FM / speech_to

/usr/local/lib/python3.6/site-packages/transformers/models/speech_to_text/

/usr/local/lib/python3.6/site-packages/transformers/models/speech_to_text

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_speech_to_text.py	9473	0644	edit dl rm
convert_s2t_fairseq_to_tfms.py	4494	0644	edit dl rm
feature_extraction_speech_to_text.py	11488	0644	edit dl rm
modeling_speech_to_text.py	65401	0644	edit dl rm
modeling_tf_speech_to_text.py	67962	0644	edit dl rm
processing_speech_to_text.py	3273	0644	edit dl rm
tokenization_speech_to_text.py	11100	0644	edit dl rm
__init__.py	3097	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/speech_to_text/__init__.py (3097B)

# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# 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 TYPE_CHECKING

from ...utils import _LazyModule, is_sentencepiece_available, is_speech_available, is_tf_available, is_torch_available

_import_structure = {
    "configuration_speech_to_text": [
        "SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Speech2TextConfig",
    ],
}

if is_sentencepiece_available():
    _import_structure["tokenization_speech_to_text"] = ["Speech2TextTokenizer"]

if is_speech_available():
    _import_structure["feature_extraction_speech_to_text"] = ["Speech2TextFeatureExtractor"]

if is_sentencepiece_available():
        _import_structure["processing_speech_to_text"] = ["Speech2TextProcessor"]

if is_tf_available():
    _import_structure["modeling_tf_speech_to_text"] = [
        "TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFSpeech2TextForConditionalGeneration",
        "TFSpeech2TextModel",
        "TFSpeech2TextPreTrainedModel",
    ]

if is_torch_available():
    _import_structure["modeling_speech_to_text"] = [
        "SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "Speech2TextForConditionalGeneration",
        "Speech2TextModel",
        "Speech2TextPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, Speech2TextConfig

if is_sentencepiece_available():
        from .tokenization_speech_to_text import Speech2TextTokenizer

if is_speech_available():
        from .feature_extraction_speech_to_text import Speech2TextFeatureExtractor

if is_sentencepiece_available():
            from .processing_speech_to_text import Speech2TextProcessor

if is_tf_available():
        from .modeling_tf_speech_to_text import (
            TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSpeech2TextForConditionalGeneration,
            TFSpeech2TextModel,
            TFSpeech2TextPreTrainedModel,
        )

if is_torch_available():
        from .modeling_speech_to_text import (
            SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
            Speech2TextForConditionalGeneration,
            Speech2TextModel,
            Speech2TextPreTrainedModel,
        )

else:
    import sys

sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

cmd: