






"""simple docstring"""






import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class       snake_case_       (    _lowerCamelCase    ,							unittest.TestCase       ):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:							Optional[int]   			=					LongformerTokenizer
	SCREAMING_SNAKE_CASE_:							Tuple   			=					True
	SCREAMING_SNAKE_CASE_:							Tuple   			=					LongformerTokenizerFast
	SCREAMING_SNAKE_CASE_:							Any   			=					True


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					A__							 =       [
					    'l',
					    'o',
					    'w',
					    'e',
					    'r',
					    's',
					    't',
					    'i',
					    'd',
					    'n',
					    '\u0120',
					    '\u0120l',
					    '\u0120n',
					    '\u0120lo',
					    '\u0120low',
					    'er',
					    '\u0120lowest',
					    '\u0120newer',
					    '\u0120wider',
					    '<unk>',
					]
					A__							 =       dict(zip(__a  ,					range(len(__a						)						)						)						)
					A__							 =       ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
					A__							 =       {'unk_token': '<unk>'}

					A__							 =       os.path.join(self.tmpdirname  ,					VOCAB_FILES_NAMES['vocab_file']						)
					A__							 =       os.path.join(self.tmpdirname  ,					VOCAB_FILES_NAMES['merges_file']						)
					with open(self.vocab_file  ,					'w'  ,					encoding='utf-8'						) as fp:
									fp.write(json.dumps(__a						) + '\n'						)
					with open(self.merges_file  ,					'w'  ,					encoding='utf-8'						) as fp:
									fp.write('\n'.join(__a						)						)


	def       _UpperCAmelCase						(      self  ,					**__a						):


					"""simple docstring"""

					kwargs.update(self.special_tokens_map						)
					return self.tokenizer_class.from_pretrained(self.tmpdirname  ,					**__a						)


	def       _UpperCAmelCase						(      self  ,					**__a						):


					"""simple docstring"""

					kwargs.update(self.special_tokens_map						)
					return self.rust_tokenizer_class.from_pretrained(self.tmpdirname  ,					**__a						)


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       'lower newer'
					A__							 =       'lower newer'
					return input_text, output_text


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer_class(self.vocab_file  ,					self.merges_file  ,					**self.special_tokens_map						)
					A__							 =       'lower newer'
					A__							 =       ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
					A__							 =       tokenizer.tokenize(__a						)  # , add_prefix_space=True)
					self.assertListEqual(__a  ,					__a						)

					A__							 =       tokens + [tokenizer.unk_token]
					A__							 =       [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(__a						)  ,					__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.get_tokenizer()

					self.assertListEqual(tokenizer.encode('Hello world!'  ,					add_special_tokens=__a						)  ,					[0, 3_1414, 232, 328, 2]						)
					self.assertListEqual(
					    tokenizer.encode('Hello world! cécé herlolip 418'  ,					add_special_tokens=__a						)  ,					[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]  ,					)


	@slow
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.tokenizer_class.from_pretrained('allenai/longformer-base-4096'						)

					A__							 =       tokenizer.encode('sequence builders'  ,					add_special_tokens=__a						)
					A__							 =       tokenizer.encode('multi-sequence build'  ,					add_special_tokens=__a						)

					A__							 =       tokenizer.encode(
					    'sequence builders'  ,					add_special_tokens=__a  ,					add_prefix_space=__a						)
					A__							 =       tokenizer.encode(
					    'sequence builders'  ,					'multi-sequence build'  ,					add_special_tokens=__a  ,					add_prefix_space=__a						)

					A__							 =       tokenizer.build_inputs_with_special_tokens(__a						)
					A__							 =       tokenizer.build_inputs_with_special_tokens(__a  ,					__a						)

					assert encoded_sentence == encoded_text_from_decode
					assert encoded_pair == encoded_pair_from_decode


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       self.get_tokenizer()

					A__							 =       'Encode this sequence.'
					A__							 =       tokenizer.byte_encoder[' '.encode('utf-8'						)[0]]

					# Testing encoder arguments
					A__							 =       tokenizer.encode(__a  ,					add_special_tokens=__a  ,					add_prefix_space=__a						)
					A__							 =       tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
					self.assertNotEqual(__a  ,					__a						)

					A__							 =       tokenizer.encode(__a  ,					add_special_tokens=__a  ,					add_prefix_space=__a						)
					A__							 =       tokenizer.convert_ids_to_tokens(encoded[0]						)[0]
					self.assertEqual(__a  ,					__a						)

					tokenizer.add_special_tokens({'bos_token': '<s>'}						)
					A__							 =       tokenizer.encode(__a  ,					add_special_tokens=__a						)
					A__							 =       tokenizer.convert_ids_to_tokens(encoded[1]						)[0]
					self.assertNotEqual(__a  ,					__a						)

					# Testing spaces after special tokens
					A__							 =       '<mask>'
					tokenizer.add_special_tokens(
					    {'mask_token': AddedToken(__a  ,					lstrip=__a  ,					rstrip=__a						)}						)  # mask token has a left space
					A__							 =       tokenizer.convert_tokens_to_ids(__a						)

					A__							 =       'Encode <mask> sequence'
					A__							 =       'Encode <mask>sequence'

					A__							 =       tokenizer.encode(__a						)
					A__							 =       encoded.index(__a						)
					A__							 =       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
					self.assertEqual(__a  ,					__a						)

					A__							 =       tokenizer.encode(__a						)
					A__							 =       encoded.index(__a						)
					A__							 =       tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]						)[0]
					self.assertNotEqual(__a  ,					__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					pass


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
													A__							 =       self.rust_tokenizer_class.from_pretrained(__a  ,					**__a						)
													A__							 =       self.tokenizer_class.from_pretrained(__a  ,					**__a						)
													A__							 =       'A, <mask> AllenNLP sentence.'
													A__							 =       tokenizer_r.encode_plus(__a  ,					add_special_tokens=__a  ,					return_token_type_ids=__a						)
													A__							 =       tokenizer_p.encode_plus(__a  ,					add_special_tokens=__a  ,					return_token_type_ids=__a						)

													# token_type_ids should put 0 everywhere
													self.assertEqual(sum(tokens_r['token_type_ids']						)  ,					sum(tokens_p['token_type_ids']						)						)

													# attention_mask should put 1 everywhere, so sum over length should be 1
													self.assertEqual(
													    sum(tokens_r['attention_mask']						) / len(tokens_r['attention_mask']						)  ,					sum(tokens_p['attention_mask']						) / len(tokens_p['attention_mask']						)  ,					)

													A__							 =       tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']						)
													A__							 =       tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']						)

													# Rust correctly handles the space before the mask while python doesnt
													self.assertSequenceEqual(tokens_p['input_ids']  ,					[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]						)
													self.assertSequenceEqual(tokens_r['input_ids']  ,					[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]						)

													self.assertSequenceEqual(
													    __a  ,					['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']						)
													self.assertSequenceEqual(
													    __a  ,					['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					for trim_offsets, add_prefix_space in itertools.product([True, False]  ,					repeat=2						):
									A__							 =       self.rust_tokenizer_class.from_pretrained(
									    self.tmpdirname  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)

									A__							 =       json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()						)
									A__							 =       json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()						)

									self.assertEqual(pre_tokenizer_state['add_prefix_space']  ,					__a						)

									self.assertEqual(post_processor_state['add_prefix_space']  ,					__a						)
									self.assertEqual(post_processor_state['trim_offsets']  ,					__a						)






	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
													A__							 =       'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
													A__							 =       f'''{text_of_1_token} {text_of_1_token}'''

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(len(__a						) + 1, len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(len(__a						) + 1, len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(len(__a						), len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(len(__a						), len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       f''' {text}'''

													# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
													#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
													# )
													# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
													# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
													# self.assertEqual(
													#     encoding.offset_mapping[1],
													#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
													# )

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(1, 1 + len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(1 + len(__a						) + 1, 1 + len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, 1 + len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(1 + len(__a						), 1 + len(__a						) + 1 + len(__a						))  ,					)

													A__							 =       self.rust_tokenizer_class.from_pretrained(
													    __a  ,					use_fast=__a  ,					add_prefix_space=__a  ,					trim_offsets=__a						)
													A__							 =       tokenizer_r(__a  ,					return_offsets_mapping=__a  ,					add_special_tokens=__a						)
													self.assertEqual(encoding.offset_mapping[0]  ,					(0, 1 + len(__a						))						)
													self.assertEqual(
													    encoding.offset_mapping[1]  ,					(1 + len(__a						), 1 + len(__a						) + 1 + len(__a						))  ,					)










"""simple docstring"""






from math import ceil



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):
				A__							 =       list(range(0       ,lowerCAmelCase__				)				)

				A__							 =       [item for sublist in list(device_map.values()				) for item in sublist]

				# Duplicate check
				A__							 =       []
				for i in device_map_blocks:
								if device_map_blocks.count(lowerCAmelCase__				) > 1 and i not in duplicate_blocks:
												duplicate_blocks.append(lowerCAmelCase__				)
    # Missing blocks
				A__							 =       [i for i in blocks if i not in device_map_blocks]
				A__							 =       [i for i in device_map_blocks if i not in blocks]

				if len(lowerCAmelCase__				) != 0:
								raise ValueError(
								    'Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device.'
								    ' These attention blocks were specified more than once: ' + str(lowerCAmelCase__				)				)
				if len(lowerCAmelCase__				) != 0:
								raise ValueError(
								    'There are attention blocks for this model that are not specified in the device_map. Add these attention '
								    'blocks to a device on the device_map: ' + str(lowerCAmelCase__				)				)
				if len(lowerCAmelCase__				) != 0:
								raise ValueError(
								    'The device_map contains more attention blocks than this model has. Remove these from the device_map:'
								    + str(lowerCAmelCase__				)				)







def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):
				A__							 =       list(range(lowerCAmelCase__				)				)
				A__							 =       int(ceil(n_layers / len(lowerCAmelCase__				)				)				)
				A__							 =       [layers[i : i + n_blocks] for i in range(0       ,lowerCAmelCase__       ,lowerCAmelCase__				)]

				return dict(zip(lowerCAmelCase__       ,lowerCAmelCase__				)				)


