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import onnx
from typing import Optional, Union
from pathlib import Path
import os
import logging
logger = logging.getLogger(__name__)
# https://github.com/onnx/onnx/pull/6556
MAXIMUM_PROTOBUF = 2147483648 # 2GiB
def strict_check_model(model_or_path: Union[onnx.ModelProto, str, Path]):
try:
onnx.checker.check_model(model_or_path, full_check=True)
except Exception as e:
if "No Op registered for" in str(e):
pass
else:
raise e
def check_and_save_model(model: onnx.ModelProto, save_path: Optional[Union[str, Path]]):
if model.ByteSize() < MAXIMUM_PROTOBUF:
strict_check_model(model)
if save_path:
save_path = Path(save_path).as_posix()
external_file_name = os.path.basename(save_path) + "_data"
external_path = os.path.join(os.path.dirname(save_path), external_file_name)
if save_path.endswith(".onnx") and os.path.isfile(save_path):
os.remove(save_path)
if os.path.isfile(external_path):
os.remove(external_path)
onnx.save(
model,
save_path,
convert_attribute=True,
)
elif save_path is not None:
# path/to/model.onnx
save_path = Path(save_path).as_posix()
external_file_name = os.path.basename(save_path) + "_data"
# path/to/model.onnx_data
external_path = os.path.join(os.path.dirname(save_path), external_file_name)
if save_path.endswith(".onnx") and os.path.isfile(save_path):
os.remove(save_path)
if os.path.isfile(external_path):
os.remove(external_path)
onnx.save(
model,
save_path,
save_as_external_data=True,
all_tensors_to_one_file=True,
location=external_file_name,
convert_attribute=True,
)
else:
logger.info(
"Merged ONNX model exceeds 2GB, the model will not be checked without `save_path` given."
)
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