



"""simple docstring"""







import json
import os
from typing import Optional, Tuple

import regex as re

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


lowerCAmelCase_   						=   logging.get_logger(__name__)

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

lowerCAmelCase_   						=   {
    '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'},
}

lowerCAmelCase_   						=   {
    'ctrl': 256,
}

lowerCAmelCase_   						=   {
    'Pregnancy': 168_629,
    'Christianity': 7_675,
    'Explain': 106_423,
    'Fitness': 63_440,
    'Saving': 63_163,
    'Ask': 27_171,
    'Ass': 95_985,
    'Joke': 163_509,
    'Questions': 45_622,
    'Thoughts': 49_605,
    'Retail': 52_342,
    'Feminism': 164_338,
    'Writing': 11_992,
    'Atheism': 192_263,
    'Netflix': 48_616,
    'Computing': 39_639,
    'Opinion': 43_213,
    'Alone': 44_967,
    'Funny': 58_917,
    'Gaming': 40_358,
    'Human': 4_088,
    'India': 1_331,
    'Joker': 77_138,
    'Diet': 36_206,
    'Legal': 11_859,
    'Norman': 4_939,
    'Tip': 72_689,
    'Weight': 52_343,
    'Movies': 46_273,
    'Running': 23_425,
    'Science': 2_090,
    'Horror': 37_793,
    'Confession': 60_572,
    'Finance': 12_250,
    'Politics': 16_360,
    'Scary': 191_985,
    'Support': 12_654,
    'Technologies': 32_516,
    'Teenage': 66_160,
    'Event': 32_769,
    'Learned': 67_460,
    'Notion': 182_770,
    'Wikipedia': 37_583,
    'Books': 6_665,
    'Extract': 76_050,
    'Confessions': 102_701,
    'Conspiracy': 75_932,
    'Links': 63_674,
    'Narcissus': 150_425,
    'Relationship': 54_766,
    'Relationships': 134_796,
    'Reviews': 41_671,
    'News': 4_256,
    'Translation': 26_820,
    'multilingual': 128_406,
}



def      __UpperCAmelCase      (    __lowerCamelCase	)							->      Union[str, Any]:
		lowercase__   :    Dict				=			set()
		lowercase__   :    Optional[int]				=			word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)	)
				lowercase__   :    Dict				=			char

		lowercase__   :    Tuple				=			set(__lowerCamelCase	)
		return pairs





class        __A       (	A_    ):







		'''simple docstring'''





		lowerCAmelCase			:					List[str]   	=				VOCAB_FILES_NAMES
		lowerCAmelCase			:					Union[str, Any]   	=				PRETRAINED_VOCAB_FILES_MAP
		lowerCAmelCase			:					int   	=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCAmelCase			:					Optional[Any]   	=				CONTROL_CODES







		def __init__(	self						:  int			,_snake_case						:  str			,_snake_case						:  Tuple			,_snake_case						:  List[str]="<unk>"			,**_snake_case						:  List[str]						)					->		Tuple:






				"""simple docstring"""



				super().__init__(unk_token=_snake_case			,**_snake_case						)

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







		@property
		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		List[Any]:






				"""simple docstring"""



				return len(self.encoder						)







		def 					UpperCAmelCase    (	self						:  Optional[int]						)					->		Union[str, Any]:






				"""simple docstring"""



				return dict(self.encoder			,**self.added_tokens_encoder						)







		def 					UpperCAmelCase    (	self						:  Any			,_snake_case						:  Union[str, Any]						)					->		Tuple:






				"""simple docstring"""



				if token in self.cache:
						return self.cache[token]
				lowercase__   :    str				=			tuple(_snake_case						)
				lowercase__   :    Dict				=			tuple(list(word[:-1]						) + [word[-1] + '''</w>''']						)
				lowercase__   :    Any				=			get_pairs(_snake_case						)

				if not pairs:
						return token

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

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







		def 					UpperCAmelCase    (	self						:  Optional[Any]			,_snake_case						:  Optional[int]						)					->		Optional[int]:






				"""simple docstring"""



				lowercase__   :    List[str]				=			[]

				lowercase__   :    int				=			re.findall(r'''\S+\n?'''			,_snake_case						)

				for token in words:
						split_tokens.extend(list(self.bpe(_snake_case						).split(''' '''						)						)						)
				return split_tokens







		def 					UpperCAmelCase    (	self						:  List[Any]			,_snake_case						:  List[Any]						)					->		Tuple:






				"""simple docstring"""



				return self.encoder.get(_snake_case			,self.encoder.get(self.unk_token						)						)







		def 					UpperCAmelCase    (	self						:  Optional[int]			,_snake_case						:  str						)					->		Optional[Any]:






				"""simple docstring"""



				return self.decoder.get(_snake_case			,self.unk_token						)







		def 					UpperCAmelCase    (	self						:  List[str]			,_snake_case						:  str						)					->		Any:






				"""simple docstring"""



				lowercase__   :    List[str]				=			''' '''.join(_snake_case						).replace('''@@ '''			,''''''						).strip()
				return out_string







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






				"""simple docstring"""



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

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

				lowercase__   :    Optional[int]				=			0
				with open(_snake_case			,'''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 _snake_case						: 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!'''						)
										lowercase__   :    List[Any]				=			token_index
								writer.write(''' '''.join(_snake_case						) + '''\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

import torch

from transformers import YosoConfig, YosoForMaskedLM



def      __UpperCAmelCase      (    __lowerCamelCase	)							->      Optional[int]:
		if "model" in orig_key:
				lowercase__   :    Tuple				=			orig_key.replace('''model.'''						,     ''''''	)
		if "norm1" in orig_key:
				lowercase__   :    List[str]				=			orig_key.replace('''norm1'''						,     '''attention.output.LayerNorm'''	)
		if "norm2" in orig_key:
				lowercase__   :    List[str]				=			orig_key.replace('''norm2'''						,     '''output.LayerNorm'''	)
		if "norm" in orig_key:
				lowercase__   :    List[str]				=			orig_key.replace('''norm'''						,     '''LayerNorm'''	)
		if "transformer" in orig_key:
				lowercase__   :    Union[str, Any]				=			orig_key.split('''.'''	)[0].split('''_'''	)[-1]
				lowercase__   :    List[str]				=			orig_key.replace(f"""transformer_{layer_num}"""						,     f"""encoder.layer.{layer_num}"""	)
		if "mha.attn" in orig_key:
				lowercase__   :    Union[str, Any]				=			orig_key.replace('''mha.attn'''						,     '''attention.self'''	)
		if "mha" in orig_key:
				lowercase__   :    str				=			orig_key.replace('''mha'''						,     '''attention'''	)
		if "W_q" in orig_key:
				lowercase__   :    Any				=			orig_key.replace('''W_q'''						,     '''self.query'''	)
		if "W_k" in orig_key:
				lowercase__   :    List[Any]				=			orig_key.replace('''W_k'''						,     '''self.key'''	)
		if "W_v" in orig_key:
				lowercase__   :    Any				=			orig_key.replace('''W_v'''						,     '''self.value'''	)
		if "ff1" in orig_key:
				lowercase__   :    Optional[int]				=			orig_key.replace('''ff1'''						,     '''intermediate.dense'''	)
		if "ff2" in orig_key:
				lowercase__   :    Optional[Any]				=			orig_key.replace('''ff2'''						,     '''output.dense'''	)
		if "ff" in orig_key:
				lowercase__   :    List[str]				=			orig_key.replace('''ff'''						,     '''output.dense'''	)
		if "mlm_class" in orig_key:
				lowercase__   :    int				=			orig_key.replace('''mlm.mlm_class'''						,     '''cls.predictions.decoder'''	)
		if "mlm" in orig_key:
				lowercase__   :    Optional[Any]				=			orig_key.replace('''mlm'''						,     '''cls.predictions.transform'''	)
		if "cls" not in orig_key:
				lowercase__   :    Optional[Any]				=			'''yoso.''' + orig_key

		return orig_key



def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase	)							->      Optional[int]:
		for key in orig_state_dict.copy().keys():
				lowercase__   :    Optional[Any]				=			orig_state_dict.pop(__lowerCamelCase	)

				if ("pooler" in key) or ("sen_class" in key):
						continue
				else:
						lowercase__   :    Tuple				=			val

		lowercase__   :    Union[str, Any]				=			orig_state_dict['''cls.predictions.decoder.bias''']
		lowercase__   :    List[str]				=			torch.arange(__lowerCamelCase	).expand((1, -1)	) + 2

		return orig_state_dict



def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase	)							->      Optional[Any]:
		lowercase__   :    Tuple				=			torch.load(__lowerCamelCase						,     map_location='''cpu'''	)['''model_state_dict''']
		lowercase__   :    List[Any]				=			YosoConfig.from_json_file(__lowerCamelCase	)
		lowercase__   :    List[Any]				=			YosoForMaskedLM(__lowerCamelCase	)

		lowercase__   :    Optional[Any]				=			convert_checkpoint_helper(config.max_position_embeddings						,     __lowerCamelCase	)

		print(model.load_state_dict(__lowerCamelCase	)	)
		model.eval()
		model.save_pretrained(__lowerCamelCase	)

		print(f"""Checkpoint successfuly converted. Model saved at {pytorch_dump_path}"""	)


if __name__ == "__main__":
							lowerCAmelCase_   						=   argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    '--pytorch_model_path', default=None, type=str, required=True, help='Path to YOSO pytorch checkpoint.'
							)
							parser.add_argument(
							    '--config_file',
							    default=None,
							    type=str,
							    required=True,
							    help='The json file for YOSO model config.',
							)
							parser.add_argument(
							    '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
							)
							lowerCAmelCase_   						=   parser.parse_args()
							convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)
