

'''simple docstring'''





import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


UpperCamelCase_							=					logging.get_logger(__name__)


UpperCamelCase_							=					{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

UpperCamelCase_							=					{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

UpperCamelCase_							=					{"""facebook/blenderbot_small-90M""": 512}






def 							_lowerCAmelCase (      __magic_name__	:    Optional[Any]	)							->     Optional[Any]:
						lowercase   :       Any								=set()
						lowercase   :       str								=word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)	)
												lowercase   :       Dict								=char

						lowercase   :       List[str]								=set(__magic_name__	)
						return pairs







class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						VOCAB_FILES_NAMES
				lowerCamelCase_							=						PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase_							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase_							=						['input_ids', 'attention_mask']







				def __init__(					self    :		Any		,				UpperCAmelCase__    :		List[str]		,				UpperCAmelCase__    :		int		,				UpperCAmelCase__    :		int="__start__"		,				UpperCAmelCase__    :		Optional[Any]="__end__"		,				UpperCAmelCase__    :		List[Any]="__unk__"		,				UpperCAmelCase__    :		Optional[int]="__null__"		,				**UpperCAmelCase__    :		Union[str, Any]		,				):
										'''simple docstring'''
										super().__init__(unk_token=UpperCAmelCase__		,				bos_token=UpperCAmelCase__		,				eos_token=UpperCAmelCase__		,				pad_token=UpperCAmelCase__		,				**UpperCAmelCase__      )

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







				@property
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										return len(self.encoder      )







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										return dict(self.encoder		,				**self.added_tokens_encoder      )







				def    lowerCamelCase_  (					self    :		int		,				UpperCAmelCase__    :		str      ):
										'''simple docstring'''
										if token in self.cache:
																return self.cache[token]
										lowercase   :       Union[str, Any]								=re.sub('''([.,!?()])'''		,				r''' \1'''		,				UpperCAmelCase__      )
										lowercase   :       List[Any]								=re.sub('''(\')'''		,				r''' \1 '''		,				UpperCAmelCase__      )
										lowercase   :       Optional[int]								=re.sub(r'''\s{2,}'''		,				''' '''		,				UpperCAmelCase__      )
										if "\n" in token:
																lowercase   :       Tuple								=token.replace('''\n'''		,				''' __newln__'''      )

										lowercase   :       Tuple								=token.split(''' '''      )
										lowercase   :       List[Any]								=[]
										for token in tokens:
																if not len(UpperCAmelCase__      ):
																						continue

																lowercase   :       Optional[Any]								=token.lower()
																lowercase   :       List[Any]								=tuple(UpperCAmelCase__      )
																lowercase   :       Any								=tuple(list(word[:-1]      ) + [word[-1] + '''</w>''']      )
																lowercase   :       List[str]								=get_pairs(UpperCAmelCase__      )

																if not pairs:
																						words.append(UpperCAmelCase__      )
																						continue

																while True:
																						lowercase   :       Optional[int]								=min(UpperCAmelCase__		,				key=lambda UpperCAmelCase__      : self.bpe_ranks.get(UpperCAmelCase__		,				float('''inf'''      )      )      )
																						if bigram not in self.bpe_ranks:
																												break
																						lowercase		,  lowercase   :       Dict								=bigram
																						lowercase   :       Union[str, Any]								=[]
																						lowercase   :       Tuple								=0

																						while i < len(UpperCAmelCase__      ):
																												try:
																																		lowercase   :       Any								=word.index(UpperCAmelCase__		,				UpperCAmelCase__      )
																																		new_word.extend(word[i:j]      )
																																		lowercase   :       Any								=j
																												except ValueError:
																																		new_word.extend(word[i:]      )
																																		break

																												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
																						lowercase   :       Tuple								=tuple(UpperCAmelCase__      )
																						lowercase   :       List[str]								=new_word
																						if len(UpperCAmelCase__      ) == 1:
																												break
																						else:
																												lowercase   :       int								=get_pairs(UpperCAmelCase__      )
																lowercase   :       Tuple								='''@@ '''.join(UpperCAmelCase__      )
																lowercase   :       List[Any]								=word[:-4]

																lowercase   :       Optional[int]								=word
																words.append(UpperCAmelCase__      )
										return " ".join(UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Tuple		,				UpperCAmelCase__    :		str      ):
										'''simple docstring'''
										lowercase   :       Union[str, Any]								=[]

										lowercase   :       Union[str, 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    :		Tuple		,				UpperCAmelCase__    :		str      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=token.lower()
										return self.encoder.get(UpperCAmelCase__		,				self.encoder.get(self.unk_token      )      )







				def    lowerCamelCase_  (					self    :		Any		,				UpperCAmelCase__    :		int      ):
										'''simple docstring'''
										return self.decoder.get(UpperCAmelCase__		,				self.unk_token      )







				def    lowerCamelCase_  (					self    :		str		,				UpperCAmelCase__    :		List[str]      ):
										'''simple docstring'''
										lowercase   :       Dict								=''' '''.join(UpperCAmelCase__      ).replace('''@@ '''		,				''''''      ).strip()
										return out_string







				def    lowerCamelCase_  (					self    :		Union[str, Any]		,				UpperCAmelCase__    :		str		,				UpperCAmelCase__    :		Optional[str] = None      ):
										'''simple docstring'''
										if not os.path.isdir(UpperCAmelCase__      ):
																logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
																return
										lowercase   :       Tuple								=os.path.join(
										    UpperCAmelCase__		,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
										lowercase   :       str								=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'''      )

										lowercase   :       Optional[int]								=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!'''      )
																												lowercase   :       List[Any]								=token_index
																						writer.write(''' '''.join(UpperCAmelCase__      ) + '''\n'''      )
																						index += 1

										return vocab_file, merge_file








'''simple docstring'''





import unittest

import numpy as np

from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
							from transformers.models.roberta.modeling_flax_roberta import (
							    FlaxRobertaForCausalLM,
							    FlaxRobertaForMaskedLM,
							    FlaxRobertaForMultipleChoice,
							    FlaxRobertaForQuestionAnswering,
							    FlaxRobertaForSequenceClassification,
							    FlaxRobertaForTokenClassification,
							    FlaxRobertaModel,
							)





class 		__SCREAMING_SNAKE_CASE       ( unittest.TestCase			):







				def __init__(					self    :		Optional[Any]		,				UpperCAmelCase__    :		Tuple		,				UpperCAmelCase__    :		str=13		,				UpperCAmelCase__    :		Optional[Any]=7		,				UpperCAmelCase__    :		Dict=True		,				UpperCAmelCase__    :		int=True		,				UpperCAmelCase__    :		int=True		,				UpperCAmelCase__    :		Dict=True		,				UpperCAmelCase__    :		Dict=99		,				UpperCAmelCase__    :		str=32		,				UpperCAmelCase__    :		Optional[Any]=5		,				UpperCAmelCase__    :		Any=4		,				UpperCAmelCase__    :		List[Any]=37		,				UpperCAmelCase__    :		str="gelu"		,				UpperCAmelCase__    :		Dict=0.1		,				UpperCAmelCase__    :		List[Any]=0.1		,				UpperCAmelCase__    :		Optional[Any]=512		,				UpperCAmelCase__    :		Any=16		,				UpperCAmelCase__    :		str=2		,				UpperCAmelCase__    :		Tuple=0.02		,				UpperCAmelCase__    :		int=4		,				):
										'''simple docstring'''
										lowercase   :       int								=parent
										lowercase   :       List[str]								=batch_size
										lowercase   :       str								=seq_length
										lowercase   :       Optional[Any]								=is_training
										lowercase   :       Union[str, Any]								=use_attention_mask
										lowercase   :       Optional[Any]								=use_token_type_ids
										lowercase   :       Tuple								=use_labels
										lowercase   :       List[str]								=vocab_size
										lowercase   :       List[str]								=hidden_size
										lowercase   :       Tuple								=num_hidden_layers
										lowercase   :       Any								=num_attention_heads
										lowercase   :       List[str]								=intermediate_size
										lowercase   :       Optional[Any]								=hidden_act
										lowercase   :       Dict								=hidden_dropout_prob
										lowercase   :       List[Any]								=attention_probs_dropout_prob
										lowercase   :       Optional[Any]								=max_position_embeddings
										lowercase   :       Tuple								=type_vocab_size
										lowercase   :       Optional[int]								=type_sequence_label_size
										lowercase   :       Optional[Any]								=initializer_range
										lowercase   :       Optional[int]								=num_choices







				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										lowercase   :       Optional[Any]								=ids_tensor([self.batch_size, self.seq_length]		,				self.vocab_size      )

										lowercase   :       Union[str, Any]								=None
										if self.use_attention_mask:
																lowercase   :       List[str]								=random_attention_mask([self.batch_size, self.seq_length]      )

										lowercase   :       Tuple								=None
										if self.use_token_type_ids:
																lowercase   :       str								=ids_tensor([self.batch_size, self.seq_length]		,				self.type_vocab_size      )

										lowercase   :       int								=RobertaConfig(
										    vocab_size=self.vocab_size		,				hidden_size=self.hidden_size		,				num_hidden_layers=self.num_hidden_layers		,				num_attention_heads=self.num_attention_heads		,				intermediate_size=self.intermediate_size		,				hidden_act=self.hidden_act		,				hidden_dropout_prob=self.hidden_dropout_prob		,				attention_probs_dropout_prob=self.attention_probs_dropout_prob		,				max_position_embeddings=self.max_position_embeddings		,				type_vocab_size=self.type_vocab_size		,				is_decoder=UpperCAmelCase__		,				initializer_range=self.initializer_range		,				)

										return config, input_ids, token_type_ids, attention_mask







				def    lowerCamelCase_  (					self    :		Dict      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=self.prepare_config_and_inputs()
										lowercase		,  lowercase		,  lowercase		,  lowercase   :       str								=config_and_inputs
										lowercase   :       Optional[Any]								={'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
										return config, inputs_dict







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										lowercase   :       List[str]								=self.prepare_config_and_inputs()
										lowercase		,  lowercase		,  lowercase		,  lowercase   :       Any								=config_and_inputs

										lowercase   :       List[str]								=True
										lowercase   :       Optional[Any]								=floats_tensor([self.batch_size, self.seq_length, self.hidden_size]      )
										lowercase   :       str								=ids_tensor([self.batch_size, self.seq_length]		,				vocab_size=2      )

										return (
										    config,
										    input_ids,
										    token_type_ids,
										    encoder_hidden_states,
										    encoder_attention_mask,
										)





@require_flax
class 		__SCREAMING_SNAKE_CASE       ( lowercase__	,       unittest.TestCase			):
				lowerCamelCase_							=						True

				lowerCamelCase_							=						(
				    (
				        FlaxRobertaModel,
				        FlaxRobertaForCausalLM,
				        FlaxRobertaForMaskedLM,
				        FlaxRobertaForSequenceClassification,
				        FlaxRobertaForTokenClassification,
				        FlaxRobertaForMultipleChoice,
				        FlaxRobertaForQuestionAnswering,
				    )
				    if is_flax_available()
				    else ()
				)







				def    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       str								=FlaxRobertaModelTester(self      )







				@slow
				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										for model_class_name in self.all_model_classes:
																lowercase   :       Optional[int]								=model_class_name.from_pretrained('''roberta-base'''		,				from_pt=UpperCAmelCase__      )
																lowercase   :       List[Any]								=model(np.ones((1, 1)      )      )
																self.assertIsNotNone(UpperCAmelCase__      )





