"""simple docstring"""







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


SCREAMING_SNAKE_CASE									=						get_tests_dir('fixtures/spiece.model')



@require_sentencepiece
@require_tokenizers
class  _lowerCamelCase			(__lowerCamelCase						,							unittest.TestCase     ):
				_snake_case     =  DebertaVaTokenizer
				_snake_case     =  DebertaVaTokenizerFast
				_snake_case     =  True
				_snake_case     =  True







				def 							__UpperCAmelCase					( self    :       List[Any]						):

					"""simple docstring"""






					super().setUp()

					# We have a SentencePiece fixture for testing
					_lowercase :    Dict							=							DebertaVaTokenizer(lowerCamelCase_			,					unk_token='<unk>'						)
					tokenizer.save_pretrained(self.tmpdirname						)







				def 							__UpperCAmelCase					( self    :       Dict			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					_lowercase :    Optional[Any]							=							'this is a test'
					_lowercase :    int							=							'this is a test'
					return input_text, output_text







				def 							__UpperCAmelCase					( self    :       List[Any]						):

					"""simple docstring"""






					_lowercase :    Optional[int]							=							'<pad>'
					_lowercase :    List[Any]							=							0

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







				def 							__UpperCAmelCase					( self    :       int						):

					"""simple docstring"""






					_lowercase :    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(lowerCamelCase_						)			,					3_0_0_0_1						)







				def 							__UpperCAmelCase					( self    :       str						):

					"""simple docstring"""






					self.assertEqual(self.get_tokenizer().vocab_size			,					3_0_0_0_0						)







				def 							__UpperCAmelCase					( self    :       Any						):

					"""simple docstring"""






					_lowercase :    Optional[int]							=							' \tHeLLo!how  \n Are yoU?  '
					_lowercase :    Optional[int]							=							['▁hello', '!', 'how', '▁are', '▁you', '?']
					# fmt: on

					_lowercase :    Optional[int]							=							DebertaVaTokenizer(lowerCamelCase_			,					do_lower_case=lowerCamelCase_						)
					_lowercase :    Dict							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    int							=							DebertaVaTokenizerFast(lowerCamelCase_			,					do_lower_case=lowerCamelCase_						)
					_lowercase :    Dict							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				@unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'						)
				def 							__UpperCAmelCase					( self    :       int						):

					"""simple docstring"""






					pass







				@unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'						)
				def 							__UpperCAmelCase					( self    :       Optional[Any]						):

					"""simple docstring"""






					pass







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






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

					_lowercase :    Union[str, Any]							=							DebertaVaTokenizer(lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Optional[int]							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    Optional[int]							=							DebertaVaTokenizerFast(lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Optional[int]							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Optional[Any]						):

					"""simple docstring"""






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

					_lowercase :    Union[str, Any]							=							DebertaVaTokenizer(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    int							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    Dict							=							DebertaVaTokenizerFast(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    List[Any]							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







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

					"""simple docstring"""






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

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

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    Union[str, Any]							=							DebertaVaTokenizerFast(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Dict							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Tuple						):

					"""simple docstring"""






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

					_lowercase :    Optional[int]							=							DebertaVaTokenizer(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Dict							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    Tuple							=							DebertaVaTokenizerFast(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Any							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       List[str]						):

					"""simple docstring"""






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

					_lowercase :    Dict							=							DebertaVaTokenizer(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Dict							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    str							=							DebertaVaTokenizerFast(lowerCamelCase_			,					do_lower_case=lowerCamelCase_			,					split_by_punct=lowerCamelCase_						)
					_lowercase :    Dict							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)

					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







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

					"""simple docstring"""






					_lowercase :    int							=							self.get_tokenizer()
					_lowercase :    str							=							self.get_rust_tokenizer()

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

					_lowercase :    List[str]							=							tokenizer.convert_ids_to_tokens(tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)
					_lowercase :    Optional[int]							=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    List[str]							=							tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					_lowercase :    List[Any]							=							rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    List[Any]							=							self.get_rust_tokenizer()
					_lowercase :    Tuple							=							tokenizer.encode(lowerCamelCase_						)
					_lowercase :    int							=							rust_tokenizer.encode(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       int						):

					"""simple docstring"""






					_lowercase :    Union[str, Any]							=							'This is a test'
					_lowercase :    Tuple							=							[1_3, 1, 4_3_9_8, 2_5, 2_1, 1_2_8_9]
					_lowercase :    Optional[Any]							=							['▁', 'T', 'his', '▁is', '▁a', '▁test']
					_lowercase :    str							=							['▁', '<unk>', 'his', '▁is', '▁a', '▁test']

					_lowercase :    List[Any]							=							DebertaVaTokenizer(lowerCamelCase_			,					keep_accents=lowerCamelCase_						)
					_lowercase :    Optional[Any]							=							DebertaVaTokenizerFast(lowerCamelCase_			,					keep_accents=lowerCamelCase_						)

					_lowercase :    Union[str, Any]							=							tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    Optional[Any]							=							tokenizer.tokenize(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    str							=							tokenizer.convert_ids_to_tokens(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    int							=							rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    int							=							rust_tokenizer.tokenize(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    int							=							rust_tokenizer.convert_ids_to_tokens(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					# fmt: off
					_lowercase :    str							=							'I was born in 92000, and this is falsé.'
					_lowercase :    str							=							[1_3, 1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]
					_lowercase :    str							=							['▁', 'I', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.', ]
					_lowercase :    Optional[int]							=							['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.', ]
					# fmt: on

					_lowercase :    Tuple							=							tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    List[str]							=							tokenizer.tokenize(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    Union[str, Any]							=							tokenizer.convert_ids_to_tokens(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)

					_lowercase :    List[str]							=							rust_tokenizer.encode(lowerCamelCase_			,					add_special_tokens=lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    Any							=							rust_tokenizer.tokenize(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)
					_lowercase :    str							=							rust_tokenizer.convert_ids_to_tokens(lowerCamelCase_						)
					self.assertListEqual(lowerCamelCase_			,					lowerCamelCase_						)







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

					"""simple docstring"""






					_lowercase :    Optional[Any]							=							DebertaVaTokenizer(lowerCamelCase_						)

					_lowercase :    str							=							tokenizer.encode('sequence builders'						)
					_lowercase :    str							=							tokenizer.encode('multi-sequence build'						)

					_lowercase :    Tuple							=							tokenizer.build_inputs_with_special_tokens(lowerCamelCase_						)
					_lowercase :    Union[str, Any]							=							tokenizer.build_inputs_with_special_tokens(lowerCamelCase_			,					lowerCamelCase_						)

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







				@slow
				def 							__UpperCAmelCase					( self    :       Union[str, Any]						):

					"""simple docstring"""






					_lowercase :    Any							=							{'input_ids': [[1, 3_9_8_6_7, 3_6, 1_9_3_9_0, 4_8_6, 2_7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 6_0_6_8_5, 1_2_2_5, 7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 9_3_6_7, 1_6_8_9_9, 1_8, 1_5_9_3_7, 5_3, 5_9_4, 7_7_3, 1_8, 1_6_2_8_7, 3_0_4_6_5, 3_6, 1_5_9_3_7, 6, 4_1_1_3_9, 3_8, 3_6_9_7_9, 6_0_7_6_3, 1_9_1, 6, 3_4_1_3_2, 9_9, 6, 5_0_5_3_8, 3_9_0, 4_3_2_3_0, 6, 3_4_1_3_2, 2_7_7_9, 2_0_8_5_0, 1_4, 6_9_9, 1_0_7_2, 1_1_9_4, 3_6, 3_8_2, 1_0_9_0_1, 5_3, 7, 6_9_9, 1_0_7_2, 2_0_8_4, 3_6, 2_0_4_2_2, 6_3_0, 5_3, 1_9, 1_0_5, 3_0_4_9, 1_8_9_6, 1_0_5_3, 1_6_8_9_9, 1_5_0_6, 1_1, 3_7_9_7_8, 4_2_4_3, 7, 1_2_3_7, 3_1_8_6_9, 2_0_0, 1_6_5_6_6, 6_5_4, 6, 3_5_0_5_2, 8_1_4_3_6, 7, 5_5_6_3_0, 1_3_5_9_3, 4, 2], [1, 2_6, 1_5_0_1_1, 1_3, 6_6_7, 8, 1_0_5_3, 1_8, 2_3_6_1_1, 1_2_3_7, 7_2_3_5_6, 1_2_8_2_0, 3_4, 1_0_4_1_3_4, 1_2_0_9, 3_5, 1_3_3_1_3, 6_6_2_7, 2_1, 2_0_2, 3_4_7, 7, 1_6_4, 2_3_9_9, 1_1, 4_6, 4_4_8_5, 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, 1_2_3_2, 2_8_6_4, 1_5_7_8_5, 1_4_9_5_1, 1_0_5, 5, 8_5_8_1, 1_2_5_0, 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=lowerCamelCase_			,					model_name='microsoft/deberta-v2-xlarge'			,					revision='ad6e42c1532ddf3a15c39246b63f5559d558b670'			,					)




"""simple docstring"""







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,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


SCREAMING_SNAKE_CASE									=						logging.get_logger(__name__)



class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  ["pixel_values"]







				def __init__( self    :       Optional[int]			,					lowerCamelCase_    :       bool = True			,					lowerCamelCase_    :       Optional[Dict[str, int]] = None			,					lowerCamelCase_    :       PILImageResampling = PILImageResampling.BILINEAR			,					lowerCamelCase_    :       bool = True			,					lowerCamelCase_    :       Dict[str, int] = None			,					lowerCamelCase_    :       bool = True			,					lowerCamelCase_    :       Union[int, float] = 1 / 2_5_5			,					lowerCamelCase_    :       bool = True			,					lowerCamelCase_    :       Optional[Union[float, List[float]]] = None			,					lowerCamelCase_    :       Optional[Union[float, List[float]]] = None			,					**lowerCamelCase_    :       int			,					):

					"""simple docstring"""






					super().__init__(**lowerCamelCase_						)
					_lowercase :    Optional[Any]							=							size if size is not None else {'shortest_edge': 2_5_6}
					_lowercase :    Optional[int]							=							get_size_dict(lowerCamelCase_			,					default_to_square=lowerCamelCase_						)
					_lowercase :    List[str]							=							crop_size if crop_size is not None else {'height': 2_2_4, 'width': 2_2_4}
					_lowercase :    Any							=							get_size_dict(lowerCamelCase_						)
					_lowercase :    Optional[int]							=							do_resize
					_lowercase :    Optional[int]							=							size
					_lowercase :    Union[str, Any]							=							resample
					_lowercase :    Optional[Any]							=							do_center_crop
					_lowercase :    Union[str, Any]							=							crop_size
					_lowercase :    Any							=							do_rescale
					_lowercase :    Tuple							=							rescale_factor
					_lowercase :    Optional[int]							=							do_normalize
					_lowercase :    int							=							image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
					_lowercase :    Any							=							image_std if image_std is not None else IMAGENET_STANDARD_STD







				def 							__UpperCAmelCase					( self    :       List[Any]			,					lowerCamelCase_    :       np.ndarray			,					lowerCamelCase_    :       Dict[str, int]			,					lowerCamelCase_    :       PILImageResampling = PILImageResampling.BICUBIC			,					lowerCamelCase_    :       Optional[Union[str, ChannelDimension]] = None			,					**lowerCamelCase_    :       Tuple			,					):

					"""simple docstring"""






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







				def 							__UpperCAmelCase					( self    :       Dict			,					lowerCamelCase_    :       np.ndarray			,					lowerCamelCase_    :       Dict[str, int]			,					lowerCamelCase_    :       Optional[Union[str, ChannelDimension]] = None			,					**lowerCamelCase_    :       str			,					):

					"""simple docstring"""






					_lowercase :    Tuple							=							get_size_dict(lowerCamelCase_						)
					return center_crop(lowerCamelCase_			,					size=(size['height'], size['width'])			,					data_format=lowerCamelCase_			,					**lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Any			,					lowerCamelCase_    :       np.ndarray			,					lowerCamelCase_    :       float			,					lowerCamelCase_    :       Optional[Union[str, ChannelDimension]] = None			,					**lowerCamelCase_    :       Optional[Any]						):

					"""simple docstring"""






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







				def 							__UpperCAmelCase					( self    :       List[Any]			,					lowerCamelCase_    :       np.ndarray			,					lowerCamelCase_    :       Union[float, List[float]]			,					lowerCamelCase_    :       Union[float, List[float]]			,					lowerCamelCase_    :       Optional[Union[str, ChannelDimension]] = None			,					**lowerCamelCase_    :       List[Any]			,					):

					"""simple docstring"""






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







				def 							__UpperCAmelCase					( self    :       List[Any]			,					lowerCamelCase_    :       ImageInput			,					lowerCamelCase_    :       Optional[bool] = None			,					lowerCamelCase_    :       Dict[str, int] = None			,					lowerCamelCase_    :       PILImageResampling = None			,					lowerCamelCase_    :       bool = None			,					lowerCamelCase_    :       Dict[str, int] = None			,					lowerCamelCase_    :       Optional[bool] = None			,					lowerCamelCase_    :       Optional[float] = None			,					lowerCamelCase_    :       Optional[bool] = None			,					lowerCamelCase_    :       Optional[Union[float, List[float]]] = None			,					lowerCamelCase_    :       Optional[Union[float, List[float]]] = None			,					lowerCamelCase_    :       Optional[Union[str, TensorType]] = None			,					lowerCamelCase_    :       Union[str, ChannelDimension] = ChannelDimension.FIRST			,					**lowerCamelCase_    :       int			,					):

					"""simple docstring"""






					_lowercase :    Optional[Any]							=							do_resize if do_resize is not None else self.do_resize
					_lowercase :    List[Any]							=							size if size is not None else self.size
					_lowercase :    Union[str, Any]							=							get_size_dict(lowerCamelCase_			,					default_to_square=lowerCamelCase_						)
					_lowercase :    Any							=							resample if resample is not None else self.resample
					_lowercase :    Tuple							=							do_center_crop if do_center_crop is not None else self.do_center_crop
					_lowercase :    List[Any]							=							crop_size if crop_size is not None else self.crop_size
					_lowercase :    Tuple							=							get_size_dict(lowerCamelCase_						)
					_lowercase :    List[Any]							=							do_rescale if do_rescale is not None else self.do_rescale
					_lowercase :    int							=							rescale_factor if rescale_factor is not None else self.rescale_factor
					_lowercase :    int							=							do_normalize if do_normalize is not None else self.do_normalize
					_lowercase :    str							=							image_mean if image_mean is not None else self.image_mean
					_lowercase :    List[Any]							=							image_std if image_std is not None else self.image_std

					_lowercase :    Union[str, Any]							=							make_list_of_images(lowerCamelCase_						)

					if not valid_images(lowerCamelCase_						):
						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.'						)

					# All transformations expect numpy arrays.
					_lowercase :    Optional[Any]							=							[to_numpy_array(lowerCamelCase_						) for image in images]

					if do_resize:
						_lowercase :    Optional[Any]							=							[self.resize(image=lowerCamelCase_			,					size=lowerCamelCase_			,					resample=lowerCamelCase_						) for image in images]

					if do_center_crop:
						_lowercase :    List[Any]							=							[self.center_crop(image=lowerCamelCase_			,					size=lowerCamelCase_						) for image in images]

					if do_rescale:
						_lowercase :    str							=							[self.rescale(image=lowerCamelCase_			,					scale=lowerCamelCase_						) for image in images]

					if do_normalize:
						_lowercase :    Any							=							[self.normalize(image=lowerCamelCase_			,					mean=lowerCamelCase_			,					std=lowerCamelCase_						) for image in images]

					_lowercase :    int							=							[to_channel_dimension_format(lowerCamelCase_			,					lowerCamelCase_						) for image in images]

					_lowercase :    Tuple							=							{'pixel_values': images}
					return BatchFeature(data=lowerCamelCase_			,					tensor_type=lowerCamelCase_						)



