76 lines
2.8 KiB
Python
76 lines
2.8 KiB
Python
# -------------------------------------------------------------------------
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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 onnx.backend.base import BackendRep
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from onnxruntime import RunOptions
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# Allowlist of RunOptions attributes that are safe to set via the backend API.
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# 'terminate' excluded: setting it True would deny the current inference call.
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# 'training_mode' excluded: silently switches inference behavior in training builds.
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_ALLOWED_RUN_OPTIONS = frozenset(
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{
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"log_severity_level",
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"log_verbosity_level",
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"logid",
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"only_execute_path_to_fetches",
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}
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)
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class OnnxRuntimeBackendRep(BackendRep):
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"""
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Wraps an :class:`onnxruntime.InferenceSession` to implement ONNX's
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:class:`onnx.backend.base.BackendRep` interface for running predictions.
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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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:param inputs: a list of input arrays (one per model input) or a single
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array when the model has exactly one input
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:param kwargs: only a safe subset of :class:`onnxruntime.RunOptions` attributes are
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accepted; see ``_ALLOWED_RUN_OPTIONS`` for the list
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:return: list of output arrays
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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 k in _ALLOWED_RUN_OPTIONS:
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setattr(options, k, v)
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elif hasattr(options, k):
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raise RuntimeError(
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f"RunOptions attribute '{k}' is not permitted via the backend API. "
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f"Allowed attributes: {', '.join(sorted(_ALLOWED_RUN_OPTIONS))}"
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)
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# else: silently ignore unknown keys
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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(f"Model expect {len(inp)} inputs")
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inps = {inp[0].name: inputs}
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return self._session.run(None, inps, options)
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