INNER CODE UNIT · Python
generate_onnx_representation
Ki6an/fastT5 · fastT5/onnx_exporter.py:56
def generate_onnx_representation(
pretrained_version=None,
model=None,
output_path=None,
input_sequence_length=256,
onnx_opset_version=12, # no other opset versions are tested, change at your own risk
):
"""Exports a given huggingface pretrained model, or a given model and tokenizer, to onnx
Args:
pretrained_version (str): Name of a pretrained model, or path to a pretrained / finetuned version of T5
output_path (Optional[str]): if missing then use ./models
input_sequence_length (Optional[int]): typical input sequence length, for use by the ORT for possible optimization
onnx_opset_version (Optional[int]): ONNX Operator Set Version, default 12 is the only tested version
"""
if (pretrained_version is None) and model is None:
print(
"You need to specify pretrained_version (the pretrained model you wish to export). Alternatively you can export a model you have in memory."