

'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp


class    a__  (							nn.Module  ):
   _SCREAMING_SNAKE_CASE    :     Tuple	       =							42
   _SCREAMING_SNAKE_CASE    :     str	       =							jnp.floataa


   def 						_lowerCamelCase   ( self  ):





      """simple docstring"""





      _lowercase			:      Optional[int]			     =   nn.Conv(
          self.out_channels			,				kernel_size=(3, 3)			,				strides=(1, 1)			,				padding=((1, 1), (1, 1))			,				dtype=self.dtype			,				)






   def __call__( self			,				_UpperCamelCase  ):





      """simple docstring"""





      _lowercase     ,      _lowercase     ,      _lowercase     ,      _lowercase			:      Optional[Any]			     =   hidden_states.shape
      _lowercase			:      Optional[int]			     =   jax.image.resize(
          A_			,				shape=(batch, height * 2, width * 2, channels)			,				method="nearest"			,				)
      _lowercase			:      Dict			     =   self.conv(A_  )
      return hidden_states




class    a__  (							nn.Module  ):
   _SCREAMING_SNAKE_CASE    :     Union[str, Any]	       =							42
   _SCREAMING_SNAKE_CASE    :     str	       =							jnp.floataa


   def 						_lowerCamelCase   ( self  ):





      """simple docstring"""





      _lowercase			:      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			,				_UpperCamelCase  ):





      """simple docstring"""





      _lowercase			:      List[str]			     =   self.conv(A_  )
      return hidden_states




class    a__  (							nn.Module  ):
   _SCREAMING_SNAKE_CASE    :     Tuple	       =							42
   _SCREAMING_SNAKE_CASE    :     Any	       =							None
   _SCREAMING_SNAKE_CASE    :     List[str]	       =							0.0
   _SCREAMING_SNAKE_CASE    :     Tuple	       =							None
   _SCREAMING_SNAKE_CASE    :     Union[str, Any]	       =							jnp.floataa


   def 						_lowerCamelCase   ( self  ):





      """simple docstring"""





      _lowercase			:      Any			     =   self.in_channels if self.out_channels is None else self.out_channels

      _lowercase			:      Optional[int]			     =   nn.GroupNorm(num_groups=32			,				epsilon=1E-5  )
      _lowercase			:      Any			     =   nn.Conv(
          A_			,				kernel_size=(3, 3)			,				strides=(1, 1)			,				padding=((1, 1), (1, 1))			,				dtype=self.dtype			,				)

      _lowercase			:      Any			     =   nn.Dense(A_			,				dtype=self.dtype  )

      _lowercase			:      str			     =   nn.GroupNorm(num_groups=32			,				epsilon=1E-5  )
      _lowercase			:      int			     =   nn.Dropout(self.dropout_prob  )
      _lowercase			:      Union[str, Any]			     =   nn.Conv(
          A_			,				kernel_size=(3, 3)			,				strides=(1, 1)			,				padding=((1, 1), (1, 1))			,				dtype=self.dtype			,				)

      _lowercase			:      Optional[Any]			     =   self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

      _lowercase			:      Union[str, Any]			     =   None
      if use_nin_shortcut:
         _lowercase			:      int			     =   nn.Conv(
             A_			,				kernel_size=(1, 1)			,				strides=(1, 1)			,				padding="VALID"			,				dtype=self.dtype			,				)






   def __call__( self			,				_UpperCamelCase			,				_UpperCamelCase			,				_UpperCamelCase=True  ):





      """simple docstring"""





      _lowercase			:      Tuple			     =   hidden_states
      _lowercase			:      List[Any]			     =   self.norma(A_  )
      _lowercase			:      int			     =   nn.swish(A_  )
      _lowercase			:      List[str]			     =   self.conva(A_  )

      _lowercase			:      str			     =   self.time_emb_proj(nn.swish(A_  )  )
      _lowercase			:      str			     =   jnp.expand_dims(jnp.expand_dims(A_			,				1  )			,				1  )
      _lowercase			:      str			     =   hidden_states + temb

      _lowercase			:      Dict			     =   self.norma(A_  )
      _lowercase			:      Dict			     =   nn.swish(A_  )
      _lowercase			:      Optional[int]			     =   self.dropout(A_			,				A_  )
      _lowercase			:      Dict			     =   self.conva(A_  )

      if self.conv_shortcut is not None:
         _lowercase			:      Optional[Any]			     =   self.conv_shortcut(A_  )

      return hidden_states + residual












import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_fnet import FNetTokenizer
else:
 lowerCamelCase				:		List[Any]     =   None

lowerCamelCase				:		int     =   logging.get_logger(__name__)
lowerCamelCase				:		Optional[int]     =   {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase				:		Optional[int]     =   {
    "vocab_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/spiece.model",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json",
    },
}

lowerCamelCase				:		List[Any]     =   {
    "google/fnet-base": 512,
    "google/fnet-large": 512,
}

lowerCamelCase				:		Any     =   "▁"







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						VOCAB_FILES_NAMES
 UpperCamelCase						   =						PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase						   =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCamelCase						   =						['''input_ids''', '''token_type_ids''']
 UpperCamelCase						   =						FNetTokenizer

 def __init__(				self					:  Optional[int]						,							A_					:  Any=None						,							A_					:  int=None						,							A_					:  int=False						,							A_					:  Optional[int]=True						,							A_					:  List[Any]=True						,							A_					:  Tuple="<unk>"						,							A_					:  Optional[int]="[SEP]"						,							A_					:  List[Any]="<pad>"						,							A_					:  Optional[int]="[CLS]"						,							A_					:  Optional[Any]="[MASK]"						,							**A_					:  Dict						,							)   ->	List[str]:

       """simple docstring"""






       lowerCamelCase_		     =    (
           AddedToken(A_						,							lstrip=A_						,							rstrip=A_						,							normalized=A_  )
           if isinstance(A_						,							A_  )
           else mask_token
       )

       super().__init__(
           A_						,							tokenizer_file=A_						,							do_lower_case=A_						,							remove_space=A_						,							keep_accents=A_						,							unk_token=A_						,							sep_token=A_						,							pad_token=A_						,							cls_token=A_						,							mask_token=A_						,							**A_						,							)

       lowerCamelCase_		     =    do_lower_case
       lowerCamelCase_		     =    remove_space
       lowerCamelCase_		     =    keep_accents
       lowerCamelCase_		     =    vocab_file
       lowerCamelCase_		     =    False if not self.vocab_file else True

 def 				a__ (				self					:  List[Any]						,							A_					:  List[int]						,							A_					:  Optional[List[int]] = None  )   ->	List[int]:

       """simple docstring"""






       lowerCamelCase_		     =    [self.sep_token_id]
       lowerCamelCase_		     =    [self.cls_token_id]
       if token_ids_a is None:
             return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep

 def 				a__ (				self					:  Tuple						,							A_					:  List[int]						,							A_					:  Optional[List[int]] = None  )   ->	List[int]:

       """simple docstring"""






       lowerCamelCase_		     =    [self.sep_token_id]
       lowerCamelCase_		     =    [self.cls_token_id]

       if token_ids_a is None:
             return len(cls + token_ids_a + sep  ) * [0]
       return len(cls + token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]





 def 				a__ (				self					:  Dict						,							A_					:  str						,							A_					:  Optional[str] = None  )   ->	Tuple[str]:

       """simple docstring"""






       if not os.path.isdir(A_  ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
             return
       lowerCamelCase_		     =    os.path.join(
           A_						,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']  )

       if os.path.abspath(self.vocab_file  ) != os.path.abspath(A_  ):
             copyfile(self.vocab_file						,							A_  )

       return (out_vocab_file,)



