'''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,
    is_vision_available,
)


UpperCamelCase    :			Union[str, Any]						     =  {
    """configuration_tvlt""": ["""TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TvltConfig"""],
    """feature_extraction_tvlt""": ["""TvltFeatureExtractor"""],
    """processing_tvlt""": ["""TvltProcessor"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    :			Optional[int]						     =  [
          """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TvltModel""",
          """TvltForPreTraining""",
          """TvltForAudioVisualClassification""",
          """TvltPreTrainedModel""",
      ]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    :			Tuple						     =  ["""TvltImageProcessor"""]


if TYPE_CHECKING:
      from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
      from .processing_tvlt import TvltProcessor
      from .feature_extraction_tvlt import TvltFeatureExtractor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tvlt import (
                TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TvltForAudioVisualClassification,
                TvltForPreTraining,
                TvltModel,
                TvltPreTrainedModel,
            )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_tvlt import TvltImageProcessor


else:
      import sys

      UpperCamelCase    :			Union[str, Any]						     =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






def        __a     (    lowerCAmelCase_   :					list				)      -> bool:






						'''simple docstring'''



						if not isinstance(lowerCAmelCase_			,lowerCAmelCase_				):
												raise ValueError("""Input series is not valid, valid series - [1, 2/3, 2]"""				)
						if len(lowerCAmelCase_				) == 0:
												raise ValueError("""Input list must be a non empty list"""				)
						if len(lowerCAmelCase_				) == 1 and series[0] != 0:
												return True
						UpperCAmelCase_=   []
						UpperCAmelCase_=   len(lowerCAmelCase_				)
						for i in range(0			,lowerCAmelCase_				):
												if series[i] == 0:
																		raise ValueError("""Input series cannot have 0 as an element"""				)
												rec_series.append(1 / series[i]				)
						UpperCAmelCase_=   rec_series[1] - rec_series[0]
						for index in range(2			,lowerCAmelCase_				):
												if rec_series[index] - rec_series[index - 1] != common_diff:
																		return False
						return True



def        __a     (    lowerCAmelCase_   :					list				)      -> float:






						'''simple docstring'''



						if not isinstance(lowerCAmelCase_			,lowerCAmelCase_				):
												raise ValueError("""Input series is not valid, valid series - [2, 4, 6]"""				)
						if len(lowerCAmelCase_				) == 0:
												raise ValueError("""Input list must be a non empty list"""				)
						UpperCAmelCase_=   0
						for val in series:
												answer += 1 / val
						return len(lowerCAmelCase_				) / answer


if __name__ == "__main__":
	import doctest

	doctest.testmod()




