onnxruntime/orttraining/tools/scripts/performance_investigation.py
Justin Chu d79515041c
[Better Engineering] Bump ruff to 0.0.278 and fix new lint errors (#16789)
Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at
bottom):
* __->__ #16789

Bump ruff to 0.0.278 and fix new lint errors. I added noqa to all
existing RUF012 errors which requires mutable class variables to be
annotated with `ClassVar`, as well as all PERF issues.

Signed-off-by: Justin Chu <justinchu@microsoft.com>
2023-07-21 12:53:41 -07:00

90 lines
2.8 KiB
Python

import argparse
import onnx
parser = argparse.ArgumentParser(description="ONNX file analyzer for performance investigation.")
parser.add_argument("onnx_file", type=str, help="ONNX file to analyze")
args = parser.parse_args()
def process_file(onnx_file):
model = onnx.load(onnx_file)
# Map from output arg to the producer of the output.
output_to_node = {}
for node in model.graph.node:
for o in node.output:
output_to_node[o] = node
aten_ops = []
python_ops = []
memcpu_ops = []
cast_ops = []
msgs = []
for node in model.graph.node:
if "Memcpy" in node.op_type:
memcpu_ops.append(f"{node.op_type} {node.name}")
if node.op_type == "Cast":
cast_ops.append(f"{node.name}")
if node.op_type == "ATen":
for attr in node.attribute:
if attr.name == "operator":
aten_ops.append(f"{node.name}: {attr.s.decode('utf-8')}") # noqa: PERF401
if node.op_type == "PythonOp":
for attr in node.attribute:
if attr.name == "name":
python_ops.append(f"{node.name}: {attr.s.decode('utf-8')}") # noqa: PERF401
# Look for stand-alone Dropout node in *_execution_model_<mode>.onnx graph.
# Examine whether it should be fused with surrounding Add ops into BiasDropout node.
if node.op_type == "Dropout" and len(node.input) == 1:
prev = output_to_node[node.input[0]]
if prev.op_type == "Add":
msgs.append(
f"Examine whether {node.name} should be fused with the leading {prev.name} op into BiasDropout node."
)
# Look for stand-alone Softmax node in *_execution_model_<mode>.onnx graph.
# Examine whether it should be fused with the leading Add ops into BiasSoftmax node.
if node.op_type == "Softmax" and len(node.input) == 1:
prev = output_to_node[node.input[0]]
if prev.op_type == "Add":
msgs.append(
f"Examine whether {node.name} should be fused with the leading {prev.name} op into BiasSoftmax node."
)
if aten_ops:
print("ATen op found:")
for line in aten_ops:
print(line)
print(10 * "-")
if python_ops:
print("PythonOp found:")
for line in python_ops:
print(line)
print(10 * "-")
if memcpu_ops:
print("Memcpu ops found:")
for line in memcpu_ops:
print(line)
print(10 * "-")
if cast_ops:
print("Cast ops found:")
for line in cast_ops:
print(line)
print(10 * "-")
for line in msgs:
print(line)
def main():
process_file(args.onnx_file)
if __name__ == "__main__":
main()