


"""simple docstring"""







import flax.linen as nn
import jax
import jax.numpy as jnp






class 						_A  (  nn.Module  ):







    """simple docstring"""




    UpperCAmelCase	:							int
    UpperCAmelCase	:							jnp.dtype     =	jnp.floataa






    def      __snake_case							( self    :   List[Any]):
      a						:		Dict											=      nn.Conv(
          self.out_channels    ,			kernel_size=(3, 3)    ,			strides=(1, 1)    ,			padding=((1, 1), (1, 1))    ,			dtype=self.dtype    ,			)






    def __call__( self    :   List[str]    ,			__UpperCAmelCase    :   Optional[Any]):
      a						:		Union[str, Any]											=      hidden_states.shape
      a						:		List[str]											=      jax.image.resize(
          __UpperCAmelCase    ,			shape=(batch, height * 2, width * 2, channels)    ,			method="nearest"    ,			)
      a						:		List[Any]											=      self.conv(__UpperCAmelCase)
      return hidden_states






class 						_A  (  nn.Module  ):







    """simple docstring"""




    UpperCAmelCase	:							int
    UpperCAmelCase	:							jnp.dtype     =	jnp.floataa






    def      __snake_case							( self    :   str):
      a						:		Optional[Any]											=      nn.Conv(
          self.out_channels    ,			kernel_size=(3, 3)    ,			strides=(2, 2)    ,			padding=((1, 1), (1, 1))    ,			dtype=self.dtype    ,			)






    def __call__( self    :   int    ,			__UpperCAmelCase    :   str):
      # pad = ((0, 0), (0, 1), (0, 1), (0, 0))  # pad height and width dim
      # hidden_states = jnp.pad(hidden_states, pad_width=pad)
      a						:		int											=      self.conv(__UpperCAmelCase)
      return hidden_states






class 						_A  (  nn.Module  ):







    """simple docstring"""




    UpperCAmelCase	:							int
    UpperCAmelCase	:							int     =	None
    UpperCAmelCase	:							float     =	0.0
    UpperCAmelCase	:							bool     =	None
    UpperCAmelCase	:							jnp.dtype     =	jnp.floataa






    def      __snake_case							( self    :   Optional[Any]):
      a						:		Any											=      self.in_channels if self.out_channels is None else self.out_channels

      a						:		List[str]											=      nn.GroupNorm(num_groups=32    ,			epsilon=1e-5)
      a						:		str											=      nn.Conv(
          __UpperCAmelCase    ,			kernel_size=(3, 3)    ,			strides=(1, 1)    ,			padding=((1, 1), (1, 1))    ,			dtype=self.dtype    ,			)

      a						:		Union[str, Any]											=      nn.Dense(__UpperCAmelCase    ,			dtype=self.dtype)

      a						:		List[Any]											=      nn.GroupNorm(num_groups=32    ,			epsilon=1e-5)
      a						:		str											=      nn.Dropout(self.dropout_prob)
      a						:		str											=      nn.Conv(
          __UpperCAmelCase    ,			kernel_size=(3, 3)    ,			strides=(1, 1)    ,			padding=((1, 1), (1, 1))    ,			dtype=self.dtype    ,			)

      a						:		List[Any]											=      self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

      a						:		Tuple											=      None
      if use_nin_shortcut:
        a						:		Optional[Any]											=      nn.Conv(
            __UpperCAmelCase    ,			kernel_size=(1, 1)    ,			strides=(1, 1)    ,			padding="VALID"    ,			dtype=self.dtype    ,			)






    def __call__( self    :   List[str]    ,			__UpperCAmelCase    :   Dict    ,			__UpperCAmelCase    :   Optional[int]    ,			__UpperCAmelCase    :   Any=True):
      a						:		Optional[int]											=      hidden_states
      a						:		List[Any]											=      self.norma(__UpperCAmelCase)
      a						:		Union[str, Any]											=      nn.swish(__UpperCAmelCase)
      a						:		List[Any]											=      self.conva(__UpperCAmelCase)

      a						:		Optional[int]											=      self.time_emb_proj(nn.swish(__UpperCAmelCase))
      a						:		Optional[Any]											=      jnp.expand_dims(jnp.expand_dims(__UpperCAmelCase    ,			1)    ,			1)
      a						:		Any											=      hidden_states + temb

      a						:		Optional[int]											=      self.norma(__UpperCAmelCase)
      a						:		Optional[Any]											=      nn.swish(__UpperCAmelCase)
      a						:		List[str]											=      self.dropout(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		int											=      self.conva(__UpperCAmelCase)

      if self.conv_shortcut is not None:
        a						:		str											=      self.conv_shortcut(__UpperCAmelCase)

      return hidden_states + residual










"""simple docstring"""







def 					lowercase      (    A_  ,       A_	)->				float:
  '''simple docstring'''







  def get_matched_characters(A_  ,       A_	) -> str:
    a						:		Optional[int]											=      []
    a						:		List[Any]											=      min(len(_stra	)  ,       len(_stra	)	) // 2
    for i, l in enumerate(_stra	):
      a						:		int											=      int(max(0  ,       i - limit	)	)
      a						:		Optional[int]											=      int(min(i + limit + 1  ,       len(_stra	)	)	)
      if l in _stra[left:right]:
        matched.append(A_	)
        a						:		int											=      F'''{_stra[0:_stra.index(A_	)]} {_stra[_stra.index(A_	) + 1:]}'''

    return "".join(A_	)

  # matching characters
  a						:		Tuple											=      get_matched_characters(A_  ,       A_	)
  a						:		str											=      get_matched_characters(A_  ,       A_	)
  a						:		List[str]											=      len(A_	)

  # transposition
  a						:		Union[str, Any]											=      (
      len([(ca, ca) for ca, ca in zip(A_  ,       A_	) if ca != ca]	) // 2
  )

  if not match_count:
    a						:		Tuple											=      0.0
  else:
    a						:		List[str]											=      (
        1
        / 3
        * (
            match_count / len(A_	)
            + match_count / len(A_	)
            + (match_count - transpositions) / match_count
        )
    )

  # common prefix up to 4 characters
  a						:		Union[str, Any]											=      0
  for ca, ca in zip(stra[:4]  ,       stra[:4]	):
    if ca == ca:
      prefix_len += 1
    else:
      break

  return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(jaro_winkler("""hello""", """world"""))






