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53 lines
1.7 KiB
53 lines
1.7 KiB
# -------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------------------
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"""
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Implements ONNX's backend API.
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"""
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from typing import Any, Tuple
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from onnx.backend.base import BackendRep
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from onnxruntime import RunOptions
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class OnnxRuntimeBackendRep(BackendRep):
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"""
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Computes the prediction for a pipeline converted into
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an :class:`onnxruntime.InferenceSession` node.
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"""
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def __init__(self, session):
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"""
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:param session: :class:`onnxruntime.InferenceSession`
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"""
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self._session = session
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def run(self, inputs, **kwargs): # type: (Any, **Any) -> Tuple[Any, ...]
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"""
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Computes the prediction.
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See :meth:`onnxruntime.InferenceSession.run`.
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"""
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options = RunOptions()
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for k, v in kwargs.items():
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if hasattr(options, k):
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setattr(options, k, v)
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if isinstance(inputs, list):
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inps = {}
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for i, inp in enumerate(self._session.get_inputs()):
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inps[inp.name] = inputs[i]
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outs = self._session.run(None, inps, options)
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if isinstance(outs, list):
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return outs
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else:
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output_names = [o.name for o in self._session.get_outputs()]
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return [outs[name] for name in output_names]
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else:
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inp = self._session.get_inputs()
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if len(inp) != 1:
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raise RuntimeError("Model expect {0} inputs".format(len(inp)))
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inps = {inp[0].name: inputs}
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return self._session.run(None, inps, options)
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