


'''simple docstring'''






import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


__UpperCAmelCase       							=				logging.get_logger(__name__)

__UpperCAmelCase       							=				{"vocab_file": "spiece.model"}

__UpperCAmelCase       							=				{
    "vocab_file": {
        "xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model",
        "xlnet-large-cased": "https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model",
    }
}

__UpperCAmelCase       							=				{
    "xlnet-base-cased": None,
    "xlnet-large-cased": None,
}

# Segments (not really needed)
__UpperCAmelCase       							=				0
__UpperCAmelCase       							=				1
__UpperCAmelCase       							=				2
__UpperCAmelCase       							=				3
__UpperCAmelCase       							=				4




class 						a__							(				UpperCamelCase__    ):





							'''simple docstring'''






							lowercase__     :  List[str]      		= VOCAB_FILES_NAMES
							lowercase__     :  Union[str, Any]      		= PRETRAINED_VOCAB_FILES_MAP
							lowercase__     :  Dict      		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__     :  int      		= "left"







							def __init__(						self   ,       lowerCamelCase_   ,       lowerCamelCase_=False   ,       lowerCamelCase_=True   ,       lowerCamelCase_=False   ,       lowerCamelCase_="<s>"   ,       lowerCamelCase_="</s>"   ,       lowerCamelCase_="<unk>"   ,       lowerCamelCase_="<sep>"   ,       lowerCamelCase_="<pad>"   ,       lowerCamelCase_="<cls>"   ,       lowerCamelCase_="<mask>"   ,       lowerCamelCase_=["<eop>", "<eod>"]   ,       lowerCamelCase_ = None   ,       **lowerCamelCase_   ,       )			->				None:
														# Mask token behave like a normal word, i.e. include the space before it
														lowerCAmelCase__			  =      AddedToken(lowercase_   ,       lstrip=lowercase_   ,       rstrip=lowercase_  ) if isinstance(lowercase_   ,       lowercase_  ) else mask_token

														lowerCAmelCase__			  =      {} if sp_model_kwargs is None else sp_model_kwargs

														super().__init__(
														    do_lower_case=lowercase_   ,       remove_space=lowercase_   ,       keep_accents=lowercase_   ,       bos_token=lowercase_   ,       eos_token=lowercase_   ,       unk_token=lowercase_   ,       sep_token=lowercase_   ,       pad_token=lowercase_   ,       cls_token=lowercase_   ,       mask_token=lowercase_   ,       additional_special_tokens=lowercase_   ,       sp_model_kwargs=self.sp_model_kwargs   ,       **lowercase_   ,       )

														lowerCAmelCase__			  =      3

														lowerCAmelCase__			  =      do_lower_case
														lowerCAmelCase__			  =      remove_space
														lowerCAmelCase__			  =      keep_accents
														lowerCAmelCase__			  =      vocab_file

														lowerCAmelCase__			  =      spm.SentencePieceProcessor(**self.sp_model_kwargs  )
														self.sp_model.Load(lowercase_  )







							@property
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Any:
														return len(self.sp_model  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Union[str, Any]:
														lowerCAmelCase__			  =      {self.convert_ids_to_tokens(lowercase_  ): i for i in range(self.vocab_size  )}
														vocab.update(self.added_tokens_encoder  )
														return vocab







							def __getstate__(						self  )			->				int:
														lowerCAmelCase__			  =      self.__dict__.copy()
														lowerCAmelCase__			  =      None
														return state







							def __setstate__(						self   ,       lowerCamelCase_  )			->				int:
														lowerCAmelCase__			  =      d

														# for backward compatibility
														if not hasattr(self   ,       '''sp_model_kwargs'''  ):
																					lowerCAmelCase__			  =      {}

														lowerCAmelCase__			  =      spm.SentencePieceProcessor(**self.sp_model_kwargs  )
														self.sp_model.Load(self.vocab_file  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				int:
														if self.remove_space:
																					lowerCAmelCase__			  =      ''' '''.join(inputs.strip().split()  )
														else:
																					lowerCAmelCase__			  =      inputs
														lowerCAmelCase__			  =      outputs.replace('''``'''   ,       '''\"'''  ).replace('''\'\''''   ,       '''\"'''  )

														if not self.keep_accents:
																					lowerCAmelCase__			  =      unicodedata.normalize('''NFKD'''   ,       lowercase_  )
																					lowerCAmelCase__			  =      ''''''.join([c for c in outputs if not unicodedata.combining(lowercase_  )]  )
														if self.do_lower_case:
																					lowerCAmelCase__			  =      outputs.lower()

														return outputs







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				List[str]:
														lowerCAmelCase__			  =      self.preprocess_text(lowercase_  )
														lowerCAmelCase__			  =      self.sp_model.encode(lowercase_   ,       out_type=lowercase_  )
														lowerCAmelCase__			  =      []
														for piece in pieces:
																					if len(lowercase_  ) > 1 and piece[-1] == str(''','''  ) and piece[-2].isdigit():
																												lowerCAmelCase__			  =      self.sp_model.EncodeAsPieces(piece[:-1].replace(lowercase_   ,       ''''''  )  )
																												if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																																			if len(cur_pieces[0]  ) == 1:
																																										lowerCAmelCase__			  =      cur_pieces[1:]
																																			else:
																																										lowerCAmelCase__			  =      cur_pieces[0][1:]
																												cur_pieces.append(piece[-1]  )
																												new_pieces.extend(lowercase_  )
																					else:
																												new_pieces.append(lowercase_  )

														return new_pieces







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				Optional[int]:
														return self.sp_model.PieceToId(lowercase_  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				List[str]:
														return self.sp_model.IdToPiece(lowercase_  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				str:
														lowerCAmelCase__			  =      ''''''.join(lowercase_  ).replace(lowercase_   ,       ''' '''  ).strip()
														return out_string







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = False   ,       lowerCamelCase_ = None   ,       lowerCamelCase_ = True   ,       **lowerCamelCase_   ,       )			->				str:
														lowerCAmelCase__			  =      kwargs.pop('''use_source_tokenizer'''   ,       lowercase_  )

														lowerCAmelCase__			  =      self.convert_ids_to_tokens(lowercase_   ,       skip_special_tokens=lowercase_  )

														# To avoid mixing byte-level and unicode for byte-level BPT
														# we need to build string separately for added tokens and byte-level tokens
														# cf. https://github.com/huggingface/transformers/issues/1133
														lowerCAmelCase__			  =      []
														lowerCAmelCase__			  =      []
														for token in filtered_tokens:
																					if skip_special_tokens and token in self.all_special_ids:
																												continue
																					if token in self.added_tokens_encoder:
																												if current_sub_text:
																																			sub_texts.append(self.convert_tokens_to_string(lowercase_  )  )
																																			lowerCAmelCase__			  =      []
																												sub_texts.append(lowercase_  )
																					else:
																												current_sub_text.append(lowercase_  )
														if current_sub_text:
																					sub_texts.append(self.convert_tokens_to_string(lowercase_  )  )

														# Mimic the behavior of the Rust tokenizer:
														# By default, there are no spaces between special tokens
														lowerCAmelCase__			  =      ''''''.join(lowercase_  )

														lowerCAmelCase__			  =      (
														    clean_up_tokenization_spaces
														    if clean_up_tokenization_spaces is not None
														    else self.clean_up_tokenization_spaces
														)
														if clean_up_tokenization_spaces:
																					lowerCAmelCase__			  =      self.clean_up_tokenization(lowercase_  )
																					return clean_text
														else:
																					return text







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None  )			->				List[int]:
														lowerCAmelCase__			  =      [self.sep_token_id]
														lowerCAmelCase__			  =      [self.cls_token_id]
														if token_ids_a is None:
																					return token_ids_a + sep + cls
														return token_ids_a + sep + token_ids_a + sep + cls







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None   ,       lowerCamelCase_ = False  )			->				List[int]:

														if already_has_special_tokens:
																					return super().get_special_tokens_mask(
																					    token_ids_a=lowercase_   ,       token_ids_a=lowercase_   ,       already_has_special_tokens=lowercase_  )

														if token_ids_a is not None:
																					return ([0] * len(lowercase_  )) + [1] + ([0] * len(lowercase_  )) + [1, 1]
														return ([0] * len(lowercase_  )) + [1, 1]







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None  )			->				List[int]:
														lowerCAmelCase__			  =      [self.sep_token_id]
														lowerCAmelCase__			  =      [2]

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







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None  )			->				Tuple[str]:
														if not os.path.isdir(lowercase_  ):
																					logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""  )
																					return
														lowerCAmelCase__			  =      os.path.join(
														    lowercase_   ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

														if os.path.abspath(self.vocab_file  ) != os.path.abspath(lowercase_  ) and os.path.isfile(self.vocab_file  ):
																					copyfile(self.vocab_file   ,       lowercase_  )
														elif not os.path.isfile(self.vocab_file  ):
																					with open(lowercase_   ,       '''wb'''  ) as fi:
																												lowerCAmelCase__			  =      self.sp_model.serialized_model_proto()
																												fi.write(lowercase_  )

														return (out_vocab_file,)






'''simple docstring'''

from dataclasses import dataclass
from typing import Optional, Tuple, Union

import torch
import torch.nn as nn

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, VectorQuantizer






@dataclass
class   UpperCAmelCase      (			UpperCamelCase__							):
 __lowercase  						=							42






class   UpperCAmelCase      (			UpperCamelCase__     ,			UpperCamelCase__							):
 @register_to_config
 def __init__(							self :Tuple		,			lowercase_ :int = 3		,			lowercase_ :int = 3		,			lowercase_ :Tuple[str] = ("DownEncoderBlock2D",)		,			lowercase_ :Tuple[str] = ("UpDecoderBlock2D",)		,			lowercase_ :Tuple[int] = (64,)		,			lowercase_ :int = 1		,			lowercase_ :str = "silu"		,			lowercase_ :int = 3		,			lowercase_ :int = 32		,			lowercase_ :int = 2_56		,			lowercase_ :int = 32		,			lowercase_ :Optional[int] = None		,			lowercase_ :float = 0.1_8_2_1_5		,			lowercase_ :str = "group"		,			)->				Optional[int]:
     super().__init__()

     # pass init params to Encoder
     A__							=     Encoder(
         in_channels=lowercase_		,			out_channels=lowercase_		,			down_block_types=lowercase_		,			block_out_channels=lowercase_		,			layers_per_block=lowercase_		,			act_fn=lowercase_		,			norm_num_groups=lowercase_		,			double_z=lowercase_		,			)

     A__							=     vq_embed_dim if vq_embed_dim is not None else latent_channels

     A__							=     nn.Convad(lowercase_		,			lowercase_		,			1				)
     A__							=     VectorQuantizer(lowercase_		,			lowercase_		,			beta=0.2_5		,			remap=lowercase_		,			sane_index_shape=lowercase_				)
     A__							=     nn.Convad(lowercase_		,			lowercase_		,			1				)

     # pass init params to Decoder
     A__							=     Decoder(
         in_channels=lowercase_		,			out_channels=lowercase_		,			up_block_types=lowercase_		,			block_out_channels=lowercase_		,			layers_per_block=lowercase_		,			act_fn=lowercase_		,			norm_num_groups=lowercase_		,			norm_type=lowercase_		,			)
 @apply_forward_hook
 def 	UpperCAmelCase_				(							self :str		,			lowercase_ :torch.FloatTensor		,			lowercase_ :bool = True				)->				VQEncoderOutput:
     A__							=     self.encoder(lowercase_				)
     A__							=     self.quant_conv(lowercase_				)

     if not return_dict:
         return (h,)

     return VQEncoderOutput(latents=lowercase_				)
 @apply_forward_hook
 def 	UpperCAmelCase_				(							self :Dict		,			lowercase_ :torch.FloatTensor		,			lowercase_ :bool = False		,			lowercase_ :bool = True				)->				Union[DecoderOutput, torch.FloatTensor]:
     # also go through quantization layer
     if not force_not_quantize:
         A__,      A__,      A__							=     self.quantize(lowercase_				)
     else:
         A__							=     h
     A__							=     self.post_quant_conv(lowercase_				)
     A__							=     self.decoder(lowercase_		,			quant if self.config.norm_type == "spatial" else None				)

     if not return_dict:
         return (dec,)

     return DecoderOutput(sample=lowercase_				)



 def 	UpperCAmelCase_				(							self :str		,			lowercase_ :torch.FloatTensor		,			lowercase_ :bool = True				)->				Union[DecoderOutput, torch.FloatTensor]:
     A__							=     sample
     A__							=     self.encode(lowercase_				).latents
     A__							=     self.decode(lowercase_				).sample

     if not return_dict:
         return (dec,)

     return DecoderOutput(sample=lowercase_				)



