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from typing import Dict |
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import numpy as np |
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import onnx |
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def load_cmvn(): |
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neg_mean = None |
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inv_stddev = None |
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with open("am.mvn") as f: |
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for line in f: |
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if not line.startswith("<LearnRateCoef>"): |
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continue |
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t = line.split()[3:-1] |
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if neg_mean is None: |
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neg_mean = ",".join(t) |
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else: |
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inv_stddev = ",".join(t) |
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return neg_mean, inv_stddev |
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def load_lfr_params(): |
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with open("config.yaml") as f: |
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for line in f: |
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if "lfr_m" in line: |
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lfr_m = int(line.split()[-1]) |
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elif "lfr_n" in line: |
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lfr_n = int(line.split()[-1]) |
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break |
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lfr_window_size = lfr_m |
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lfr_window_shift = lfr_n |
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return lfr_window_size, lfr_window_shift |
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def get_vocab_size(): |
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with open("tokens.txt") as f: |
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return len(f.readlines()) |
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def add_meta_data(filename: str, meta_data: Dict[str, str]): |
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"""Add meta data to an ONNX model. It is changed in-place. |
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Args: |
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filename: |
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Filename of the ONNX model to be changed. |
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meta_data: |
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Key-value pairs. |
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""" |
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model = onnx.load(filename) |
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for key, value in meta_data.items(): |
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meta = model.metadata_props.add() |
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meta.key = key |
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meta.value = value |
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onnx.save(model, filename) |
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print(f"Updated {filename}") |
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def main(): |
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lfr_window_size, lfr_window_shift = load_lfr_params() |
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neg_mean, inv_stddev = load_cmvn() |
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vocab_size = get_vocab_size() |
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meta_data = { |
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"lfr_window_size": str(lfr_window_size), |
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"lfr_window_shift": str(lfr_window_shift), |
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"neg_mean": neg_mean, |
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"inv_stddev": inv_stddev, |
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"model_type": "paraformer", |
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"version": "1", |
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"model_author": "damo", |
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"vocab_size": str(vocab_size), |
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"comment": "speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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} |
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add_meta_data("model.onnx", meta_data) |
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if __name__ == "__main__": |
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main() |
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