



'''simple docstring'''



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 	lowerCamelCase_							(					snake_case_    ,				unittest.TestCase			):
						_lowerCAmelCase     :   List[str]	     =				MvpTokenizer
						_lowerCAmelCase     :   Tuple	     =				MvpTokenizerFast
						_lowerCAmelCase     :   Dict	     =				True
						_lowerCAmelCase     :   Any	     =				filter_roberta_detectors







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													super().setUp()
													SCREAMING_SNAKE_CASE					:      int     					=			[
													    '''l''',
													    '''o''',
													    '''w''',
													    '''e''',
													    '''r''',
													    '''s''',
													    '''t''',
													    '''i''',
													    '''d''',
													    '''n''',
													    '''\u0120''',
													    '''\u0120l''',
													    '''\u0120n''',
													    '''\u0120lo''',
													    '''\u0120low''',
													    '''er''',
													    '''\u0120lowest''',
													    '''\u0120newer''',
													    '''\u0120wider''',
													    '''<unk>''',
													]
													SCREAMING_SNAKE_CASE					:      Dict     					=			dict(zip(lowerCAmelCase__				,    range(len(lowerCAmelCase__				)				)				)				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			{'''unk_token''': '''<unk>'''}

													SCREAMING_SNAKE_CASE					:      str     					=			os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES['''vocab_file''']				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			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 					__lowercase    (  self   :      List[str]				,    **lowerCAmelCase__   :      str				):

													"""simple docstring"""
													kwargs.update(self.special_tokens_map				)
													return self.tokenizer_class.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Dict				,    **lowerCAmelCase__   :      List[str]				):

													"""simple docstring"""
													kwargs.update(self.special_tokens_map				)
													return self.rust_tokenizer_class.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Dict				,    lowerCAmelCase__   :      List[Any]				):

													"""simple docstring"""
													return "lower newer", "lower newer"







						@cached_property
						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													return MvpTokenizer.from_pretrained('''RUCAIBox/mvp'''				)







						@cached_property
						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													return MvpTokenizerFast.from_pretrained('''RUCAIBox/mvp'''				)







						@require_torch
						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
													SCREAMING_SNAKE_CASE					:      str     					=			[0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				SCREAMING_SNAKE_CASE					:      Dict     					=			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				)
																				SCREAMING_SNAKE_CASE					:      int     					=			batch.input_ids.tolist()[0]
																				self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)
																				# Test that special tokens are reset







						@require_torch
						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				SCREAMING_SNAKE_CASE					:      str     					=			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 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      int     					=			[
													    '''Summary of the text.''',
													    '''Another summary.''',
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				SCREAMING_SNAKE_CASE					:      List[str]     					=			tokenizer(text_target=lowerCAmelCase__				,    max_length=32				,    padding='''max_length'''				,    return_tensors='''pt'''				)
																				self.assertEqual(32				,    targets['''input_ids'''].shape[1]				)







						@require_torch
						def 					__lowercase    (  self   :      str				):

													"""simple docstring"""
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer(
																				    ['''I am a small frog''' * 10_24, '''I am a small frog''']				,    padding=lowerCAmelCase__				,    truncation=lowerCAmelCase__				,    return_tensors='''pt'''				)
																				self.assertIsInstance(lowerCAmelCase__				,    lowerCAmelCase__				)
																				self.assertEqual(batch.input_ids.shape				,    (2, 10_24)				)







						@require_torch
						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			['''A long paragraph for summarization.''']
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			[
													    '''Summary of the text.''',
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				SCREAMING_SNAKE_CASE					:      List[str]     					=			tokenizer(lowerCAmelCase__				,    text_target=lowerCAmelCase__				,    return_tensors='''pt'''				)
																				SCREAMING_SNAKE_CASE					:      str     					=			inputs['''input_ids''']
																				SCREAMING_SNAKE_CASE					:      int     					=			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 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													pass







						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																				with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
																											SCREAMING_SNAKE_CASE					:      Dict     					=			self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__				,    **lowerCAmelCase__				)
																											SCREAMING_SNAKE_CASE					:      List[str]     					=			self.tokenizer_class.from_pretrained(lowerCAmelCase__				,    **lowerCAmelCase__				)
																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			'''A, <mask> AllenNLP sentence.'''
																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer_r.encode_plus(lowerCAmelCase__				,    add_special_tokens=lowerCAmelCase__				,    return_token_type_ids=lowerCAmelCase__				)
																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			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''']				)				,    )

																											SCREAMING_SNAKE_CASE					:      Dict     					=			tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']				)
																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			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(
																											    lowerCAmelCase__				,    ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']				)
																											self.assertSequenceEqual(
																											    lowerCAmelCase__				,    ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']				)









'''simple docstring'''



import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
							from PIL import Image

							from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor
@require_vision
class 	lowerCamelCase_							(					unittest.TestCase			):







						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tempfile.mkdtemp()

													SCREAMING_SNAKE_CASE					:      int     					=			[
													    '''[UNK]''',
													    '''[CLS]''',
													    '''[SEP]''',
													    '''[PAD]''',
													    '''[MASK]''',
													    '''的''',
													    '''价''',
													    '''格''',
													    '''是''',
													    '''15''',
													    '''便''',
													    '''alex''',
													    '''##andra''',
													    '''，''',
													    '''。''',
													    '''-''',
													    '''t''',
													    '''shirt''',
													]
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES['''vocab_file''']				)
													with open(self.vocab_file				,    '''w'''				,    encoding='''utf-8'''				) as vocab_writer:
																				vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]				)				)

													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			{
													    '''do_resize''': True,
													    '''size''': {'''height''': 2_24, '''width''': 2_24},
													    '''do_center_crop''': True,
													    '''crop_size''': {'''height''': 18, '''width''': 18},
													    '''do_normalize''': True,
													    '''image_mean''': [0.4814_5466, 0.457_8275, 0.4082_1073],
													    '''image_std''': [0.2686_2954, 0.2613_0258, 0.2757_7711],
													    '''do_convert_rgb''': True,
													}
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			os.path.join(self.tmpdirname				,    lowerCAmelCase__				)
													with open(self.image_processor_file				,    '''w'''				,    encoding='''utf-8'''				) as fp:
																				json.dump(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      str				,    **lowerCAmelCase__   :      int				):

													"""simple docstring"""
													return BertTokenizer.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Any				,    **lowerCAmelCase__   :      Dict				):

													"""simple docstring"""
													return BertTokenizerFast.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[Any]				,    **lowerCAmelCase__   :      Dict				):

													"""simple docstring"""
													return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[Any]				):

													"""simple docstring"""
													shutil.rmtree(self.tmpdirname				)







						def 					__lowercase    (  self   :      int				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			[np.random.randint(2_55				,    size=(3, 30, 4_00)				,    dtype=np.uinta				)]

													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			[Image.fromarray(np.moveaxis(lowerCAmelCase__				,    0				,    -1				)				) for x in image_inputs]

													return image_inputs







						def 					__lowercase    (  self   :      int				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			self.get_tokenizer()
													SCREAMING_SNAKE_CASE					:      str     					=			self.get_rust_tokenizer()
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.get_image_processor()

													SCREAMING_SNAKE_CASE					:      Dict     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)
													processor_slow.save_pretrained(self.tmpdirname				)
													SCREAMING_SNAKE_CASE					:      List[str]     					=			ChineseCLIPProcessor.from_pretrained(self.tmpdirname				,    use_fast=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)
													processor_fast.save_pretrained(self.tmpdirname				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			ChineseCLIPProcessor.from_pretrained(self.tmpdirname				)

													self.assertEqual(processor_slow.tokenizer.get_vocab()				,    tokenizer_slow.get_vocab()				)
													self.assertEqual(processor_fast.tokenizer.get_vocab()				,    tokenizer_fast.get_vocab()				)
													self.assertEqual(tokenizer_slow.get_vocab()				,    tokenizer_fast.get_vocab()				)
													self.assertIsInstance(processor_slow.tokenizer				,    lowerCAmelCase__				)
													self.assertIsInstance(processor_fast.tokenizer				,    lowerCAmelCase__				)

													self.assertEqual(processor_slow.image_processor.to_json_string()				,    image_processor.to_json_string()				)
													self.assertEqual(processor_fast.image_processor.to_json_string()				,    image_processor.to_json_string()				)
													self.assertIsInstance(processor_slow.image_processor				,    lowerCAmelCase__				)
													self.assertIsInstance(processor_fast.image_processor				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Tuple				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			ChineseCLIPProcessor(tokenizer=self.get_tokenizer()				,    image_processor=self.get_image_processor()				)
													processor.save_pretrained(self.tmpdirname				)

													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			self.get_tokenizer(cls_token='''(CLS)'''				,    sep_token='''(SEP)'''				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			self.get_image_processor(do_normalize=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			ChineseCLIPProcessor.from_pretrained(
													    self.tmpdirname				,    cls_token='''(CLS)'''				,    sep_token='''(SEP)'''				,    do_normalize=lowerCAmelCase__				)

													self.assertEqual(processor.tokenizer.get_vocab()				,    tokenizer_add_kwargs.get_vocab()				)
													self.assertIsInstance(processor.tokenizer				,    lowerCAmelCase__				)

													self.assertEqual(processor.image_processor.to_json_string()				,    image_processor_add_kwargs.to_json_string()				)
													self.assertIsInstance(processor.image_processor				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			self.get_image_processor()
													SCREAMING_SNAKE_CASE					:      str     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Tuple     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.prepare_image_inputs()

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			image_processor(lowerCAmelCase__				,    return_tensors='''np'''				)
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			processor(images=lowerCAmelCase__				,    return_tensors='''np'''				)

													for key in input_feat_extract.keys():
																				self.assertAlmostEqual(input_feat_extract[key].sum()				,    input_processor[key].sum()				,    delta=1e-2				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			self.get_image_processor()
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Tuple     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			'''Alexandra，T-shirt的价格是15便士。'''

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			processor(text=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[str]     					=			tokenizer(lowerCAmelCase__				)

													for key in encoded_tok.keys():
																				self.assertListEqual(encoded_tok[key]				,    encoded_processor[key]				)







						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_image_processor()
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Tuple     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      str     					=			'''Alexandra，T-shirt的价格是15便士。'''
													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.prepare_image_inputs()

													SCREAMING_SNAKE_CASE					:      List[str]     					=			processor(text=lowerCAmelCase__				,    images=lowerCAmelCase__				)

													self.assertListEqual(list(inputs.keys()				)				,    ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']				)

													# test if it raises when no input is passed
													with pytest.raises(lowerCAmelCase__				):
																				processor()







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.get_image_processor()
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Tuple     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

													SCREAMING_SNAKE_CASE					:      Any     					=			processor.batch_decode(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tokenizer.batch_decode(lowerCAmelCase__				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      str     					=			self.get_image_processor()
													SCREAMING_SNAKE_CASE					:      List[str]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Dict     					=			ChineseCLIPProcessor(tokenizer=lowerCAmelCase__				,    image_processor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			'''Alexandra，T-shirt的价格是15便士。'''
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.prepare_image_inputs()

													SCREAMING_SNAKE_CASE					:      Any     					=			processor(text=lowerCAmelCase__				,    images=lowerCAmelCase__				)

													self.assertListEqual(list(inputs.keys()				)				,    processor.model_input_names				)




