Shortcuts

Source code for flash.audio.speech_recognition.output_transform

# Copyright The PyTorch Lightning 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.
from typing import Any

import torch

from flash.core.data.io.output_transform import OutputTransform
from flash.core.utilities.imports import _AUDIO_AVAILABLE, requires

if _AUDIO_AVAILABLE:
    from transformers import Wav2Vec2CTCTokenizer


[docs]class SpeechRecognitionOutputTransform(OutputTransform): def __init__(self, backbone: str): super().__init__() self.backbone = backbone self._tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(self.backbone) @requires("audio") def per_batch_transform(self, batch: Any) -> Any: # converts logits into greedy transcription pred_ids = torch.argmax(batch, dim=-1) transcriptions = self._tokenizer.batch_decode(pred_ids) return transcriptions def __getstate__(self): # TODO: Find out why this is being pickled state = self.__dict__.copy() state.pop("_tokenizer", None) return state def __setstate__(self, state): self.__dict__.update(state) if self.backbone is not None: self._tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(self.backbone)

© Copyright 2020-2021, PyTorch Lightning. Revision da42a635.

Built with Sphinx using a theme provided by Read the Docs.
Read the Docs v: stable
Versions
latest
stable
0.8.0
0.7.5
0.7.4
0.7.3
0.7.2
0.7.1
0.7.0
0.6.0
0.5.2
0.5.1
0.5.0
0.4.0
0.3.2
0.3.1
0.3.0
0.2.3
0.2.2
0.2.1
0.2.0
0.1.0post1
Downloads
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.