = call.split(",", 2) # first 2 args are simple, remainder need custom processing
op = args[1].strip()
if not op.startswith('"') or not op.endswith('"'):
log.error(f"Symbolic name of '{op}' found for op. Please check manually. File:{file}")
continue
versions_and_domain_arg = args[2]
v1 = versions_and_domain_arg.find("{")
v2 = versions_and_domain_arg.find("}")
versions = versions_and_domain_arg[v1 + 1 : v2].split(",")
last_version = versions[-1].strip()
domain_arg_start = versions_and_domain_arg.find(",", v2)
if domain_arg_start != -1:
domain = versions_and_domain_arg[domain_arg_start + 1 :].strip()
else:
domain = "kOnnxDomain"
op = domain + "." + op[1:-1]
if op in op_to_opset:
latest = op_to_opset[op]
if int(latest) != int(last_version):
log.warning(
f"Newer opset found for {op}. Latest:{latest} Optimizer support ends at {last_version}. File:{file}"
)
else:
log.error(f"Failed to find version information for {op}. File:{file}")
if __name__ == "__main__":
arguments = parse_args()
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)