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| # coding=utf-8 | |
| # Copyright 2022 The HuggingFace Inc. team. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """ | |
| Speech processor class for Whisper | |
| """ | |
| from ...processing_utils import ProcessorMixin | |
| class WhisperProcessor(ProcessorMixin): | |
| r""" | |
| Constructs a Whisper processor which wraps a Whisper feature extractor and a Whisper tokenizer into a single | |
| processor. | |
| [`WhisperProcessor`] offers all the functionalities of [`WhisperFeatureExtractor`] and [`WhisperTokenizer`]. See | |
| the [`~WhisperProcessor.__call__`] and [`~WhisperProcessor.decode`] for more information. | |
| Args: | |
| feature_extractor (`WhisperFeatureExtractor`): | |
| An instance of [`WhisperFeatureExtractor`]. The feature extractor is a required input. | |
| tokenizer (`WhisperTokenizer`): | |
| An instance of [`WhisperTokenizer`]. The tokenizer is a required input. | |
| """ | |
| feature_extractor_class = "WhisperFeatureExtractor" | |
| tokenizer_class = "WhisperTokenizer" | |
| def __init__(self, feature_extractor, tokenizer): | |
| super().__init__(feature_extractor, tokenizer) | |
| self.current_processor = self.feature_extractor | |
| self._in_target_context_manager = False | |
| def get_decoder_prompt_ids(self, task=None, language=None, no_timestamps=True): | |
| return self.tokenizer.get_decoder_prompt_ids(task=task, language=language, no_timestamps=no_timestamps) | |
| def __call__(self, *args, **kwargs): | |
| """ | |
| Forwards the `audio` argument to WhisperFeatureExtractor's [`~WhisperFeatureExtractor.__call__`] and the `text` | |
| argument to [`~WhisperTokenizer.__call__`]. Please refer to the doctsring of the above two methods for more | |
| information. | |
| """ | |
| # For backward compatibility | |
| if self._in_target_context_manager: | |
| return self.current_processor(*args, **kwargs) | |
| audio = kwargs.pop("audio", None) | |
| sampling_rate = kwargs.pop("sampling_rate", None) | |
| text = kwargs.pop("text", None) | |
| if len(args) > 0: | |
| audio = args[0] | |
| args = args[1:] | |
| if audio is None and text is None: | |
| raise ValueError("You need to specify either an `audio` or `text` input to process.") | |
| if audio is not None: | |
| inputs = self.feature_extractor(audio, *args, sampling_rate=sampling_rate, **kwargs) | |
| if text is not None: | |
| encodings = self.tokenizer(text, **kwargs) | |
| if text is None: | |
| return inputs | |
| elif audio is None: | |
| return encodings | |
| else: | |
| inputs["labels"] = encodings["input_ids"] | |
| return inputs | |
| def batch_decode(self, *args, **kwargs): | |
| """ | |
| This method forwards all its arguments to WhisperTokenizer's [`~PreTrainedTokenizer.batch_decode`]. Please | |
| refer to the docstring of this method for more information. | |
| """ | |
| return self.tokenizer.batch_decode(*args, **kwargs) | |
| def decode(self, *args, **kwargs): | |
| """ | |
| This method forwards all its arguments to WhisperTokenizer's [`~PreTrainedTokenizer.decode`]. Please refer to | |
| the docstring of this method for more information. | |
| """ | |
| return self.tokenizer.decode(*args, **kwargs) | |
| def get_prompt_ids(self, text: str, return_tensors="np"): | |
| return self.tokenizer.get_prompt_ids(text, return_tensors=return_tensors) | |