"""simple docstring"""





import json
import os
from typing import Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A  =				logging.get_logger(__name__)

__A  =				{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

__A  =				{
    '''vocab_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json'''},
    '''merges_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt'''},
}

__A  =				{
    '''ctrl''': 256,
}

__A  =				{
    '''Pregnancy''': 168629,
    '''Christianity''': 7675,
    '''Explain''': 106423,
    '''Fitness''': 63440,
    '''Saving''': 63163,
    '''Ask''': 27171,
    '''Ass''': 95985,
    '''Joke''': 163509,
    '''Questions''': 45622,
    '''Thoughts''': 49605,
    '''Retail''': 52342,
    '''Feminism''': 164338,
    '''Writing''': 11992,
    '''Atheism''': 192263,
    '''Netflix''': 48616,
    '''Computing''': 39639,
    '''Opinion''': 43213,
    '''Alone''': 44967,
    '''Funny''': 58917,
    '''Gaming''': 40358,
    '''Human''': 4088,
    '''India''': 1331,
    '''Joker''': 77138,
    '''Diet''': 36206,
    '''Legal''': 11859,
    '''Norman''': 4939,
    '''Tip''': 72689,
    '''Weight''': 52343,
    '''Movies''': 46273,
    '''Running''': 23425,
    '''Science''': 2090,
    '''Horror''': 37793,
    '''Confession''': 60572,
    '''Finance''': 12250,
    '''Politics''': 16360,
    '''Scary''': 191985,
    '''Support''': 12654,
    '''Technologies''': 32516,
    '''Teenage''': 66160,
    '''Event''': 32769,
    '''Learned''': 67460,
    '''Notion''': 182770,
    '''Wikipedia''': 37583,
    '''Books''': 6665,
    '''Extract''': 76050,
    '''Confessions''': 102701,
    '''Conspiracy''': 75932,
    '''Links''': 63674,
    '''Narcissus''': 150425,
    '''Relationship''': 54766,
    '''Relationships''': 134796,
    '''Reviews''': 41671,
    '''News''': 4256,
    '''Translation''': 26820,
    '''multilingual''': 128406,
}


def    lowercase_   (   _lowerCamelCase:	Optional[int]      ) ->      Optional[Any]:



       '''simple docstring'''

       __lowerCamelCase					:		Tuple		   =     set()
       __lowerCamelCase					:		Tuple		   =     word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)      )
              __lowerCamelCase					:		Any		   =     char

       __lowerCamelCase					:		Union[str, Any]		   =     set(__A      )
       return pairs







class  _snake_case     (					__A		):
      snake_case__			  =			VOCAB_FILES_NAMES
      snake_case__			  =			PRETRAINED_VOCAB_FILES_MAP
      snake_case__			  =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      snake_case__			  =			CONTROL_CODES






      def __init__(       self      :			Dict							,					UpperCAmelCase      :			Tuple							,					UpperCAmelCase      :			int							,					UpperCAmelCase      :			Dict="<unk>"							,					**UpperCAmelCase      :			Tuple    ):
             super().__init__(unk_token=UpperCAmelCase							,					**UpperCAmelCase    )

             with open(UpperCAmelCase							,					encoding="utf-8"    ) as vocab_handle:
                    __lowerCamelCase					:		List[Any]		   =     json.load(UpperCAmelCase    )
             __lowerCamelCase					:		Union[str, Any]		   =     {v: k for k, v in self.encoder.items()}
             with open(UpperCAmelCase							,					encoding="utf-8"    ) as merges_handle:
                    __lowerCamelCase					:		Tuple		   =     merges_handle.read().split("\n"    )[1:-1]
             __lowerCamelCase					:		List[str]		   =     [tuple(merge.split()    ) for merge in merges]
             __lowerCamelCase					:		Tuple		   =     dict(zip(UpperCAmelCase							,					range(len(UpperCAmelCase    )    )    )    )
             __lowerCamelCase					:		Dict		   =     {}






      @property
      def       lowerCamelCase__     (       self      :			Optional[Any]    ):
             return len(self.encoder    )






      def       lowerCamelCase__     (       self      :			Optional[int]    ):
             return dict(self.encoder							,					**self.added_tokens_encoder    )






      def       lowerCamelCase__     (       self      :			str							,					UpperCAmelCase      :			Optional[int]    ):

             if token in self.cache:
                    return self.cache[token]
             __lowerCamelCase					:		Dict		   =     tuple(UpperCAmelCase    )
             __lowerCamelCase					:		Any		   =     tuple(list(word[:-1]    ) + [word[-1] + "</w>"]    )
             __lowerCamelCase					:		Dict		   =     get_pairs(UpperCAmelCase    )

             if not pairs:
                    return token

             while True:
                    __lowerCamelCase					:		List[Any]		   =     min(UpperCAmelCase							,					key=lambda UpperCAmelCase    : self.bpe_ranks.get(UpperCAmelCase							,					float("inf"    )    )    )
                    if bigram not in self.bpe_ranks:
                           break
                    __lowerCamelCase					:		Tuple		   =     bigram
                    __lowerCamelCase					:		Union[str, Any]		   =     []
                    __lowerCamelCase					:		Dict		   =     0
                    while i < len(UpperCAmelCase    ):
                           try:
                                  __lowerCamelCase					:		List[Any]		   =     word.index(UpperCAmelCase							,					UpperCAmelCase    )
                           except ValueError:
                                  new_word.extend(word[i:]    )
                                  break
                           else:
                                  new_word.extend(word[i:j]    )
                                  __lowerCamelCase					:		int		   =     j

                           if word[i] == first and i < len(UpperCAmelCase    ) - 1 and word[i + 1] == second:
                                  new_word.append(first + second    )
                                  i += 2
                           else:
                                  new_word.append(word[i]    )
                                  i += 1
                    __lowerCamelCase					:		int		   =     tuple(UpperCAmelCase    )
                    __lowerCamelCase					:		Optional[Any]		   =     new_word
                    if len(UpperCAmelCase    ) == 1:
                           break
                    else:
                           __lowerCamelCase					:		int		   =     get_pairs(UpperCAmelCase    )
             __lowerCamelCase					:		List[str]		   =     '''@@ '''.join(UpperCAmelCase    )
             __lowerCamelCase					:		Optional[Any]		   =     word[:-4]
             __lowerCamelCase					:		Union[str, Any]		   =     word
             return word






      def       lowerCamelCase__     (       self      :			int							,					UpperCAmelCase      :			List[str]    ):
             __lowerCamelCase					:		int		   =     []

             __lowerCamelCase					:		Any		   =     re.findall(r"\S+\n?"							,					UpperCAmelCase    )

             for token in words:
                    split_tokens.extend(list(self.bpe(UpperCAmelCase    ).split(" "    )    )    )
             return split_tokens






      def       lowerCamelCase__     (       self      :			int							,					UpperCAmelCase      :			str    ):
             return self.encoder.get(UpperCAmelCase							,					self.encoder.get(self.unk_token    )    )






      def       lowerCamelCase__     (       self      :			Tuple							,					UpperCAmelCase      :			List[str]    ):
             return self.decoder.get(UpperCAmelCase							,					self.unk_token    )






      def       lowerCamelCase__     (       self      :			Optional[Any]							,					UpperCAmelCase      :			List[str]    ):
             __lowerCamelCase					:		Optional[Any]		   =     ''' '''.join(UpperCAmelCase    ).replace("@@ "							,					""    ).strip()
             return out_string







      def       lowerCamelCase__     (       self      :			List[Any]							,					UpperCAmelCase      :			str							,					UpperCAmelCase      :			Optional[str] = None    ):

             if not os.path.isdir(UpperCAmelCase    ):
                    logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
                    return
             __lowerCamelCase					:		Union[str, Any]		   =     os.path.join(
                 UpperCAmelCase							,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]    )
             __lowerCamelCase					:		Union[str, Any]		   =     os.path.join(
                 UpperCAmelCase							,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]    )

             with open(UpperCAmelCase							,					"w"							,					encoding="utf-8"    ) as f:
                    f.write(json.dumps(self.encoder							,					indent=2							,					sort_keys=UpperCAmelCase							,					ensure_ascii=UpperCAmelCase    ) + "\n"    )

             __lowerCamelCase					:		Dict		   =     0
             with open(UpperCAmelCase							,					"w"							,					encoding="utf-8"    ) as writer:
                    writer.write("#version: 0.2\n"    )
                    for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,					key=lambda UpperCAmelCase    : kv[1]    ):
                           if index != token_index:
                                  logger.warning(
                                      F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                                      " Please check that the tokenizer is not corrupted!"    )
                                  __lowerCamelCase					:		List[str]		   =     token_index
                           writer.write(" ".join(UpperCAmelCase    ) + "\n"    )
                           index += 1

             return vocab_file, merge_file

      # def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
      #     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
      #     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
      #     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
      #     return ''.join(tokens_generated_so_far)
"""simple docstring"""





import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()


def    lowercase_   (   _lowerCamelCase:	Dict						,   _lowerCamelCase:	str						,   _lowerCamelCase:	Dict      ) ->      List[str]:



							'''simple docstring'''

							__lowerCamelCase					:		List[Any]		   =     TaConfig.from_json_file(_lowerCamelCase      )
							print(F"""Building PyTorch model from configuration: {config}"""      )
							__lowerCamelCase					:		Optional[int]		   =     TaForConditionalGeneration(_lowerCamelCase      )

							# Load weights from tf checkpoint
							load_tf_weights_in_ta(_lowerCamelCase						,   _lowerCamelCase						,   _lowerCamelCase      )

							# Save pytorch-model
							print(F"""Save PyTorch model to {pytorch_dump_path}"""      )
							model.save_pretrained(_lowerCamelCase      )


if __name__ == "__main__":
				__A  =				argparse.ArgumentParser()
				# Required parameters
				parser.add_argument(
				    '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
				)
				parser.add_argument(
				    '''--config_file''',
				    default=None,
				    type=str,
				    required=True,
				    help=(
				        '''The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture.'''
				    ),
				)
				parser.add_argument(
				    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
				)
				__A  =				parser.parse_args()
				convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)