





import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors






@require_tokenizers
class       __A					(					lowerCAmelCase    ,       unittest.TestCase				):

			'''simple docstring'''







			lowerCAmelCase_							  =		MvpTokenizer
			lowerCAmelCase_							  =		MvpTokenizerFast
			lowerCAmelCase_							  =		True
			lowerCAmelCase_							  =		filter_roberta_detectors





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				super().setUp()
				lowerCamelCase__              =	[
				    '''l''',
				    '''o''',
				    '''w''',
				    '''e''',
				    '''r''',
				    '''s''',
				    '''t''',
				    '''i''',
				    '''d''',
				    '''n''',
				    '''\u0120''',
				    '''\u0120l''',
				    '''\u0120n''',
				    '''\u0120lo''',
				    '''\u0120low''',
				    '''er''',
				    '''\u0120lowest''',
				    '''\u0120newer''',
				    '''\u0120wider''',
				    '''<unk>''',
				]
				lowerCamelCase__              =	dict(zip(__lowerCAmelCase ,						range(len(__lowerCAmelCase							)							)							)							)
				lowerCamelCase__              =	['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
				lowerCamelCase__              =	{'''unk_token''': '''<unk>'''}

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





			def 	__lowerCamelCase       (					self ,						**__lowerCAmelCase							):



				'''simple docstring'''







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





			def 	__lowerCamelCase       (					self ,						**__lowerCAmelCase							):



				'''simple docstring'''







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





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase							):



				'''simple docstring'''







				return "lower newer", "lower newer"





			@cached_property
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				return MvpTokenizer.from_pretrained('''RUCAIBox/mvp'''							)





			@cached_property
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				return MvpTokenizerFast.from_pretrained('''RUCAIBox/mvp'''							)





			@require_torch
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
				lowerCamelCase__              =	[0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					lowerCamelCase__              =	tokenizer(__lowerCAmelCase ,						max_length=len(__lowerCAmelCase							) ,						padding=__lowerCAmelCase ,						return_tensors='''pt'''							)
					self.assertIsInstance(__lowerCAmelCase ,						__lowerCAmelCase							)

					self.assertEqual((2, 9) ,						batch.input_ids.shape							)
					self.assertEqual((2, 9) ,						batch.attention_mask.shape							)
					lowerCamelCase__              =	batch.input_ids.tolist()[0]
					self.assertListEqual(__lowerCAmelCase ,						__lowerCAmelCase							)
					# Test that special tokens are reset





			@require_torch
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					lowerCamelCase__              =	tokenizer(__lowerCAmelCase ,						padding=__lowerCAmelCase ,						return_tensors='''pt'''							)
					# check if input_ids are returned and no labels
					self.assertIn('''input_ids''' ,						__lowerCAmelCase							)
					self.assertIn('''attention_mask''' ,						__lowerCAmelCase							)
					self.assertNotIn('''labels''' ,						__lowerCAmelCase							)
					self.assertNotIn('''decoder_attention_mask''' ,						__lowerCAmelCase							)





			@require_torch
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	[
				    '''Summary of the text.''',
				    '''Another summary.''',
				]
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					lowerCamelCase__              =	tokenizer(text_target=__lowerCAmelCase ,						max_length=3_2 ,						padding='''max_length''' ,						return_tensors='''pt'''							)
					self.assertEqual(3_2 ,						targets['''input_ids'''].shape[1]							)





			@require_torch
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					lowerCamelCase__              =	tokenizer(
					    ['''I am a small frog''' * 1_0_2_4, '''I am a small frog'''] ,						padding=__lowerCAmelCase ,						truncation=__lowerCAmelCase ,						return_tensors='''pt'''							)
					self.assertIsInstance(__lowerCAmelCase ,						__lowerCAmelCase							)
					self.assertEqual(batch.input_ids.shape ,						(2, 1_0_2_4)							)





			@require_torch
			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	['''A long paragraph for summarization.''']
				lowerCamelCase__              =	[
				    '''Summary of the text.''',
				]
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
					lowerCamelCase__              =	tokenizer(__lowerCAmelCase ,						text_target=__lowerCAmelCase ,						return_tensors='''pt'''							)
					lowerCamelCase__              =	inputs['''input_ids''']
					lowerCamelCase__              =	inputs['''labels''']
					self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()							)
					self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()							)
					self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()							)
					self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				pass





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







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

						# 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''']							) ,						)

						lowerCamelCase__              =	tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']							)
						lowerCamelCase__              =	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_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]							)
						self.assertSequenceEqual(tokens_r['''input_ids'''] ,						[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]							)

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










import warnings

from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor


_a						=   logging.get_logger(__name__)






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			def __init__(					self ,						*__lowerCAmelCase ,						**__lowerCAmelCase							):



				'''simple docstring'''







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



