
'''simple docstring'''
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 			SCREAMING_SNAKE_CASE__      (     snake_case_							,       unittest.TestCase):
				lowerCAmelCase_     			=							RobertaTokenizer
				lowerCAmelCase_     			=							RobertaTokenizerFast
				lowerCAmelCase_     			=							True
				lowerCAmelCase_     			=							{"""cls_token""": """<s>"""}







				def 						UpperCAmelCase_    (       self     )->		Any:







											'''simple docstring'''






											super().setUp()

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

											UpperCamelCase   			=     os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES['vocab_file']     )
											UpperCamelCase   			=     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_     )->		str:







											'''simple docstring'''






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







				def 						UpperCAmelCase_    (       self						,				**A_     )->		Union[str, Any]:







											'''simple docstring'''






											kwargs.update(self.special_tokens_map     )
											return RobertaTokenizerFast.from_pretrained(self.tmpdirname						,				**A_     )







				def 						UpperCAmelCase_    (       self						,				A_     )->		Union[str, Any]:







											'''simple docstring'''






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







				def 						UpperCAmelCase_    (       self     )->		Union[str, Any]:







											'''simple docstring'''






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

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







				def 						UpperCAmelCase_    (       self     )->		List[str]:







											'''simple docstring'''






											UpperCamelCase   			=     self.get_tokenizer()

											self.assertListEqual(tokenizer.encode('Hello world!'						,				add_special_tokens=A_     )						,				[0, 31414, 232, 328, 2]     )
											self.assertListEqual(
											    tokenizer.encode('Hello world! cécé herlolip 418'						,				add_special_tokens=A_     )						,				[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]						,				)







				@slow
				def 						UpperCAmelCase_    (       self     )->		Optional[int]:







											'''simple docstring'''






											UpperCamelCase   			=     self.tokenizer_class.from_pretrained('roberta-base'     )

											UpperCamelCase   			=     tokenizer.encode('sequence builders'						,				add_special_tokens=A_     )
											UpperCamelCase   			=     tokenizer.encode('multi-sequence build'						,				add_special_tokens=A_     )

											UpperCamelCase   			=     tokenizer.encode(
											    'sequence builders'						,				add_special_tokens=A_						,				add_prefix_space=A_     )
											UpperCamelCase   			=     tokenizer.encode(
											    'sequence builders'						,				'multi-sequence build'						,				add_special_tokens=A_						,				add_prefix_space=A_     )

											UpperCamelCase   			=     tokenizer.build_inputs_with_special_tokens(A_     )
											UpperCamelCase   			=     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     )->		str:







											'''simple docstring'''






											UpperCamelCase   			=     self.get_tokenizer()

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

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

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

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

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

											UpperCamelCase   			=     'Encode <mask> sequence'
											UpperCamelCase   			=     'Encode <mask>sequence'

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

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







				def 						UpperCAmelCase_    (       self     )->		Any:







											'''simple docstring'''






											pass







				def 						UpperCAmelCase_    (       self     )->		int:







											'''simple docstring'''






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

																									UpperCamelCase   			=     tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']     )
																									UpperCamelCase   			=     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, 50264, 3823, 487, 21992, 3645, 4, 2]     )
																									self.assertSequenceEqual(tokens_r['input_ids']						,				[0, 250, 6, 50264, 3823, 487, 21992, 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     )->		Optional[Any]:







											'''simple docstring'''






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

																		UpperCamelCase   			=     json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
																		UpperCamelCase   			=     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     )->		Any:







											'''simple docstring'''






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

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     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)),
																									# )

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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_     ))						,				)

																									UpperCamelCase   			=     self.rust_tokenizer_class.from_pretrained(
																									    A_						,				use_fast=A_						,				add_prefix_space=A_						,				trim_offsets=A_     )
																									UpperCamelCase   			=     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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase					:    Union[str, Any]           = {
    'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
    'processing_git': ['GitProcessor'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    List[Any]           = [
						    'GIT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'GitForCausalLM',
						    'GitModel',
						    'GitPreTrainedModel',
						    'GitVisionModel',
						]

if TYPE_CHECKING:
						from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
						from .processing_git import GitProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_git import (
												    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GitForCausalLM,
												    GitModel,
												    GitPreTrainedModel,
												    GitVisionModel,
												)

else:
						import sys

						lowerCAmelCase					:    Optional[Any]           = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




