





'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_tf_available,
    is_torch_available,
)


__lowerCamelCase						: str		=   {
    'configuration_speech_to_text': ['SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Speech2TextConfig'],
    'processing_speech_to_text': ['Speech2TextProcessor'],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						: List[str]		=   ['Speech2TextTokenizer']

try:
      if not is_speech_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						: str		=   ['Speech2TextFeatureExtractor']

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						: Optional[Any]		=   [
          'TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFSpeech2TextForConditionalGeneration',
          'TFSpeech2TextModel',
          'TFSpeech2TextPreTrainedModel',
      ]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						: Union[str, Any]		=   [
          '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, SpeechaTextConfig
      from .processing_speech_to_text import SpeechaTextProcessor

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_speech_to_text import SpeechaTextTokenizer

      try:
            if not is_speech_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_speech_to_text import (
                TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFSpeechaTextForConditionalGeneration,
                TFSpeechaTextModel,
                TFSpeechaTextPreTrainedModel,
            )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_speech_to_text import (
                SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                SpeechaTextForConditionalGeneration,
                SpeechaTextModel,
                SpeechaTextPreTrainedModel,
            )

else:
      import sys

      __lowerCamelCase						: Optional[int]		=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)













'''simple docstring'''






# Copyright 2023 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 OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase						: Optional[int]		=   {
    'configuration_xmod': [
        'XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'XmodConfig',
        'XmodOnnxConfig',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						: int		=   [
          'XMOD_PRETRAINED_MODEL_ARCHIVE_LIST',
          'XmodForCausalLM',
          'XmodForMaskedLM',
          'XmodForMultipleChoice',
          'XmodForQuestionAnswering',
          'XmodForSequenceClassification',
          'XmodForTokenClassification',
          'XmodModel',
          'XmodPreTrainedModel',
      ]

if TYPE_CHECKING:
      from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_xmod import (
                XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
                XmodForCausalLM,
                XmodForMaskedLM,
                XmodForMultipleChoice,
                XmodForQuestionAnswering,
                XmodForSequenceClassification,
                XmodForTokenClassification,
                XmodModel,
                XmodPreTrainedModel,
            )

else:
      import sys

      __lowerCamelCase						: Dict		=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






