


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 IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import AlignProcessor, EfficientNetImageProcessor







@require_vision
class 	__lowercase    (unittest.TestCase  ):





							"""simple docstring"""







							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     int					=					tempfile.mkdtemp()

										SCREAMING_SNAKE_CASE_		:     List[Any]					=					[
										    '[UNK]',
										    '[CLS]',
										    '[SEP]',
										    '[PAD]',
										    '[MASK]',
										    'want',
										    '##want',
										    '##ed',
										    'wa',
										    'un',
										    'runn',
										    '##ing',
										    ',',
										    'low',
										    'lowest',
										]
										SCREAMING_SNAKE_CASE_		:     Union[str, 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_		:     Any					=					{
										    'do_resize': True,
										    'size': 2_0,
										    'do_center_crop': True,
										    'crop_size': 1_8,
										    'do_normalize': True,
										    'image_mean': [0.48_145_466, 0.4_578_275, 0.40_821_073],
										    'image_std': [0.26_862_954, 0.26_130_258, 0.27_577_711],
										}
										SCREAMING_SNAKE_CASE_		:     List[str]					=					os.path.join(self.tmpdirname			,						lowerCAmelCase__       )
										with open(self.image_processor_file			,						'w'			,						encoding='utf-8'       ) as fp:
													json.dump(lowerCAmelCase__			,						lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return BertTokenizer.from_pretrained(self.tmpdirname			,						**lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return BertTokenizerFast.from_pretrained(self.tmpdirname			,						**lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										return EfficientNetImageProcessor.from_pretrained(self.tmpdirname			,						**lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										shutil.rmtree(self.tmpdirname       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					[np.random.randint(2_5_5			,						size=(3, 3_0, 4_0_0)			,						dtype=np.uinta       )]
										SCREAMING_SNAKE_CASE_		:     str					=					[Image.fromarray(np.moveaxis(lowerCAmelCase__			,						0			,						-1       )       ) for x in image_inputs]
										return image_inputs






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     str					=					self.get_tokenizer()
										SCREAMING_SNAKE_CASE_		:     Dict					=					self.get_rust_tokenizer()
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					self.get_image_processor()

										SCREAMING_SNAKE_CASE_		:     List[Any]					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )
										processor_slow.save_pretrained(self.tmpdirname       )
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					AlignProcessor.from_pretrained(self.tmpdirname			,						use_fast=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     str					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )
										processor_fast.save_pretrained(self.tmpdirname       )
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					AlignProcessor.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 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					AlignProcessor(tokenizer=self.get_tokenizer()			,						image_processor=self.get_image_processor()       )
										processor.save_pretrained(self.tmpdirname       )

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.get_tokenizer(bos_token='(BOS)'			,						eos_token='(EOS)'       )
										SCREAMING_SNAKE_CASE_		:     Any					=					self.get_image_processor(do_normalize=lowerCAmelCase__			,						padding_value=1.0       )

										SCREAMING_SNAKE_CASE_		:     List[str]					=					AlignProcessor.from_pretrained(
										    self.tmpdirname			,						bos_token='(BOS)'			,						eos_token='(EOS)'			,						do_normalize=lowerCAmelCase__			,						padding_value=1.0       )

										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 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.get_image_processor()
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.get_tokenizer()

										SCREAMING_SNAKE_CASE_		:     List[Any]					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.prepare_image_inputs()

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					image_processor(lowerCAmelCase__			,						return_tensors='np'       )
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					processor(images=lowerCAmelCase__			,						return_tensors='np'       )

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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Any					=					self.get_image_processor()
										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.get_tokenizer()

										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     int					=					'lower newer'

										SCREAMING_SNAKE_CASE_		:     Tuple					=					processor(text=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Tuple					=					tokenizer(lowerCAmelCase__			,						padding='max_length'			,						max_length=6_4       )

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






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.get_image_processor()
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.get_tokenizer()

										SCREAMING_SNAKE_CASE_		:     Any					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Any					=					'lower newer'
										SCREAMING_SNAKE_CASE_		:     List[str]					=					self.prepare_image_inputs()

										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					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 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Tuple					=					self.get_image_processor()
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					self.get_tokenizer()

										SCREAMING_SNAKE_CASE_		:     str					=					AlignProcessor(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_		:     Union[str, Any]					=					processor.batch_decode(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     str					=					tokenizer.batch_decode(lowerCAmelCase__       )

										self.assertListEqual(lowerCAmelCase__			,						lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					self.get_image_processor()
										SCREAMING_SNAKE_CASE_		:     Tuple					=					self.get_tokenizer()

										SCREAMING_SNAKE_CASE_		:     Optional[int]					=					AlignProcessor(tokenizer=lowerCAmelCase__			,						image_processor=lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Any					=					'lower newer'
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.prepare_image_inputs()

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

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







'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase







def 		A_(     A						:		str):
							if not sentence:
														return ""
							UpperCamelCase   			=     dict(zip(A		,     A))
							return lower_to_upper.get(sentence[0]		,     sentence[0]) + sentence[1:]


if __name__ == "__main__":
						from doctest import testmod

						testmod()




