






"""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											=     {
    """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											=     [
         """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TvltModel""",
         """TvltForPreTraining""",
         """TvltForAudioVisualClassification""",
         """TvltPreTrainedModel""",
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase											=     ["""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											=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""




import math






def 							lowerCAmelCase			(   UpperCamelCase_:				int       )							->				list:







  '''simple docstring'''







  if n <= 0:
    raise ValueError("Only positive integers have prime factors"       )
  _a					      =						[]
  while n % 2 == 0:
    pf.append(2       )
    _a					      =						int(n / 2       )
  for i in range(3  ,			int(math.sqrt(UpperCamelCase_       )       ) + 1  ,			2       ):
    while n % i == 0:
      pf.append(UpperCamelCase_       )
      _a					      =						int(n / i       )
  if n > 2:
    pf.append(UpperCamelCase_       )
  return pf






def 							lowerCAmelCase			(   UpperCamelCase_:				int       )							->				int:







  '''simple docstring'''







  if n <= 0:
    raise ValueError("Only positive numbers are accepted"       )
  _a					      =						1
  _a					      =						1
  while n % 2 == 0:
    temp += 1
    _a					      =						int(n / 2       )
  div *= temp
  for i in range(3  ,			int(math.sqrt(UpperCamelCase_       )       ) + 1  ,			2       ):
    _a					      =						1
    while n % i == 0:
      temp += 1
      _a					      =						int(n / i       )
    div *= temp
  if n > 1:
    div *= 2
  return div






def 							lowerCAmelCase			(   UpperCamelCase_:				int       )							->				int:







  '''simple docstring'''







  if n <= 0:
    raise ValueError("Only positive numbers are accepted"       )
  _a					      =						1
  _a					      =						1
  while n % 2 == 0:
    temp += 1
    _a					      =						int(n / 2       )
  if temp > 1:
    s *= (2**temp - 1) / (2 - 1)
  for i in range(3  ,			int(math.sqrt(UpperCamelCase_       )       ) + 1  ,			2       ):
    _a					      =						1
    while n % i == 0:
      temp += 1
      _a					      =						int(n / i       )
    if temp > 1:
      s *= (i**temp - 1) / (i - 1)
  return int(UpperCamelCase_       )






def 							lowerCAmelCase			(   UpperCamelCase_:				int       )							->				int:







  '''simple docstring'''







  _a					      =						n
  for x in set(prime_factors(UpperCamelCase_       )       ):
    s *= (x - 1) / x
  return int(UpperCamelCase_       )


if __name__ == "__main__":
     import doctest

     doctest.testmod()


