



import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


SCREAMING_SNAKE_CASE__       =      logging.get_logger(__name__)


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
     """simple docstring"""






     def __init__(     self					:       str				,					*_snake_case					:       Union[str, Any]				,					**_snake_case					:       str					):






        """simple docstring"""


        warnings.warn(
            'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
            ' use DonutImageProcessor instead.'				,					_snake_case				,					)
        super().__init__(*_snake_case				,					**_snake_case					)









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      __lowerCAmelCase     (		UpperCAmelCase_							,     unittest.TestCase      ):
					"""simple docstring"""






					A__				:		int			       =    LongformerTokenizer
					A__				:		Optional[int]			       =    True
					A__				:		Any			       =    LongformerTokenizerFast
					A__				:		Dict			       =    True



					def     _a							(     self					:       int					):






								"""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(_snake_case				,					range(len(_snake_case					)					)					)					)
								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(_snake_case					) + '\n'					)
								with open(self.merges_file				,					'w'				,					encoding='utf-8'					) as fp:
											fp.write('\n'.join(_snake_case					)					)



					def     _a							(     self					:       int				,					**_snake_case					:       Union[str, Any]					):






								"""simple docstring"""


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



					def     _a							(     self					:       Optional[int]				,					**_snake_case					:       List[Any]					):






								"""simple docstring"""


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



					def     _a							(     self					:       Any				,					_snake_case					:       Optional[Any]					):






								"""simple docstring"""


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



					def     _a							(     self					:       Any					):






								"""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(_snake_case					)  # , add_prefix_space=True)
								self.assertListEqual(_snake_case				,					_snake_case					)

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



					def     _a							(     self					:       List[str]					):






								"""simple docstring"""


								A__       =    self.get_tokenizer()

								self.assertListEqual(tokenizer.encode('Hello world!'				,					add_special_tokens=_snake_case					)				,					[0, 3_14_14, 2_32, 3_28, 2]					)
								self.assertListEqual(
								    tokenizer.encode('Hello world! cécé herlolip 418'				,					add_special_tokens=_snake_case					)				,					[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]				,					)



					@slow
					def     _a							(     self					:       List[Any]					):






								"""simple docstring"""


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

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

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

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

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode



					def     _a							(     self					:       List[str]					):






								"""simple docstring"""


								A__       =    self.get_tokenizer()

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

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

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

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

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

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

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

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



					def     _a							(     self					:       Dict					):






								"""simple docstring"""


								pass



					def     _a							(     self					:       Union[str, Any]					):






								"""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(_snake_case				,					**_snake_case					)
														A__       =    self.tokenizer_class.from_pretrained(_snake_case				,					**_snake_case					)
														A__       =    'A, <mask> AllenNLP sentence.'
														A__       =    tokenizer_r.encode_plus(_snake_case				,					add_special_tokens=_snake_case				,					return_token_type_ids=_snake_case					)
														A__       =    tokenizer_p.encode_plus(_snake_case				,					add_special_tokens=_snake_case				,					return_token_type_ids=_snake_case					)

														# 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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]					)
														self.assertSequenceEqual(tokens_r['input_ids']				,					[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]					)

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



					def     _a							(     self					:       List[Any]					):






								"""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=_snake_case				,					add_prefix_space=_snake_case				,					trim_offsets=_snake_case					)

											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']				,					_snake_case					)

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



					def     _a							(     self					:       Optional[Any]					):






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

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

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

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

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

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

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




