






import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
							from PIL import Image

							from transformers import (
							    AutoProcessor,
							    BertTokenizerFast,
							    BlipImageProcessor,
							    GPTaTokenizer,
							    InstructBlipProcessor,
							    PreTrainedTokenizerFast,
							)




@require_vision
class 		UpperCAmelCase_						(	unittest.TestCase					):


						'''simple docstring'''




						def       _lowerCAmelCase       (	self				) ->				int:
								snake_case_				:							str						 =       tempfile.mkdtemp()

								snake_case_				:							str						 =       BlipImageProcessor()
								snake_case_				:							List[Any]						 =       GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model"				)
								snake_case_				:							List[Any]						 =       BertTokenizerFast.from_pretrained("hf-internal-testing/tiny-random-bert"				)

								snake_case_				:							Dict						 =       InstructBlipProcessor(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)

								processor.save_pretrained(self.tmpdirname				)






						def       _lowerCAmelCase       (	self		,				**_SCREAMING_SNAKE_CASE				) ->				List[Any]:
								return AutoProcessor.from_pretrained(self.tmpdirname		,				**_SCREAMING_SNAKE_CASE				).tokenizer






						def       _lowerCAmelCase       (	self		,				**_SCREAMING_SNAKE_CASE				) ->				str:
								return AutoProcessor.from_pretrained(self.tmpdirname		,				**_SCREAMING_SNAKE_CASE				).image_processor






						def       _lowerCAmelCase       (	self		,				**_SCREAMING_SNAKE_CASE				) ->				Optional[Any]:
								return AutoProcessor.from_pretrained(self.tmpdirname		,				**_SCREAMING_SNAKE_CASE				).qformer_tokenizer






						def       _lowerCAmelCase       (	self				) ->				List[str]:
								shutil.rmtree(self.tmpdirname				)






						def       _lowerCAmelCase       (	self				) ->				str:
								snake_case_				:							int						 =       [np.random.randint(255		,				size=(3, 30, 400)		,				dtype=np.uinta				)]

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

								return image_inputs






						def       _lowerCAmelCase       (	self				) ->				Union[str, Any]:
								snake_case_				:							Any						 =       InstructBlipProcessor(
								    tokenizer=self.get_tokenizer()		,				image_processor=self.get_image_processor()		,				qformer_tokenizer=self.get_qformer_tokenizer()		,				)
								processor.save_pretrained(self.tmpdirname				)

								snake_case_				:							Tuple						 =       self.get_tokenizer(bos_token="(BOS)"		,				eos_token="(EOS)"				)
								snake_case_				:							List[Any]						 =       self.get_image_processor(do_normalize=_SCREAMING_SNAKE_CASE		,				padding_value=1.0				)

								snake_case_				:							Union[str, Any]						 =       InstructBlipProcessor.from_pretrained(
								    self.tmpdirname		,				bos_token="(BOS)"		,				eos_token="(EOS)"		,				do_normalize=_SCREAMING_SNAKE_CASE		,				padding_value=1.0				)

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

								self.assertEqual(processor.image_processor.to_json_string()		,				image_processor_add_kwargs.to_json_string()				)
								self.assertIsInstance(processor.image_processor		,				_SCREAMING_SNAKE_CASE				)
								self.assertIsInstance(processor.qformer_tokenizer		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				List[Any]:
								snake_case_				:							Any						 =       self.get_image_processor()
								snake_case_				:							Any						 =       self.get_tokenizer()
								snake_case_				:							Tuple						 =       self.get_qformer_tokenizer()

								snake_case_				:							List[Any]						 =       InstructBlipProcessor(
								    tokenizer=_SCREAMING_SNAKE_CASE		,				image_processor=_SCREAMING_SNAKE_CASE		,				qformer_tokenizer=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							List[Any]						 =       self.prepare_image_inputs()

								snake_case_				:							Dict						 =       image_processor(_SCREAMING_SNAKE_CASE		,				return_tensors="np"				)
								snake_case_				:							List[str]						 =       processor(images=_SCREAMING_SNAKE_CASE		,				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       _lowerCAmelCase       (	self				) ->				Optional[Any]:
								snake_case_				:							Dict						 =       self.get_image_processor()
								snake_case_				:							List[str]						 =       self.get_tokenizer()
								snake_case_				:							Any						 =       self.get_qformer_tokenizer()

								snake_case_				:							Optional[Any]						 =       InstructBlipProcessor(
								    tokenizer=_SCREAMING_SNAKE_CASE		,				image_processor=_SCREAMING_SNAKE_CASE		,				qformer_tokenizer=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							Union[str, Any]						 =       "lower newer"

								snake_case_				:							List[str]						 =       processor(text=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							Optional[Any]						 =       tokenizer(_SCREAMING_SNAKE_CASE		,				return_token_type_ids=_SCREAMING_SNAKE_CASE				)
								snake_case_				:							str						 =       qformer_tokenizer(_SCREAMING_SNAKE_CASE		,				return_token_type_ids=_SCREAMING_SNAKE_CASE				)

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

								for key in encoded_tokens_qformer.keys():
										self.assertListEqual(encoded_tokens_qformer[key]		,				encoded_processor["qformer_" + key]				)






						def       _lowerCAmelCase       (	self				) ->				str:
								snake_case_				:							List[Any]						 =       self.get_image_processor()
								snake_case_				:							List[Any]						 =       self.get_tokenizer()
								snake_case_				:							Any						 =       self.get_qformer_tokenizer()

								snake_case_				:							Dict						 =       InstructBlipProcessor(
								    tokenizer=_SCREAMING_SNAKE_CASE		,				image_processor=_SCREAMING_SNAKE_CASE		,				qformer_tokenizer=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							List[Any]						 =       "lower newer"
								snake_case_				:							Optional[int]						 =       self.prepare_image_inputs()

								snake_case_				:							List[str]						 =       processor(text=_SCREAMING_SNAKE_CASE		,				images=_SCREAMING_SNAKE_CASE				)

								self.assertListEqual(
								    list(inputs.keys()				)		,				["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]		,				)

								# test if it raises when no input is passed
								with pytest.raises(_SCREAMING_SNAKE_CASE				):
										processor()






						def       _lowerCAmelCase       (	self				) ->				Dict:
								snake_case_				:							Union[str, Any]						 =       self.get_image_processor()
								snake_case_				:							Union[str, Any]						 =       self.get_tokenizer()
								snake_case_				:							Any						 =       self.get_qformer_tokenizer()

								snake_case_				:							Any						 =       InstructBlipProcessor(
								    tokenizer=_SCREAMING_SNAKE_CASE		,				image_processor=_SCREAMING_SNAKE_CASE		,				qformer_tokenizer=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							Optional[int]						 =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								snake_case_				:							str						 =       processor.batch_decode(_SCREAMING_SNAKE_CASE				)
								snake_case_				:							Dict						 =       tokenizer.batch_decode(_SCREAMING_SNAKE_CASE				)

								self.assertListEqual(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)






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

								snake_case_				:							List[Any]						 =       InstructBlipProcessor(
								    tokenizer=_SCREAMING_SNAKE_CASE		,				image_processor=_SCREAMING_SNAKE_CASE		,				qformer_tokenizer=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							Optional[Any]						 =       "lower newer"
								snake_case_				:							Union[str, Any]						 =       self.prepare_image_inputs()

								snake_case_				:							Dict						 =       processor(text=_SCREAMING_SNAKE_CASE		,				images=_SCREAMING_SNAKE_CASE				)

								self.assertListEqual(
								    list(inputs.keys()				)		,				["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]		,				)








def      lowerCAmelCase__	(    _a       :			int    ):
		if num < 0:
				return False

		snake_case_				:							int						 =       num
		snake_case_				:							int						 =       0
		while num > 0:
				snake_case_				:							Union[str, Any]						 =       rev_num * 10 + (num % 10)
				num //= 10

		return num_copy == rev_num


if __name__ == "__main__":
							import doctest

							doctest.testmod()
