


'''simple docstring'''

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


_UpperCAmelCase				: Union[str, Any]							    =				logging.get_logger(__name__)


_UpperCAmelCase				: Union[str, Any]							    =				{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

_UpperCAmelCase				: Dict							    =				{
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
}

_UpperCAmelCase				: Optional[Any]							    =				{
    """allenai/longformer-base-4096""": 4_0_9_6,
    """allenai/longformer-large-4096""": 4_0_9_6,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4_0_9_6,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4_0_9_6,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4_0_9_6,
}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 							__magic_name__(						):
						__lowerCAmelCase							       =				(
						    list(range(ord('''!'''),				ord('''~''') + 1)) + list(range(ord('''¡'''),				ord('''¬''') + 1)) + list(range(ord('''®'''),				ord('''ÿ''') + 1))
						)
						__lowerCAmelCase							       =				bs[:]
						__lowerCAmelCase							       =				0
						for b in range(2**8):
												if b not in bs:
																		bs.append(a_)
																		cs.append(2**8 + n)
																		n += 1
						__lowerCAmelCase							       =				[chr(a_) for n in cs]
						return dict(zip(a_,				a_))

def 							__magic_name__(						lowerCamelCase):
						__lowerCAmelCase							       =				set()
						__lowerCAmelCase							       =				word[0]
						for char in word[1:]:
												pairs.add((prev_char, char))
												__lowerCAmelCase							       =				char
						return pairs




class       a__				( __SCREAMING_SNAKE_CASE      ):







				"""simple docstring"""



				__UpperCamelCase    :		Tuple		=	VOCAB_FILES_NAMES
				__UpperCamelCase    :		int		=	PRETRAINED_VOCAB_FILES_MAP
				__UpperCamelCase    :		Optional[Any]		=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__UpperCamelCase    :		List[str]		=	['input_ids', 'attention_mask']




				def __init__(self       ,			__lowercase       ,			__lowercase       ,			__lowercase="replace"       ,			__lowercase="<s>"       ,			__lowercase="</s>"       ,			__lowercase="</s>"       ,			__lowercase="<s>"       ,			__lowercase="<unk>"       ,			__lowercase="<pad>"       ,			__lowercase="<mask>"       ,			__lowercase=False       ,			**__lowercase       ,			):
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else bos_token
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else eos_token
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else sep_token
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else cls_token
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else unk_token
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else pad_token

										# Mask token behave like a normal word, i.e. include the space before it
										__lowerCAmelCase							       =				AddedToken(__snake_case       ,			lstrip=__snake_case       ,			rstrip=__snake_case		) if isinstance(__snake_case       ,			__snake_case		) else mask_token

										super().__init__(
										    errors=__snake_case       ,			bos_token=__snake_case       ,			eos_token=__snake_case       ,			unk_token=__snake_case       ,			sep_token=__snake_case       ,			cls_token=__snake_case       ,			pad_token=__snake_case       ,			mask_token=__snake_case       ,			add_prefix_space=__snake_case       ,			**__snake_case       ,			)

										with open(__snake_case       ,			encoding='''utf-8'''		) as vocab_handle:
																__lowerCAmelCase							       =				json.load(__snake_case		)
										__lowerCAmelCase							       =				{v: k for k, v in self.encoder.items()}
										__lowerCAmelCase							       =				errors  # how to handle errors in decoding
										__lowerCAmelCase							       =				bytes_to_unicode()
										__lowerCAmelCase							       =				{v: k for k, v in self.byte_encoder.items()}
										with open(__snake_case       ,			encoding='''utf-8'''		) as merges_handle:
																__lowerCAmelCase							       =				merges_handle.read().split('''\n'''		)[1:-1]
										__lowerCAmelCase							       =				[tuple(merge.split()		) for merge in bpe_merges]
										__lowerCAmelCase							       =				dict(zip(__snake_case       ,			range(len(__snake_case		)		)		)		)
										__lowerCAmelCase							       =				{}
										__lowerCAmelCase							       =				add_prefix_space

										# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
										__lowerCAmelCase							       =				re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''		)




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




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




				def 					_snake_case  (self       ,			__lowercase		):
										if token in self.cache:
																return self.cache[token]
										__lowerCAmelCase							       =				tuple(__snake_case		)
										__lowerCAmelCase							       =				get_pairs(__snake_case		)

										if not pairs:
																return token

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




				def 					_snake_case  (self       ,			__lowercase		):
										__lowerCAmelCase							       =				[]
										for token in re.findall(self.pat       ,			__snake_case		):
																__lowerCAmelCase							       =				''''''.join(
																    self.byte_encoder[b] for b in token.encode('''utf-8'''		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__snake_case		).split(''' '''		)		)
										return bpe_tokens




				def 					_snake_case  (self       ,			__lowercase		):
										return self.encoder.get(__snake_case       ,			self.encoder.get(self.unk_token		)		)




				def 					_snake_case  (self       ,			__lowercase		):
										return self.decoder.get(__snake_case		)




				def 					_snake_case  (self       ,			__lowercase		):
										__lowerCAmelCase							       =				''''''.join(__snake_case		)
										__lowerCAmelCase							       =				bytearray([self.byte_decoder[c] for c in text]		).decode('''utf-8'''       ,			errors=self.errors		)
										return text




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase = None		):
										if not os.path.isdir(__snake_case		):
																logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
																return
										__lowerCAmelCase							       =				os.path.join(
										    __snake_case       ,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)
										__lowerCAmelCase							       =				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'''		)

										__lowerCAmelCase							       =				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 __lowercase		: 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(__snake_case		) + '''\n'''		)
																						index += 1

										return vocab_file, merge_file




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase = None		):
										if token_ids_a is None:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										__lowerCAmelCase							       =				[self.cls_token_id]
										__lowerCAmelCase							       =				[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = False		):
										if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=__snake_case       ,			token_ids_a=__snake_case       ,			already_has_special_tokens=__snake_case		)

										if token_ids_a is None:
																return [1] + ([0] * len(__snake_case		)) + [1]
										return [1] + ([0] * len(__snake_case		)) + [1, 1] + ([0] * len(__snake_case		)) + [1]




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase = None		):
										__lowerCAmelCase							       =				[self.sep_token_id]
										__lowerCAmelCase							       =				[self.cls_token_id]

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




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase=False       ,			**__lowercase		):
										__lowerCAmelCase							       =				kwargs.pop('''add_prefix_space'''       ,			self.add_prefix_space		)
										if (is_split_into_words or add_prefix_space) and (len(__snake_case		) > 0 and not text[0].isspace()):
																__lowerCAmelCase							       =				''' ''' + text
										return (text, kwargs)





'''simple docstring'''

import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf, slow


if is_tf_available():
	import tensorflow as tf

if is_keras_nlp_available():
	from transformers.models.gpta import TFGPTaTokenizer


_UpperCAmelCase				: str							    =				["""gpt2"""]
_UpperCAmelCase				: Optional[int]							    =				"""gpt2"""

if is_tf_available():


	class       a__				( tf.Module      ):







					"""simple docstring"""



					def __init__(self       ,			__lowercase		):
											super().__init__()
											__lowerCAmelCase							       =				tokenizer
											__lowerCAmelCase							       =				AutoConfig.from_pretrained(__lowercase		)
											__lowerCAmelCase							       =				TFGPTaLMHeadModel.from_config(__lowercase		)




					@tf.function(input_signature=(tf.TensorSpec((None,)       ,			tf.string       ,			name='''text'''		),)		)
					def 					_snake_case  (self       ,			__lowercase		):
											__lowerCAmelCase							       =				self.tokenizer(__lowercase		)
											__lowerCAmelCase							       =				tokenized['''input_ids'''].to_tensor()

											__lowerCAmelCase							       =				tf.cast(input_ids_dense > 0       ,			tf.intaa		)
											# input_mask = tf.reshape(input_mask, [-1, MAX_SEQ_LEN])

											__lowerCAmelCase							       =				self.model(input_ids=__lowercase       ,			attention_mask=__lowercase		)['''logits''']

											return outputs


@require_tf
@require_keras_nlp
class       a__				( unittest.TestCase      ):







				"""simple docstring"""



				def 					_snake_case  (self		):
										super().setUp()

										__lowerCAmelCase							       =				[GPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in (TOKENIZER_CHECKPOINTS)]
										__lowerCAmelCase							       =				[TFGPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in TOKENIZER_CHECKPOINTS]
										assert len(self.tokenizers		) == len(self.tf_tokenizers		)

										__lowerCAmelCase							       =				[
										    '''This is a straightforward English test sentence.''',
										    '''This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.''',
										    '''Now we\'re going to add some Chinese: 一 二 三 一二三''',
										    '''And some much more rare Chinese: 齉 堃 齉堃''',
										    '''Je vais aussi écrire en français pour tester les accents''',
										    '''Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ''',
										]
										__lowerCAmelCase							       =				list(zip(self.test_sentences       ,			self.test_sentences[::-1]		)		)




				def 					_snake_case  (self		):
										for tokenizer, tf_tokenizer in zip(self.tokenizers       ,			self.tf_tokenizers		):
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tokenizer([test_inputs]       ,			return_tensors='''tf'''		)
																						__lowerCAmelCase							       =				tf_tokenizer([test_inputs]		)

																						for key in python_outputs.keys():
																												# convert them to numpy to avoid messing with ragged tensors
																												__lowerCAmelCase							       =				python_outputs[key].numpy()
																												__lowerCAmelCase							       =				tf_outputs[key].numpy()

																												self.assertTrue(tf.reduce_all(python_outputs_values.shape == tf_outputs_values.shape		)		)
																												self.assertTrue(tf.reduce_all(tf.cast(__lowercase       ,			tf.intaa		) == tf_outputs_values		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.function(__lowercase		)
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tf.constant(__lowercase		)
																						__lowerCAmelCase							       =				compiled_tokenizer(__lowercase		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)

																						for key in eager_outputs.keys():
																												self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				ModelToSave(tokenizer=__lowercase		)
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				model.serving(__lowercase		)  # Build model with some sample inputs
																with TemporaryDirectory() as tempdir:
																						__lowerCAmelCase							       =				Path(__lowercase		) / '''saved.model'''
																						tf.saved_model.save(__lowercase       ,			__lowercase       ,			signatures={'''serving_default''': model.serving}		)
																						__lowerCAmelCase							       =				tf.saved_model.load(__lowercase		)
																__lowerCAmelCase							       =				loaded_model.signatures['''serving_default'''](__lowercase		)['''output_0''']
																# We may see small differences because the loaded model is compiled, so we need an epsilon for the test
																self.assertTrue(tf.reduce_all(out == loaded_output		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)  # Build model with some sample inputs

																__lowerCAmelCase							       =				tf_tokenizer.get_config()
																__lowerCAmelCase							       =				TFGPTaTokenizer.from_config(__lowercase		)
																__lowerCAmelCase							       =				model_from_config(__lowercase		)

																for key in from_config_output.keys():
																						self.assertTrue(tf.reduce_all(from_config_output[key] == out[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																# for the test to run
																__lowerCAmelCase							       =				12_31_23

																for max_length in [3, 5, 10_24]:
																						__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase       ,			max_length=__lowercase		)

																						__lowerCAmelCase							       =				out['''input_ids'''].numpy().shape[1]

																						assert out_length == max_length

