
"""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""": 16_8629,
    """Christianity""": 7675,
    """Explain""": 10_6423,
    """Fitness""": 6_3440,
    """Saving""": 6_3163,
    """Ask""": 2_7171,
    """Ass""": 9_5985,
    """Joke""": 16_3509,
    """Questions""": 4_5622,
    """Thoughts""": 4_9605,
    """Retail""": 5_2342,
    """Feminism""": 16_4338,
    """Writing""": 1_1992,
    """Atheism""": 19_2263,
    """Netflix""": 4_8616,
    """Computing""": 3_9639,
    """Opinion""": 4_3213,
    """Alone""": 4_4967,
    """Funny""": 5_8917,
    """Gaming""": 4_0358,
    """Human""": 4088,
    """India""": 1331,
    """Joker""": 7_7138,
    """Diet""": 3_6206,
    """Legal""": 1_1859,
    """Norman""": 4939,
    """Tip""": 7_2689,
    """Weight""": 5_2343,
    """Movies""": 4_6273,
    """Running""": 2_3425,
    """Science""": 2090,
    """Horror""": 3_7793,
    """Confession""": 6_0572,
    """Finance""": 1_2250,
    """Politics""": 1_6360,
    """Scary""": 19_1985,
    """Support""": 1_2654,
    """Technologies""": 3_2516,
    """Teenage""": 6_6160,
    """Event""": 3_2769,
    """Learned""": 6_7460,
    """Notion""": 18_2770,
    """Wikipedia""": 3_7583,
    """Books""": 6665,
    """Extract""": 7_6050,
    """Confessions""": 10_2701,
    """Conspiracy""": 7_5932,
    """Links""": 6_3674,
    """Narcissus""": 15_0425,
    """Relationship""": 5_4766,
    """Relationships""": 13_4796,
    """Reviews""": 4_1671,
    """News""": 4256,
    """Translation""": 2_6820,
    """multilingual""": 12_8406,
}






def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  set()
			lowerCamelCase_					=  word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)						)
						lowerCamelCase_					=  char

			lowerCamelCase_					=  set(lowerCAmelCase__						)
			return pairs




class  __lowerCamelCase  ( lowerCAmelCase			):
				a__:      Optional[Any]          =    VOCAB_FILES_NAMES
				a__:      List[Any]          =    PRETRAINED_VOCAB_FILES_MAP
				a__:      Union[str, Any]          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				a__:      str          =    CONTROL_CODES




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

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




				@property
				def        UpperCAmelCase__						(				self   ):
							return len(self.encoder   )




				def        UpperCAmelCase__						(				self   ):
							return dict(self.encoder							,						**self.added_tokens_encoder   )




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							if token in self.cache:
										return self.cache[token]
							lowerCamelCase_					=  tuple(UpperCAmelCase   )
							lowerCamelCase_					=  tuple(list(word[:-1]   ) + [word[-1] + '''</w>''']   )
							lowerCamelCase_					=  get_pairs(UpperCAmelCase   )

							if not pairs:
										return token

							while True:
										lowerCamelCase_					=  min(UpperCAmelCase							,						key=lambda UpperCAmelCase   : self.bpe_ranks.get(UpperCAmelCase							,						float('''inf'''   )   )   )
										if bigram not in self.bpe_ranks:
													break
										lowerCamelCase_		, lowerCamelCase_					=  bigram
										lowerCamelCase_					=  []
										lowerCamelCase_					=  0
										while i < len(UpperCAmelCase   ):
													try:
																lowerCamelCase_					=  word.index(UpperCAmelCase							,						UpperCAmelCase   )
													except ValueError:
																new_word.extend(word[i:]   )
																break
													else:
																new_word.extend(word[i:j]   )
																lowerCamelCase_					=  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_					=  tuple(UpperCAmelCase   )
										lowerCamelCase_					=  new_word
										if len(UpperCAmelCase   ) == 1:
													break
										else:
													lowerCamelCase_					=  get_pairs(UpperCAmelCase   )
							lowerCamelCase_					=  '''@@ '''.join(UpperCAmelCase   )
							lowerCamelCase_					=  word[:-4]
							lowerCamelCase_					=  word
							return word




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							lowerCamelCase_					=  []

							lowerCamelCase_					=  re.findall(r'''\S+\n?'''							,						UpperCAmelCase   )

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




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							return self.encoder.get(UpperCAmelCase							,						self.encoder.get(self.unk_token   )   )




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							return self.decoder.get(UpperCAmelCase							,						self.unk_token   )




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase   ):
							lowerCamelCase_					=  ''' '''.join(UpperCAmelCase   ).replace('''@@ '''							,						''''''   ).strip()
							return out_string





				def        UpperCAmelCase__						(				self							,						UpperCAmelCase							,						UpperCAmelCase = None   ):
							if not os.path.isdir(UpperCAmelCase   ):
										logger.error(f"Vocabulary path ({save_directory}) should be a directory"   )
										return
							lowerCamelCase_					=  os.path.join(
							    UpperCAmelCase							,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )
							lowerCamelCase_					=  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_					=  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_					=  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 timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD






def  lowercase						(	lowerCAmelCase__						):
			def wrapper(*lowerCAmelCase__	,**lowerCAmelCase__						):
						lowerCamelCase_					=  timeit.default_timer()
						lowerCamelCase_					=  func(*lowerCAmelCase__	,**lowerCAmelCase__						)
						lowerCamelCase_					=  timeit.default_timer() - starttime
						return delta

			lowerCamelCase_					=  func.__name__

			return wrapper






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__=100	,lowerCAmelCase__=None						):
			lowerCamelCase_					=  []
			lowerCamelCase_					=  seq_shapes or {}
			for i in range(lowerCAmelCase__						):
						lowerCamelCase_					=  {}
						for col_id, (k, v) in enumerate(features.items()						):
									if isinstance(lowerCAmelCase__	,_ArrayXD						):
												lowerCamelCase_					=  np.random.rand(*v.shape						).astype(v.dtype						)
									elif isinstance(lowerCAmelCase__	,datasets.Value						):
												if v.dtype == "string":
															lowerCamelCase_					=  '''The small grey turtle was surprisingly fast when challenged.'''
												else:
															lowerCamelCase_					=  np.random.randint(10	,size=1						).astype(v.dtype						).item()
									elif isinstance(lowerCAmelCase__	,datasets.Sequence						):
												while isinstance(lowerCAmelCase__	,datasets.Sequence						):
															lowerCamelCase_					=  v.feature
												lowerCamelCase_					=  seq_shapes[k]
												lowerCamelCase_					=  np.random.rand(*lowerCAmelCase__						).astype(v.dtype						)
									lowerCamelCase_					=  data

						dummy_data.append((i, example)						)

			return dummy_data






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__=100	,lowerCAmelCase__=None						):
			lowerCamelCase_					=  generate_examples(lowerCAmelCase__	,num_examples=lowerCAmelCase__	,seq_shapes=lowerCAmelCase__						)

			with ArrowWriter(features=lowerCAmelCase__	,path=lowerCAmelCase__						) as writer:
						for key, record in dummy_data:
									lowerCamelCase_					=  features.encode_example(lowerCAmelCase__						)
									writer.write(lowerCAmelCase__						)

						lowerCamelCase_		, lowerCamelCase_					=  writer.finalize()

			if not num_final_examples == num_examples:
						raise ValueError(
						    f"Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."						)

			lowerCamelCase_					=  datasets.Dataset.from_file(filename=lowerCAmelCase__	,info=datasets.DatasetInfo(features=lowerCAmelCase__						)						)

			return dataset



