


# 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,
)


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

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case   = ["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

     _snake_case   = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







from collections.abc import Callable

_snake_case   = Callable[[float], float]  # type alias for a real -> real function







def   A   (		A__		,		A__		,		A__		,		):
     UpperCAmelCase						:				Any		  =			float(A__ )
     while True:
          try:
               UpperCAmelCase						:				Optional[Any]		  =			prev_guess - function(A__ ) / derivative(A__ )
          except ZeroDivisionError:
               raise ZeroDivisionError("Could not find root" ) from None
          if abs(prev_guess - next_guess ) < 1_0**-5:
               return next_guess
          UpperCAmelCase						:				List[str]		  =			next_guess







def   A   (		A__ ):
     return (x**3) - (2 * x) - 5







def   A   (		A__ ):
     return 3 * (x**2) - 2


if __name__ == "__main__":
      print(newton(f, fa, 3))



