'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__snake_case   :      List[Any]						    =  {'configuration_regnet': ['REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RegNetConfig']}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case   :      Union[str, Any]						    =  [
      'REGNET_PRETRAINED_MODEL_ARCHIVE_LIST',
      'RegNetForImageClassification',
      'RegNetModel',
      'RegNetPreTrainedModel',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case   :      Tuple						    =  [
      'TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFRegNetForImageClassification',
      'TFRegNetModel',
      'TFRegNetPreTrainedModel',
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case   :      str						    =  [
      'FlaxRegNetForImageClassification',
      'FlaxRegNetModel',
      'FlaxRegNetPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_regnet import (
        REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        RegNetForImageClassification,
        RegNetModel,
        RegNetPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_regnet import (
        TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFRegNetForImageClassification,
        TFRegNetModel,
        TFRegNetPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_regnet import (
        FlaxRegNetForImageClassification,
        FlaxRegNetModel,
        FlaxRegNetPreTrainedModel,
    )


else:
  import sys

  __snake_case   :      Optional[Any]						    =  _LazyModule(__name__, globals()['__file__'], _import_structure)








"""simple docstring"""




from __future__ import annotations

def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			):
					SCREAMING_SNAKE_CASE	,    SCREAMING_SNAKE_CASE				=	m - 1, 0
					while i >= 0 and j < n:
										if key == mat[i][j]:
															print(f'''Key {key} found at row- {i + 1} column- {j + 1}'''			)
															return
										if key < mat[i][j]:
															i -= 1
										else:
															j += 1
					print(f'''Key {key} not found'''			)

def   UpperCamelCase_  (		):
					SCREAMING_SNAKE_CASE				=	[[2, 5, 7], [4, 8, 1_3], [9, 1_1, 1_5], [1_2, 1_7, 2_0]]
					SCREAMING_SNAKE_CASE				=	int(input('Enter the element to be searched:'			)			)
					print(SCREAMING_SNAKE_CASE_			)
					search_in_a_sorted_matrix(SCREAMING_SNAKE_CASE_,     len(SCREAMING_SNAKE_CASE_			),     len(mat[0]			),     SCREAMING_SNAKE_CASE_			)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()
