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Add backend.prepare Handle Large Models #1074

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Add backend.prepare Handle Large Models #1074

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10 changes: 9 additions & 1 deletion onnx_tf/backend.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,13 +7,16 @@
from __future__ import print_function
from __future__ import unicode_literals

import os

try:
from itertools import izip as zip
except ImportError: # will be 3.x series
pass

from onnx import defs
from onnx import numpy_helper
from onnx import load
from onnx.backend.base import Backend
from onnx.backend.base import namedtupledict
from onnx.backend.test.runner import BackendIsNotSupposedToImplementIt
Expand Down Expand Up @@ -51,7 +54,9 @@ def prepare(cls,
of the computational graph called TensorflowRep and returns
the converted representation.

:param model: The ONNX model to be converted.
:param model: The ONNX model or the file path to the ONNX model to be converted.
If a file path is provided for a model larger than 2GB, the model will be loaded directly
from the path to handle large file sizes.
:param device: The device to execute this model on. It can be either CPU (default) or CUDA.
:param strict: Whether to enforce semantic equivalence between the original model
and the converted tensorflow model, defaults to True (yes, enforce semantic equivalence).
Expand All @@ -70,6 +75,9 @@ def prepare(cls,
common.sys_config.auto_cast = auto_cast
common.sys_config.device = device

if isinstance(model, (str, os.PathLike)):
model = load(model)

return cls.onnx_model_to_tensorflow_rep(model, strict, **kwargs)

@classmethod
Expand Down