


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


lowerCamelCase					:		str            =						logging.get_logger(__name__)

lowerCamelCase					:		str            =						{"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase					:		Tuple            =						{
    """vocab_file""": {
        """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_char_small""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_chinese_char_base""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_discriminator""": (
            """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_generator""": (
            """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"""
        ),
    }
}

lowerCamelCase					:		str            =						{
    """junnyu/roformer_chinese_small""": 1_5_3_6,
    """junnyu/roformer_chinese_base""": 1_5_3_6,
    """junnyu/roformer_chinese_char_small""": 5_1_2,
    """junnyu/roformer_chinese_char_base""": 5_1_2,
    """junnyu/roformer_small_discriminator""": 1_2_8,
    """junnyu/roformer_small_generator""": 1_2_8,
}


lowerCamelCase					:		Tuple            =						{
    """junnyu/roformer_chinese_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_base""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_base""": {"""do_lower_case""": True},
    """junnyu/roformer_small_discriminator""": {"""do_lower_case""": True},
    """junnyu/roformer_small_generator""": {"""do_lower_case""": True},
}


class snake_case__			(    _UpperCAmelCase					):
       _lowerCAmelCase   =VOCAB_FILES_NAMES
       _lowerCAmelCase   =PRETRAINED_VOCAB_FILES_MAP
       _lowerCAmelCase   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _lowerCAmelCase   =PRETRAINED_INIT_CONFIGURATION
       _lowerCAmelCase   =RoFormerTokenizer




       def __init__( self				:    Union[str, Any]    ,				_lowerCamelCase				:    Optional[Any]=None    ,				_lowerCamelCase				:    List[str]=None    ,				_lowerCamelCase				:    Union[str, Any]=True    ,				_lowerCamelCase				:    Tuple="[UNK]"    ,				_lowerCamelCase				:    Optional[int]="[SEP]"    ,				_lowerCamelCase				:    List[Any]="[PAD]"    ,				_lowerCamelCase				:    int="[CLS]"    ,				_lowerCamelCase				:    Optional[Any]="[MASK]"    ,				_lowerCamelCase				:    Tuple=True    ,				_lowerCamelCase				:    Dict=None    ,				**_lowerCamelCase				:    Tuple    ,				):
              super().__init__(
                  SCREAMING_SNAKE_CASE_    ,				tokenizer_file=SCREAMING_SNAKE_CASE_    ,				do_lower_case=SCREAMING_SNAKE_CASE_    ,				unk_token=SCREAMING_SNAKE_CASE_    ,				sep_token=SCREAMING_SNAKE_CASE_    ,				pad_token=SCREAMING_SNAKE_CASE_    ,				cls_token=SCREAMING_SNAKE_CASE_    ,				mask_token=SCREAMING_SNAKE_CASE_    ,				tokenize_chinese_chars=SCREAMING_SNAKE_CASE_    ,				strip_accents=SCREAMING_SNAKE_CASE_    ,				**SCREAMING_SNAKE_CASE_    ,				)

              snake_case__ :       Optional[int]	   =							json.loads(self.backend_tokenizer.normalizer.__getstate__()			)
              if (
                  pre_tok_state.get('lowercase'    ,				SCREAMING_SNAKE_CASE_			) != do_lower_case
                  or pre_tok_state.get('strip_accents'    ,				SCREAMING_SNAKE_CASE_			) != strip_accents
              ):
                     snake_case__ :       Optional[int]	   =							getattr(SCREAMING_SNAKE_CASE_    ,				pre_tok_state.pop('type'			)			)
                     snake_case__ :       Union[str, Any]	   =							do_lower_case
                     snake_case__ :       str	   =							strip_accents
                     snake_case__ :       Optional[Any]	   =							pre_tok_class(**SCREAMING_SNAKE_CASE_			)

              snake_case__ :       Tuple	   =							do_lower_case




       def __getstate__( self				:    Union[str, Any]			):
              snake_case__ :       Union[str, Any]	   =							self.__dict__.copy()
              snake_case__ :       Dict	   =							BertPreTokenizer()
              return state




       def __setstate__( self				:    Optional[int]    ,				_lowerCamelCase				:    Dict			):
              snake_case__ :       Optional[int]	   =							d
              snake_case__ :       List[Any]	   =							self.__dict__['_tokenizer'].get_vocab()
              snake_case__ :       Union[str, Any]	   =							PreTokenizer.custom(JiebaPreTokenizer(SCREAMING_SNAKE_CASE_			)			)




       def     UpperCAmelCase__    ( self				:    List[str]    ,				_lowerCamelCase				:    List[str]    ,				_lowerCamelCase				:    Optional[int]=None			):
              snake_case__ :       Union[str, Any]	   =							[self.cls_token_id] + token_ids_a + [self.sep_token_id]

              if token_ids_a:
                     output += token_ids_a + [self.sep_token_id]

              return output




       def     UpperCAmelCase__    ( self				:    int    ,				_lowerCamelCase				:    Optional[Any]    ,				_lowerCamelCase				:    int = None			):
              snake_case__ :       List[str]	   =							[self.sep_token_id]
              snake_case__ :       Dict	   =							[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     UpperCAmelCase__    ( self				:    str    ,				_lowerCamelCase				:    int    ,				_lowerCamelCase				:    Union[str, Any] = None			):
              snake_case__ :       Optional[Any]	   =							self._tokenizer.model.save(SCREAMING_SNAKE_CASE_    ,				name=SCREAMING_SNAKE_CASE_			)
              return tuple(SCREAMING_SNAKE_CASE_			)




       def     UpperCAmelCase__    ( self				:    Union[str, Any]    ,				_lowerCamelCase				:    Any    ,				_lowerCamelCase				:    Union[str, Any]=None    ,				_lowerCamelCase				:    int=None    ,				_lowerCamelCase				:    Any=False    ,				**_lowerCamelCase				:    Optional[Any]    ,				):
              snake_case__ :       Tuple	   =							BertPreTokenizer()
              return super().save_pretrained(SCREAMING_SNAKE_CASE_    ,				SCREAMING_SNAKE_CASE_    ,				SCREAMING_SNAKE_CASE_    ,				SCREAMING_SNAKE_CASE_    ,				**SCREAMING_SNAKE_CASE_			)









'''simple docstring'''



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





class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






    lowerCamelCase    :   int
    lowerCamelCase    :   jnp.dtype					=     jnp.floataa







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      Optional[Any]														=						nn.Conv(
             self.out_channels     ,	kernel_size=(3, 3)     ,	strides=(1, 1)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_      )							->	Any:
         __lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase							,			__lowerCamelCase  :      Optional[int]														=						hidden_states.shape
         __lowerCamelCase  :      Dict														=						jax.image.resize(
             SCREAMING_SNAKE_CASE_     ,	shape=(batch, height * 2, width * 2, channels)     ,	method='nearest'     ,	)
         __lowerCamelCase  :      Optional[Any]														=						self.conv(SCREAMING_SNAKE_CASE_      )
         return hidden_states







class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






    lowerCamelCase    :   int
    lowerCamelCase    :   jnp.dtype					=     jnp.floataa







    def  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      str														=						nn.Conv(
             self.out_channels     ,	kernel_size=(3, 3)     ,	strides=(2, 2)     ,	padding=((1, 1), (1, 1))     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_      )							->	List[str]:
         # pad = ((0, 0), (0, 1), (0, 1), (0, 0))  # pad height and width dim
         # hidden_states = jnp.pad(hidden_states, pad_width=pad)
         __lowerCamelCase  :      str														=						self.conv(SCREAMING_SNAKE_CASE_      )
         return hidden_states







class   UpperCAmelCase_    (nn.Module    ):





    """simple docstring"""






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







    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Optional[Any]														=						self.in_channels if self.out_channels is None else self.out_channels

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

         __lowerCamelCase  :      List[str]														=						nn.Dense(SCREAMING_SNAKE_CASE_     ,	dtype=self.dtype      )

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

         __lowerCamelCase  :      Optional[int]														=						self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

         __lowerCamelCase  :      List[Any]														=						None
         if use_nin_shortcut:
              __lowerCamelCase  :      Any														=						nn.Conv(
                  SCREAMING_SNAKE_CASE_     ,	kernel_size=(1, 1)     ,	strides=(1, 1)     ,	padding='VALID'     ,	dtype=self.dtype     ,	)







    def __call__(				self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_=True      )							->	Tuple:
         __lowerCamelCase  :      List[Any]														=						hidden_states
         __lowerCamelCase  :      str														=						self.norma(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						nn.swish(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						self.conva(SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      str														=						self.time_emb_proj(nn.swish(SCREAMING_SNAKE_CASE_      )      )
         __lowerCamelCase  :      List[str]														=						jnp.expand_dims(jnp.expand_dims(SCREAMING_SNAKE_CASE_     ,	1      )     ,	1      )
         __lowerCamelCase  :      Optional[int]														=						hidden_states + temb

         __lowerCamelCase  :      List[Any]														=						self.norma(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Any														=						nn.swish(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      List[Any]														=						self.dropout(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      List[Any]														=						self.conva(SCREAMING_SNAKE_CASE_      )

         if self.conv_shortcut is not None:
              __lowerCamelCase  :      List[str]														=						self.conv_shortcut(SCREAMING_SNAKE_CASE_      )

         return hidden_states + residual






