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90 lines
3.2 KiB
Python
90 lines
3.2 KiB
Python
# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Shared helpers (calibration I/O) for ``quantize_onnx_model`` / ``debug_onnx_qdq`` / ``build_onnx_calib_npy``.
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Entry scripts prepend this file's directory to ``sys.path`` before ``from utils import ...`` so
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``import utils`` does not depend on the process working directory. The top-level name ``utils`` is
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generic; the scripts resolve ``utils.py`` in this same ``scripts/`` directory first.
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from typing import Any
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__all__ = [
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"die",
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"user_input_names",
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"build_npy_dir_reader",
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]
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def die(msg: str) -> None:
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print(f"error: {msg}", file=sys.stderr)
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raise SystemExit(1)
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def user_input_names(model_path: Path) -> list[str]:
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"""Return non-initializer graph input names (user-visible inputs)."""
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import onnx
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m = onnx.load(str(model_path), load_external_data=True)
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init = {t.name for t in m.graph.initializer}
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return [i.name for i in m.graph.input if i.name not in init]
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def build_npy_dir_reader(
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model_path: Path, data_dir: Path, *, max_samples: int | None = None
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) -> Any:
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"""ONNX Runtime ``CalibrationDataReader``: one float32 ``(NCHW)`` ``.npy`` per sample; sorted by filename.
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*model_path* is used to discover the single graph input name (``user_input_names``); it may be
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the original or an augmented model as long as the first user input is unchanged.
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"""
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from onnxruntime.quantization import CalibrationDataReader
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class NpyDirectoryDataReader(CalibrationDataReader):
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def __init__(self) -> None:
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names = user_input_names(model_path)
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if len(names) != 1:
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die(
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"expected exactly one non-initializer graph input; "
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f"found {len(names)}: {names}"
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)
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self._input_name = names[0]
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files = sorted(data_dir.glob("*.npy"))
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if not files:
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die(f"no .npy files under {data_dir}")
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if max_samples is not None:
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files = files[: max(0, max_samples)]
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self._it = iter(files)
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def get_next(self) -> Any:
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import numpy as np
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try:
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path = next(self._it)
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except StopIteration:
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return None
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arr = np.load(str(path))
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if not isinstance(arr, np.ndarray):
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die(f"expected ndarray in {path}, got {type(arr)}")
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if arr.dtype != np.float32:
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arr = arr.astype(np.float32, copy=False)
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return {self._input_name: arr}
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return NpyDirectoryDataReader()
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