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77 lines
2.6 KiB
77 lines
2.6 KiB
# Copyright (c) 2021 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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# Modified from espnet(https://github.com/espnet/espnet)
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"""ST Interface module."""
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from .asr_interface import ASRInterface
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from paddlespeech.s2t.utils.dynamic_import import dynamic_import
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class STInterface(ASRInterface):
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"""ST Interface model implementation.
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NOTE: This class is inherited from ASRInterface to enable joint translation
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and recognition when performing multi-task learning with the ASR task.
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"""
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def translate(self,
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x,
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trans_args,
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char_list=None,
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rnnlm=None,
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ensemble_models=[]):
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"""Recognize x for evaluation.
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:param ndarray x: input acouctic feature (B, T, D) or (T, D)
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:param namespace trans_args: argment namespace contraining options
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:param list char_list: list of characters
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:param paddle.nn.Layer rnnlm: language model module
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:return: N-best decoding results
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:rtype: list
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"""
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raise NotImplementedError("translate method is not implemented")
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def translate_batch(self, x, trans_args, char_list=None, rnnlm=None):
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"""Beam search implementation for batch.
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:param paddle.Tensor x: encoder hidden state sequences (B, Tmax, Henc)
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:param namespace trans_args: argument namespace containing options
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:param list char_list: list of characters
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:param paddle.nn.Layer rnnlm: language model module
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:return: N-best decoding results
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:rtype: list
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"""
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raise NotImplementedError("Batch decoding is not supported yet.")
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predefined_st = {
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"transformer": "paddlespeech.s2t.models.u2_st:U2STModel",
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}
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def dynamic_import_st(module):
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"""Import ST models dynamically.
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Args:
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module (str): module_name:class_name or alias in `predefined_st`
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Returns:
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type: ST class
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"""
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model_class = dynamic_import(module, predefined_st)
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assert issubclass(model_class,
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STInterface), f"{module} does not implement STInterface"
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return model_class
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