



import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__A   			=get_tests_dir("fixtures/spiece.model")

@require_sentencepiece
@require_tokenizers
class 		UpperCAmelCase__			(			__UpperCamelCase						,unittest.TestCase   ):




			'''simple docstring'''






			UpperCamelCase									=       DebertaVaTokenizer
			UpperCamelCase									=       DebertaVaTokenizerFast
			UpperCamelCase									=       True
			UpperCamelCase									=       True




			def  snake_case__     (   self							: List[str] ):
					'''simple docstring'''





					super().setUp()

					# We have a SentencePiece fixture for testing
					__UpperCAmelCase    :     List[Any]													=	DebertaVaTokenizer(a_       ,       unk_token='''<unk>''' )
					tokenizer.save_pretrained(self.tmpdirname )




			def  snake_case__     (   self							: List[str]       ,       a_							: List[Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	'''this is a test'''
					__UpperCAmelCase    :     List[str]													=	'''this is a test'''
					return input_text, output_text




			def  snake_case__     (   self							: Dict ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[str]													=	'''<pad>'''
					__UpperCAmelCase    :     Optional[Any]													=	0

					self.assertEqual(self.get_tokenizer()._convert_token_to_id(a_ )       ,       a_ )
					self.assertEqual(self.get_tokenizer()._convert_id_to_token(a_ )       ,       a_ )




			def  snake_case__     (   self							: str ):
					'''simple docstring'''





					__UpperCAmelCase    :     Union[str, Any]													=	list(self.get_tokenizer().get_vocab().keys() )
					self.assertEqual(vocab_keys[0]       ,       '''<pad>''' )
					self.assertEqual(vocab_keys[1]       ,       '''<unk>''' )
					self.assertEqual(vocab_keys[-1]       ,       '''[PAD]''' )
					self.assertEqual(len(a_ )       ,       3_00_01 )




			def  snake_case__     (   self							: Optional[Any] ):
					'''simple docstring'''





					self.assertEqual(self.get_tokenizer().vocab_size       ,       3_00_00 )




			def  snake_case__     (   self							: Optional[Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     str													=	''' \tHeLLo!how  \n Are yoU?  '''
					__UpperCAmelCase    :     Union[str, Any]													=	['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
					# fmt: on

					__UpperCAmelCase    :     int													=	DebertaVaTokenizer(a_       ,       do_lower_case=a_ )
					__UpperCAmelCase    :     List[str]													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Optional[Any]													=	DebertaVaTokenizerFast(a_       ,       do_lower_case=a_ )
					__UpperCAmelCase    :     str													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )




			@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
			def  snake_case__     (   self							: Union[str, Any] ):
					'''simple docstring'''





					pass




			@unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
			def  snake_case__     (   self							: List[str] ):
					'''simple docstring'''





					pass




			def  snake_case__     (   self							: Any ):
					'''simple docstring'''





					__UpperCAmelCase    :     Optional[int]													=	'''I was born in 92000, and this is falsé.'''
					__UpperCAmelCase    :     Optional[Any]													=	['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
					# fmt: on

					__UpperCAmelCase    :     Any													=	DebertaVaTokenizer(a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     str													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     int													=	DebertaVaTokenizerFast(a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     Optional[Any]													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: List[Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	'''I was born in 92000, and this is falsé.'''
					__UpperCAmelCase    :     Optional[int]													=	['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
					# fmt: on

					__UpperCAmelCase    :     Union[str, Any]													=	DebertaVaTokenizer(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     List[Any]													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Any													=	DebertaVaTokenizerFast(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     List[Any]													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )
					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: Dict ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[Any]													=	'''I was born in 92000, and this is falsé.'''
					__UpperCAmelCase    :     List[str]													=	['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
					# fmt: on

					__UpperCAmelCase    :     Dict													=	DebertaVaTokenizer(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     List[Any]													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     List[str]													=	DebertaVaTokenizerFast(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     List[str]													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: List[str] ):
					'''simple docstring'''





					__UpperCAmelCase    :     Optional[Any]													=	'''I was born in 92000, and this is falsé.'''
					__UpperCAmelCase    :     Dict													=	['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
					# fmt: on

					__UpperCAmelCase    :     List[Any]													=	DebertaVaTokenizer(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     Any													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Tuple													=	DebertaVaTokenizerFast(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     Tuple													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: Optional[int] ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[str]													=	''' \tHeLLo!how  \n Are yoU?  '''
					__UpperCAmelCase    :     Optional[Any]													=	['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
					# fmt: on

					__UpperCAmelCase    :     Union[str, Any]													=	DebertaVaTokenizer(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     Optional[int]													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     List[str]													=	DebertaVaTokenizerFast(a_       ,       do_lower_case=a_       ,       split_by_punct=a_ )
					__UpperCAmelCase    :     Dict													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )

					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: List[Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[str]													=	self.get_tokenizer()
					__UpperCAmelCase    :     Any													=	self.get_rust_tokenizer()

					__UpperCAmelCase    :     Optional[Any]													=	'''I was born in 92000, and this is falsé.'''

					__UpperCAmelCase    :     List[Any]													=	tokenizer.convert_ids_to_tokens(tokenizer.encode(a_       ,       add_special_tokens=a_ ) )
					__UpperCAmelCase    :     Optional[Any]													=	rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a_       ,       add_special_tokens=a_ ) )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Tuple													=	tokenizer.encode(a_       ,       add_special_tokens=a_ )
					__UpperCAmelCase    :     Any													=	rust_tokenizer.encode(a_       ,       add_special_tokens=a_ )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Union[str, Any]													=	self.get_rust_tokenizer()
					__UpperCAmelCase    :     Dict													=	tokenizer.encode(a_ )
					__UpperCAmelCase    :     int													=	rust_tokenizer.encode(a_ )
					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: Any ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[Any]													=	'''This is a test'''
					__UpperCAmelCase    :     Any													=	[13, 1, 43_98, 25, 21, 12_89]
					__UpperCAmelCase    :     int													=	['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
					__UpperCAmelCase    :     Optional[int]													=	['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

					__UpperCAmelCase    :     int													=	DebertaVaTokenizer(a_       ,       keep_accents=a_ )
					__UpperCAmelCase    :     Dict													=	DebertaVaTokenizerFast(a_       ,       keep_accents=a_ )

					__UpperCAmelCase    :     Any													=	tokenizer.encode(a_       ,       add_special_tokens=a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     List[Any]													=	tokenizer.tokenize(a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     List[Any]													=	tokenizer.convert_ids_to_tokens(a_ )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     Tuple													=	rust_tokenizer.encode(a_       ,       add_special_tokens=a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     Optional[int]													=	rust_tokenizer.tokenize(a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     Optional[Any]													=	rust_tokenizer.convert_ids_to_tokens(a_ )
					self.assertListEqual(a_       ,       a_ )

					# fmt: off
					__UpperCAmelCase    :     Dict													=	'''I was born in 92000, and this is falsé.'''
					__UpperCAmelCase    :     Optional[Any]													=	[13, 1, 23, 3_86, 19, 5_61, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]
					__UpperCAmelCase    :     Dict													=	['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
					__UpperCAmelCase    :     Optional[Any]													=	['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
					# fmt: on

					__UpperCAmelCase    :     Dict													=	tokenizer.encode(a_       ,       add_special_tokens=a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     Optional[Any]													=	tokenizer.tokenize(a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     int													=	tokenizer.convert_ids_to_tokens(a_ )
					self.assertListEqual(a_       ,       a_ )

					__UpperCAmelCase    :     int													=	rust_tokenizer.encode(a_       ,       add_special_tokens=a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     Tuple													=	rust_tokenizer.tokenize(a_ )
					self.assertListEqual(a_       ,       a_ )
					__UpperCAmelCase    :     List[Any]													=	rust_tokenizer.convert_ids_to_tokens(a_ )
					self.assertListEqual(a_       ,       a_ )




			def  snake_case__     (   self							: List[Any] ):
					'''simple docstring'''





					__UpperCAmelCase    :     Any													=	DebertaVaTokenizer(a_ )

					__UpperCAmelCase    :     List[Any]													=	tokenizer.encode('''sequence builders''' )
					__UpperCAmelCase    :     int													=	tokenizer.encode('''multi-sequence build''' )

					__UpperCAmelCase    :     Tuple													=	tokenizer.build_inputs_with_special_tokens(a_ )
					__UpperCAmelCase    :     int													=	tokenizer.build_inputs_with_special_tokens(a_       ,       a_ )

					self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]       ,       a_ )
					self.assertEqual(
					    [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]       ,       a_       ,       )




			@slow
			def  snake_case__     (   self							: Dict ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	{'''input_ids''': [[1, 3_98_67, 36, 1_93_90, 4_86, 27, 3_50_52, 8_14_36, 18, 6_06_85, 12_25, 7, 3_50_52, 8_14_36, 18, 93_67, 1_68_99, 18, 1_59_37, 53, 5_94, 7_73, 18, 1_62_87, 3_04_65, 36, 1_59_37, 6, 4_11_39, 38, 3_69_79, 6_07_63, 1_91, 6, 3_41_32, 99, 6, 5_05_38, 3_90, 4_32_30, 6, 3_41_32, 27_79, 2_08_50, 14, 6_99, 10_72, 11_94, 36, 3_82, 1_09_01, 53, 7, 6_99, 10_72, 20_84, 36, 2_04_22, 6_30, 53, 19, 1_05, 30_49, 18_96, 10_53, 1_68_99, 15_06, 11, 3_79_78, 42_43, 7, 12_37, 3_18_69, 2_00, 1_65_66, 6_54, 6, 3_50_52, 8_14_36, 7, 5_56_30, 1_35_93, 4, 2], [1, 26, 1_50_11, 13, 6_67, 8, 10_53, 18, 2_36_11, 12_37, 7_23_56, 1_28_20, 34, 10_41_34, 12_09, 35, 1_33_13, 66_27, 21, 2_02, 3_47, 7, 1_64, 23_99, 11, 46, 44_85, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 12_32, 28_64, 1_57_85, 1_49_51, 1_05, 5, 85_81, 12_50, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
					# fmt: on

					self.tokenizer_integration_test_util(
					    expected_encoding=a_       ,       model_name='''microsoft/deberta-v2-xlarge'''       ,       revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''       ,       )










from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


__A   			=logging.get_logger(__name__)


if is_vision_available():
				import PIL

class 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






			UpperCamelCase									=       ["""pixel_values"""]




			def __init__(   self							: Tuple       ,       a_							: bool = True       ,       a_							: Dict[str, int] = None       ,       a_							: PILImageResampling = PILImageResampling.BICUBIC       ,       a_							: bool = True       ,       a_							: Dict[str, int] = None       ,       a_							: bool = True       ,       a_							: Union[int, float] = 1 / 2_55       ,       a_							: bool = True       ,       a_							: Optional[Union[float, List[float]]] = None       ,       a_							: Optional[Union[float, List[float]]] = None       ,       a_							: bool = True       ,       **a_							: str       ,       ):
					'''simple docstring'''





					super().__init__(**a_ )
					__UpperCAmelCase    :     List[Any]													=	size if size is not None else {'''shortest_edge''': 2_24}
					__UpperCAmelCase    :     List[str]													=	get_size_dict(a_       ,       default_to_square=a_ )
					__UpperCAmelCase    :     int													=	crop_size if crop_size is not None else {'''height''': 2_24, '''width''': 2_24}
					__UpperCAmelCase    :     Optional[int]													=	get_size_dict(a_       ,       default_to_square=a_       ,       param_name='''crop_size''' )

					__UpperCAmelCase    :     int													=	do_resize
					__UpperCAmelCase    :     Union[str, Any]													=	size
					__UpperCAmelCase    :     Union[str, Any]													=	resample
					__UpperCAmelCase    :     Any													=	do_center_crop
					__UpperCAmelCase    :     Any													=	crop_size
					__UpperCAmelCase    :     Any													=	do_rescale
					__UpperCAmelCase    :     Dict													=	rescale_factor
					__UpperCAmelCase    :     Union[str, Any]													=	do_normalize
					__UpperCAmelCase    :     Any													=	image_mean if image_mean is not None else OPENAI_CLIP_MEAN
					__UpperCAmelCase    :     int													=	image_std if image_std is not None else OPENAI_CLIP_STD
					__UpperCAmelCase    :     List[str]													=	do_convert_rgb




			def  snake_case__     (   self							: Optional[Any]       ,       a_							: np.ndarray       ,       a_							: Dict[str, int]       ,       a_							: PILImageResampling = PILImageResampling.BICUBIC       ,       a_							: Optional[Union[str, ChannelDimension]] = None       ,       **a_							: Optional[int]       ,       ):
					'''simple docstring'''





					__UpperCAmelCase    :     Dict													=	get_size_dict(a_       ,       default_to_square=a_ )
					if "shortest_edge" not in size:
							raise ValueError(F'The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}' )
					__UpperCAmelCase    :     Optional[int]													=	get_resize_output_image_size(a_       ,       size=size['''shortest_edge''']       ,       default_to_square=a_ )
					return resize(a_       ,       size=a_       ,       resample=a_       ,       data_format=a_       ,       **a_ )




			def  snake_case__     (   self							: Union[str, Any]       ,       a_							: np.ndarray       ,       a_							: Dict[str, int]       ,       a_							: Optional[Union[str, ChannelDimension]] = None       ,       **a_							: Dict       ,       ):
					'''simple docstring'''





					__UpperCAmelCase    :     Optional[Any]													=	get_size_dict(a_ )
					if "height" not in size or "width" not in size:
							raise ValueError(F'The `size` parameter must contain the keys (height, width). Got {size.keys()}' )
					return center_crop(a_       ,       size=(size['''height'''], size['''width'''])       ,       data_format=a_       ,       **a_ )




			def  snake_case__     (   self							: Union[str, Any]       ,       a_							: np.ndarray       ,       a_							: Union[int, float]       ,       a_							: Optional[Union[str, ChannelDimension]] = None       ,       **a_							: List[str]       ,       ):
					'''simple docstring'''





					return rescale(a_       ,       scale=a_       ,       data_format=a_       ,       **a_ )




			def  snake_case__     (   self							: Optional[Any]       ,       a_							: np.ndarray       ,       a_							: Union[float, List[float]]       ,       a_							: Union[float, List[float]]       ,       a_							: Optional[Union[str, ChannelDimension]] = None       ,       **a_							: Dict       ,       ):
					'''simple docstring'''





					return normalize(a_       ,       mean=a_       ,       std=a_       ,       data_format=a_       ,       **a_ )




			def  snake_case__     (   self							: Any       ,       a_							: ImageInput       ,       a_							: bool = None       ,       a_							: Dict[str, int] = None       ,       a_							: PILImageResampling = None       ,       a_							: bool = None       ,       a_							: int = None       ,       a_							: bool = None       ,       a_							: float = None       ,       a_							: bool = None       ,       a_							: Optional[Union[float, List[float]]] = None       ,       a_							: Optional[Union[float, List[float]]] = None       ,       a_							: bool = None       ,       a_							: Optional[Union[str, TensorType]] = None       ,       a_							: Optional[ChannelDimension] = ChannelDimension.FIRST       ,       **a_							: Dict       ,       ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	do_resize if do_resize is not None else self.do_resize
					__UpperCAmelCase    :     Optional[Any]													=	size if size is not None else self.size
					__UpperCAmelCase    :     Dict													=	get_size_dict(a_       ,       param_name='''size'''       ,       default_to_square=a_ )
					__UpperCAmelCase    :     int													=	resample if resample is not None else self.resample
					__UpperCAmelCase    :     Optional[Any]													=	do_center_crop if do_center_crop is not None else self.do_center_crop
					__UpperCAmelCase    :     Any													=	crop_size if crop_size is not None else self.crop_size
					__UpperCAmelCase    :     Dict													=	get_size_dict(a_       ,       param_name='''crop_size'''       ,       default_to_square=a_ )
					__UpperCAmelCase    :     int													=	do_rescale if do_rescale is not None else self.do_rescale
					__UpperCAmelCase    :     Optional[int]													=	rescale_factor if rescale_factor is not None else self.rescale_factor
					__UpperCAmelCase    :     List[str]													=	do_normalize if do_normalize is not None else self.do_normalize
					__UpperCAmelCase    :     Optional[int]													=	image_mean if image_mean is not None else self.image_mean
					__UpperCAmelCase    :     Tuple													=	image_std if image_std is not None else self.image_std
					__UpperCAmelCase    :     List[str]													=	do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

					__UpperCAmelCase    :     List[str]													=	make_list_of_images(a_ )

					if not valid_images(a_ ):
							raise ValueError(
							    '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
							    '''torch.Tensor, tf.Tensor or jax.ndarray.''' )

					if do_resize and size is None:
							raise ValueError('''Size must be specified if do_resize is True.''' )

					if do_center_crop and crop_size is None:
							raise ValueError('''Crop size must be specified if do_center_crop is True.''' )

					if do_rescale and rescale_factor is None:
							raise ValueError('''Rescale factor must be specified if do_rescale is True.''' )

					if do_normalize and (image_mean is None or image_std is None):
							raise ValueError('''Image mean and std must be specified if do_normalize is True.''' )

					# PIL RGBA images are converted to RGB
					if do_convert_rgb:
							__UpperCAmelCase    :     Optional[Any]													=	[convert_to_rgb(a_ ) for image in images]

					# All transformations expect numpy arrays.
					__UpperCAmelCase    :     int													=	[to_numpy_array(a_ ) for image in images]

					if do_resize:
							__UpperCAmelCase    :     int													=	[self.resize(image=a_       ,       size=a_       ,       resample=a_ ) for image in images]

					if do_center_crop:
							__UpperCAmelCase    :     List[str]													=	[self.center_crop(image=a_       ,       size=a_ ) for image in images]

					if do_rescale:
							__UpperCAmelCase    :     Dict													=	[self.rescale(image=a_       ,       scale=a_ ) for image in images]

					if do_normalize:
							__UpperCAmelCase    :     Optional[int]													=	[self.normalize(image=a_       ,       mean=a_       ,       std=a_ ) for image in images]

					__UpperCAmelCase    :     Optional[int]													=	[to_channel_dimension_format(a_       ,       a_ ) for image in images]

					__UpperCAmelCase    :     Union[str, Any]													=	{'''pixel_values''': images}
					return BatchFeature(data=a_       ,       tensor_type=a_ )





