


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 				a		(unittest.TestCase      ):




							"""simple docstring"""


							def     __snake_case					(							self       :  Union[str, Any]				)	->    Dict:
														__snake_case		:			List[Any]							 =   tempfile.mkdtemp()

														__snake_case		:			Dict							 =   [
														    """[UNK]""",
														    """[CLS]""",
														    """[SEP]""",
														    """[PAD]""",
														    """[MASK]""",
														    """的""",
														    """价""",
														    """格""",
														    """是""",
														    """15""",
														    """便""",
														    """alex""",
														    """##andra""",
														    """，""",
														    """。""",
														    """-""",
														    """t""",
														    """shirt""",
														]
														__snake_case		:			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]				)				)

														__snake_case		:			Any							 =   {
														    """do_resize""": True,
														    """size""": {"""height""": 224, """width""": 224},
														    """do_center_crop""": True,
														    """crop_size""": {"""height""": 18, """width""": 18},
														    """do_normalize""": True,
														    """image_mean""": [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
														    """image_std""": [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
														    """do_convert_rgb""": True,
														}
														__snake_case		:			Tuple							 =   os.path.join(self.tmpdirname    ,	lowerCamelCase				)
														with open(self.image_processor_file    ,	"w"    ,	encoding="utf-8"				) as fp:
																					json.dump(lowerCamelCase    ,	lowerCamelCase				)

							def     __snake_case					(							self       :  Optional[int]    ,	**lowerCamelCase       :  Dict				)	->    str:
														return BertTokenizer.from_pretrained(self.tmpdirname    ,	**lowerCamelCase				)

							def     __snake_case					(							self       :  List[str]    ,	**lowerCamelCase       :  str				)	->    Union[str, Any]:
														return BertTokenizerFast.from_pretrained(self.tmpdirname    ,	**lowerCamelCase				)

							def     __snake_case					(							self       :  str    ,	**lowerCamelCase       :  Any				)	->    Optional[int]:
														return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname    ,	**lowerCamelCase				)

							def     __snake_case					(							self       :  List[Any]				)	->    Dict:
														shutil.rmtree(self.tmpdirname				)

							def     __snake_case					(							self       :  Any				)	->    Optional[Any]:
														__snake_case		:			int							 =   [np.random.randint(255    ,	size=(3, 30, 400)    ,	dtype=np.uinta				)]

														__snake_case		:			List[str]							 =   [Image.fromarray(np.moveaxis(lowerCamelCase    ,	0    ,	-1				)				) for x in image_inputs]

														return image_inputs

							def     __snake_case					(							self       :  Union[str, Any]				)	->    int:
														__snake_case		:			List[str]							 =   self.get_tokenizer()
														__snake_case		:			Union[str, Any]							 =   self.get_rust_tokenizer()
														__snake_case		:			int							 =   self.get_image_processor()

														__snake_case		:			Tuple							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)
														processor_slow.save_pretrained(self.tmpdirname				)
														__snake_case		:			Optional[int]							 =   ChineseCLIPProcessor.from_pretrained(self.tmpdirname    ,	use_fast=lowerCamelCase				)

														__snake_case		:			List[str]							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)
														processor_fast.save_pretrained(self.tmpdirname				)
														__snake_case		:			List[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     __snake_case					(							self       :  List[str]				)	->    List[str]:
														__snake_case		:			str							 =   ChineseCLIPProcessor(tokenizer=self.get_tokenizer()    ,	image_processor=self.get_image_processor()				)
														processor.save_pretrained(self.tmpdirname				)

														__snake_case		:			str							 =   self.get_tokenizer(cls_token="(CLS)"    ,	sep_token="(SEP)"				)
														__snake_case		:			Tuple							 =   self.get_image_processor(do_normalize=lowerCamelCase				)

														__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     __snake_case					(							self       :  Any				)	->    Dict:
														__snake_case		:			Dict							 =   self.get_image_processor()
														__snake_case		:			Tuple							 =   self.get_tokenizer()

														__snake_case		:			Optional[int]							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)

														__snake_case		:			Dict							 =   self.prepare_image_inputs()

														__snake_case		:			Tuple							 =   image_processor(lowerCamelCase    ,	return_tensors="np"				)
														__snake_case		:			int							 =   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     __snake_case					(							self       :  Optional[int]				)	->    Dict:
														__snake_case		:			Dict							 =   self.get_image_processor()
														__snake_case		:			Union[str, Any]							 =   self.get_tokenizer()

														__snake_case		:			Dict							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)

														__snake_case		:			Union[str, Any]							 =   """Alexandra，T-shirt的价格是15便士。"""

														__snake_case		:			Dict							 =   processor(text=lowerCamelCase				)

														__snake_case		:			Dict							 =   tokenizer(lowerCamelCase				)

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

							def     __snake_case					(							self       :  int				)	->    List[Any]:
														__snake_case		:			str							 =   self.get_image_processor()
														__snake_case		:			Tuple							 =   self.get_tokenizer()

														__snake_case		:			List[Any]							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)

														__snake_case		:			Optional[int]							 =   """Alexandra，T-shirt的价格是15便士。"""
														__snake_case		:			List[Any]							 =   self.prepare_image_inputs()

														__snake_case		:			Optional[int]							 =   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     __snake_case					(							self       :  str				)	->    Any:
														__snake_case		:			Any							 =   self.get_image_processor()
														__snake_case		:			int							 =   self.get_tokenizer()

														__snake_case		:			Optional[Any]							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)

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

														__snake_case		:			Union[str, Any]							 =   processor.batch_decode(lowerCamelCase				)
														__snake_case		:			List[Any]							 =   tokenizer.batch_decode(lowerCamelCase				)

														self.assertListEqual(lowerCamelCase    ,	lowerCamelCase				)






							def     __snake_case					(							self       :  Tuple				)	->    Union[str, Any]:
														__snake_case		:			Optional[int]							 =   self.get_image_processor()
														__snake_case		:			int							 =   self.get_tokenizer()

														__snake_case		:			Tuple							 =   ChineseCLIPProcessor(tokenizer=lowerCamelCase    ,	image_processor=lowerCamelCase				)

														__snake_case		:			List[Any]							 =   """Alexandra，T-shirt的价格是15便士。"""
														__snake_case		:			Any							 =   self.prepare_image_inputs()

														__snake_case		:			str							 =   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			( lowerCamelCase__    ):
			'''simple docstring'''





			if not sentence:
						return ""
			A_	:						Optional[int]	=     dict(zip(lowerCamelCase__						,      lowerCamelCase__    )    )
			return lower_to_upper.get(sentence[0]						,      sentence[0]    ) + sentence[1:]


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

						testmod()