FM / wav2vec2

/usr/local/lib/python3.6/site-packages/transformers/models/wav2vec2/

/usr/local/lib/python3.6/site-packages/transformers/models/wav2vec2

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_wav2vec2.py	19492	0644	edit dl rm
convert_wav2vec2_original_pytorch_checkpoint_to_pytorch.py	10968	0644	edit dl rm
convert_wav2vec2_original_s3prl_checkpoint_to_pytorch.py	4838	0644	edit dl rm
feature_extraction_wav2vec2.py	11201	0644	edit dl rm
modeling_flax_wav2vec2.py	56828	0644	edit dl rm
modeling_tf_wav2vec2.py	71419	0644	edit dl rm
modeling_wav2vec2.py	94738	0644	edit dl rm
processing_wav2vec2.py	4877	0644	edit dl rm
tokenization_wav2vec2.py	38823	0644	edit dl rm
__init__.py	3413	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/wav2vec2/__init__.py (3413B)

# 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_flax_available, is_tf_available, is_torch_available

_import_structure = {
    "configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
    "feature_extraction_wav2vec2": ["Wav2Vec2FeatureExtractor"],
    "processing_wav2vec2": ["Wav2Vec2Processor"],
    "tokenization_wav2vec2": ["Wav2Vec2CTCTokenizer", "Wav2Vec2Tokenizer"],
}

if is_torch_available():
    _import_structure["modeling_wav2vec2"] = [
        "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "Wav2Vec2ForAudioFrameClassification",
        "Wav2Vec2ForCTC",
        "Wav2Vec2ForMaskedLM",
        "Wav2Vec2ForPreTraining",
        "Wav2Vec2ForSequenceClassification",
        "Wav2Vec2ForXVector",
        "Wav2Vec2Model",
        "Wav2Vec2PreTrainedModel",
    ]

if is_tf_available():
    _import_structure["modeling_tf_wav2vec2"] = [
        "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFWav2Vec2ForCTC",
        "TFWav2Vec2Model",
        "TFWav2Vec2PreTrainedModel",
    ]

if is_flax_available():
    _import_structure["modeling_flax_wav2vec2"] = [
        "FlaxWav2Vec2ForCTC",
        "FlaxWav2Vec2ForPreTraining",
        "FlaxWav2Vec2Model",
        "FlaxWav2Vec2PreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_wav2vec2 import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, Wav2Vec2Config
    from .feature_extraction_wav2vec2 import Wav2Vec2FeatureExtractor
    from .processing_wav2vec2 import Wav2Vec2Processor
    from .tokenization_wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2Tokenizer

if is_torch_available():
        from .modeling_wav2vec2 import (
            WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
            Wav2Vec2ForAudioFrameClassification,
            Wav2Vec2ForCTC,
            Wav2Vec2ForMaskedLM,
            Wav2Vec2ForPreTraining,
            Wav2Vec2ForSequenceClassification,
            Wav2Vec2ForXVector,
            Wav2Vec2Model,
            Wav2Vec2PreTrainedModel,
        )

if is_tf_available():
        from .modeling_tf_wav2vec2 import (
            TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFWav2Vec2ForCTC,
            TFWav2Vec2Model,
            TFWav2Vec2PreTrainedModel,
        )

if is_flax_available():
        from .modeling_tf_wav2vec2 import (
            FlaxWav2Vec2ForCTC,
            FlaxWav2Vec2ForPreTraining,
            FlaxWav2Vec2Model,
            FlaxWav2Vec2PreTrainedModel,
        )

else:
    import sys

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

# 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_flax_available, is_tf_available, is_torch_available _import_structure = { "configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"], "feature_extraction_wav2vec2": ["Wav2Vec2FeatureExtractor"], "processing_wav2vec2": ["Wav2Vec2Processor"], "tokenization_wav2vec2": ["Wav2Vec2CTCTokenizer", "Wav2Vec2Tokenizer"], } if is_torch_available(): _import_structure["modeling_wav2vec2"] = [ "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST", "Wav2Vec2ForAudioFrameClassification", "Wav2Vec2ForCTC", "Wav2Vec2ForMaskedLM", "Wav2Vec2ForPreTraining", "Wav2Vec2ForSequenceClassification", "Wav2Vec2ForXVector", "Wav2Vec2Model", "Wav2Vec2PreTrainedModel", ] if is_tf_available(): _import_structure["modeling_tf_wav2vec2"] = [ "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST", "TFWav2Vec2ForCTC", "TFWav2Vec2Model", "TFWav2Vec2PreTrainedModel", ] if is_flax_available(): _import_structure["modeling_flax_wav2vec2"] = [ "FlaxWav2Vec2ForCTC", "FlaxWav2Vec2ForPreTraining", "FlaxWav2Vec2Model", "FlaxWav2Vec2PreTrainedModel", ] if TYPE_CHECKING: from .configuration_wav2vec2 import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, Wav2Vec2Config from .feature_extraction_wav2vec2 import Wav2Vec2FeatureExtractor from .processing_wav2vec2 import Wav2Vec2Processor from .tokenization_wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2Tokenizer if is_torch_available(): from .modeling_wav2vec2 import ( WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, Wav2Vec2ForAudioFrameClassification, Wav2Vec2ForCTC, Wav2Vec2ForMaskedLM, Wav2Vec2ForPreTraining, Wav2Vec2ForSequenceClassification, Wav2Vec2ForXVector, Wav2Vec2Model, Wav2Vec2PreTrainedModel, ) if is_tf_available(): from .modeling_tf_wav2vec2 import ( TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, TFWav2Vec2ForCTC, TFWav2Vec2Model, TFWav2Vec2PreTrainedModel, ) if is_flax_available(): from .modeling_tf_wav2vec2 import ( FlaxWav2Vec2ForCTC, FlaxWav2Vec2ForPreTraining, FlaxWav2Vec2Model, FlaxWav2Vec2PreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)