mirror of
https://github.com/storytold/artcraft.git
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67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. 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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import argparse
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from nemo.collections.asr.models import EncDecClassificationModel, EncDecCTCModel, EncDecSpeakerLabelModel
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from nemo.utils import logging
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def get_parser():
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parser = argparse.ArgumentParser(description="Convert .nemo file to encoder decoder onnx files")
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parser.add_argument(
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"--nemo_file", default=None, type=str, required=True, help="Path to .nemo file",
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)
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parser.add_argument(
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"--onnx_encoder", default=None, type=str, required=True, help="Path to the onnx encoder output.",
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)
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parser.add_argument(
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"--onnx_decoder", default=None, type=str, required=True, help="Path to the onnx decoder output.",
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)
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parser.add_argument(
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"--model_type",
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default='asr',
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type=str,
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choices=['asr', 'speech_label', 'speaker'],
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help="Type of decoder used by the model.",
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)
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return parser
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def main(
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nemo_file, onnx_encoder, onnx_decoder, model_type='asr',
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):
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if model_type == 'asr':
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logging.info("Preparing encoder decoder for ASR model")
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model = EncDecCTCModel.restore_from(nemo_file)
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elif model_type == 'speech_label':
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logging.info("Preparing encoder decoder for Speech Label Classification model")
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model = EncDecClassificationModel.restore_from(nemo_file)
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elif model_type == 'speaker':
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logging.info("Preparing encoder decoder for Speaker Recognition model")
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model = EncDecSpeakerLabelModel.restore_from(nemo_file)
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else:
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raise NameError("Available model names are asr, speech_label and speaker ")
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logging.info("Writing onnx encoder and decoder onnx files")
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model.encoder.export(onnx_encoder)
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model.decoder.export(onnx_decoder, onnx_opset_version=10)
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logging.info("succesfully ported onnx files")
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if __name__ == "__main__":
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args = get_parser().parse_args()
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main(
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args.nemo_file, args.onnx_encoder, args.onnx_decoder, model_type=args.model_type,
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)
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