




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 			UpperCAmelCase_      (   unittest.TestCase       ):




							'''simple docstring'''



							def    _UpperCAmelCase     (					self       :	Any			)			->					Union[str, Any]:
										SCREAMING_SNAKE_CASE           =					tempfile.mkdtemp()

										SCREAMING_SNAKE_CASE           =					[
										    """[UNK]""",
										    """[CLS]""",
										    """[SEP]""",
										    """[PAD]""",
										    """[MASK]""",
										    """的""",
										    """价""",
										    """格""",
										    """是""",
										    """15""",
										    """便""",
										    """alex""",
										    """##andra""",
										    """，""",
										    """。""",
										    """-""",
										    """t""",
										    """shirt""",
										]
										SCREAMING_SNAKE_CASE           =					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           =					{
										    """do_resize""": True,
										    """size""": {"""height""": 224, """width""": 224},
										    """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           =					os.path.join(self.tmpdirname       ,     a			)
										with open(self.image_processor_file       ,     """w"""       ,     encoding="""utf-8"""			) as fp:
													json.dump(a       ,     a			)





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





							def    _UpperCAmelCase     (					self       :	Optional[Any]       ,     **a       :	Tuple			)			->					Tuple:
										return BertTokenizerFast.from_pretrained(self.tmpdirname       ,     **a			)





							def    _UpperCAmelCase     (					self       :	List[str]       ,     **a       :	str			)			->					Any:
										return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname       ,     **a			)





							def    _UpperCAmelCase     (					self       :	Dict			)			->					Any:
										shutil.rmtree(self.tmpdirname			)





							def    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					Any:
										SCREAMING_SNAKE_CASE           =					[np.random.randint(255       ,     size=(3, 30, 400)       ,     dtype=np.uinta			)]

										SCREAMING_SNAKE_CASE           =					[Image.fromarray(np.moveaxis(a       ,     0       ,     -1			)			) for x in image_inputs]

										return image_inputs





							def    _UpperCAmelCase     (					self       :	str			)			->					Dict:
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()
										SCREAMING_SNAKE_CASE           =					self.get_rust_tokenizer()
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)
										processor_slow.save_pretrained(self.tmpdirname			)
										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor.from_pretrained(self.tmpdirname       ,     use_fast=a			)

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)
										processor_fast.save_pretrained(self.tmpdirname			)
										SCREAMING_SNAKE_CASE           =					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       ,     a			)
										self.assertIsInstance(processor_fast.tokenizer       ,     a			)

										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       ,     a			)
										self.assertIsInstance(processor_fast.image_processor       ,     a			)





							def    _UpperCAmelCase     (					self       :	List[Any]			)			->					List[Any]:
										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=self.get_tokenizer()       ,     image_processor=self.get_image_processor()			)
										processor.save_pretrained(self.tmpdirname			)

										SCREAMING_SNAKE_CASE           =					self.get_tokenizer(cls_token="""(CLS)"""       ,     sep_token="""(SEP)"""			)
										SCREAMING_SNAKE_CASE           =					self.get_image_processor(do_normalize=a			)

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor.from_pretrained(
										    self.tmpdirname       ,     cls_token="""(CLS)"""       ,     sep_token="""(SEP)"""       ,     do_normalize=a			)

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

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





							def    _UpperCAmelCase     (					self       :	Dict			)			->					List[Any]:
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)

										SCREAMING_SNAKE_CASE           =					self.prepare_image_inputs()

										SCREAMING_SNAKE_CASE           =					image_processor(a       ,     return_tensors="""np"""			)
										SCREAMING_SNAKE_CASE           =					processor(images=a       ,     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    _UpperCAmelCase     (					self       :	str			)			->					Optional[Any]:
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)

										SCREAMING_SNAKE_CASE           =					"""Alexandra，T-shirt的价格是15便士。"""

										SCREAMING_SNAKE_CASE           =					processor(text=a			)

										SCREAMING_SNAKE_CASE           =					tokenizer(a			)

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





							def    _UpperCAmelCase     (					self       :	int			)			->					Optional[Any]:
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)

										SCREAMING_SNAKE_CASE           =					"""Alexandra，T-shirt的价格是15便士。"""
										SCREAMING_SNAKE_CASE           =					self.prepare_image_inputs()

										SCREAMING_SNAKE_CASE           =					processor(text=a       ,     images=a			)

										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(a			):
													processor()





							def    _UpperCAmelCase     (					self       :	Dict			)			->					Any:
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)

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

										SCREAMING_SNAKE_CASE           =					processor.batch_decode(a			)
										SCREAMING_SNAKE_CASE           =					tokenizer.batch_decode(a			)

										self.assertListEqual(a       ,     a			)







							def    _UpperCAmelCase     (					self       :	Union[str, Any]			)			->					int:
										SCREAMING_SNAKE_CASE           =					self.get_image_processor()
										SCREAMING_SNAKE_CASE           =					self.get_tokenizer()

										SCREAMING_SNAKE_CASE           =					ChineseCLIPProcessor(tokenizer=a       ,     image_processor=a			)

										SCREAMING_SNAKE_CASE           =					"""Alexandra，T-shirt的价格是15便士。"""
										SCREAMING_SNAKE_CASE           =					self.prepare_image_inputs()

										SCREAMING_SNAKE_CASE           =					processor(text=a       ,     images=a			)

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












from __future__ import annotations
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			create_state_space_tree(SCREAMING_SNAKE_CASE					,	[]					,	0					,	[0 for i in range(len(SCREAMING_SNAKE_CASE   )   )]   )
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	):
			'''simple docstring'''

			if index == len(SCREAMING_SNAKE_CASE   ):
						print(SCREAMING_SNAKE_CASE   )
						return

			for i in range(len(SCREAMING_SNAKE_CASE   )   ):
						if not index_used[i]:
									current_sequence.append(sequence[i]   )
									SCREAMING_SNAKE_CASE           =					True
									create_state_space_tree(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	index + 1					,	SCREAMING_SNAKE_CASE   )
									current_sequence.pop()
									SCREAMING_SNAKE_CASE           =					False
__A						:							list[int | str]							=  [3, 1, 2, 4]
generate_all_permutations(sequence)

__A						:							list[int | str]							=  ["A", "B", "C"]




generate_all_permutations(sequence_a)






