


'''simple docstring'''
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, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast

@require_vision
class 						_lowerCamelCase					(    unittest.TestCase				):




	'''simple docstring'''


	def  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		str       =			tempfile.mkdtemp()

		__A  :		Tuple       =			BlipImageProcessor()
		__A  :		Union[str, Any]       =			BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-BertModel'						)

		__A  :		Optional[int]       =			BlipProcessor(lowerCamelCase__      ,      lowerCamelCase__						)

		processor.save_pretrained(self.tmpdirname						)


	def  snake_case__   (      self      ,      **__lowercase						):

		"""simple docstring"""







		return AutoProcessor.from_pretrained(self.tmpdirname      ,      **lowerCamelCase__						).tokenizer


	def  snake_case__   (      self      ,      **__lowercase						):

		"""simple docstring"""







		return AutoProcessor.from_pretrained(self.tmpdirname      ,      **lowerCamelCase__						).image_processor


	def  snake_case__   (      self						):

		"""simple docstring"""







		shutil.rmtree(self.tmpdirname						)


	def  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		str       =			[np.random.randint(255      ,      size=(3, 30, 400)      ,      dtype=np.uinta						)]

		__A  :		List[Any]       =			[Image.fromarray(np.moveaxis(lowerCamelCase__      ,      0      ,      -1						)						) for x in image_inputs]

		return image_inputs


	def  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		Optional[Any]       =			BlipProcessor(tokenizer=self.get_tokenizer()      ,      image_processor=self.get_image_processor()						)
		processor.save_pretrained(self.tmpdirname						)

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

		__A  :		int       =			BlipProcessor.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  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		int       =			self.get_image_processor()
		__A  :		int       =			self.get_tokenizer()

		__A  :		Any       =			BlipProcessor(tokenizer=lowerCamelCase__      ,      image_processor=lowerCamelCase__						)

		__A  :		str       =			self.prepare_image_inputs()

		__A  :		str       =			image_processor(lowerCamelCase__      ,      return_tensors='np'						)
		__A  :		Dict       =			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						):

		"""simple docstring"""







		__A  :		List[str]       =			self.get_image_processor()
		__A  :		str       =			self.get_tokenizer()

		__A  :		List[Any]       =			BlipProcessor(tokenizer=lowerCamelCase__      ,      image_processor=lowerCamelCase__						)

		__A  :		Tuple       =			"lower newer"

		__A  :		str       =			processor(text=lowerCamelCase__						)

		__A  :		int       =			tokenizer(lowerCamelCase__      ,      return_token_type_ids=lowerCamelCase__						)

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


	def  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		Any       =			self.get_image_processor()
		__A  :		Any       =			self.get_tokenizer()

		__A  :		Tuple       =			BlipProcessor(tokenizer=lowerCamelCase__      ,      image_processor=lowerCamelCase__						)

		__A  :		Tuple       =			"lower newer"
		__A  :		Any       =			self.prepare_image_inputs()

		__A  :		Dict       =			processor(text=lowerCamelCase__      ,      images=lowerCamelCase__						)

		self.assertListEqual(list(inputs.keys()						)      ,      ['pixel_values', 'input_ids', 'attention_mask']						)

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


	def  snake_case__   (      self						):

		"""simple docstring"""







		__A  :		Union[str, Any]       =			self.get_image_processor()
		__A  :		List[Any]       =			self.get_tokenizer()

		__A  :		Optional[int]       =			BlipProcessor(tokenizer=lowerCamelCase__      ,      image_processor=lowerCamelCase__						)

		__A  :		str       =			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

		__A  :		List[Any]       =			processor.batch_decode(lowerCamelCase__						)
		__A  :		Optional[int]       =			tokenizer.batch_decode(lowerCamelCase__						)

		self.assertListEqual(lowerCamelCase__      ,      lowerCamelCase__						)







	def  snake_case__   (      self						):

		"""simple docstring"""







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

		__A  :		Union[str, Any]       =			BlipProcessor(tokenizer=lowerCamelCase__      ,      image_processor=lowerCamelCase__						)

		__A  :		Optional[Any]       =			"lower newer"
		__A  :		Dict       =			self.prepare_image_inputs()

		__A  :		str       =			processor(text=lowerCamelCase__      ,      images=lowerCamelCase__						)

		# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
		self.assertListEqual(list(inputs.keys()						)      ,      ['pixel_values', 'input_ids', 'attention_mask']						)










'''simple docstring'''
from collections.abc import Sequence


def 			_lowercase       (				UpperCamelCase__       :					Sequence[float],				UpperCamelCase__       :					float			):
 return sum(c * (x**i) for i, c in enumerate(UpperCamelCase__			)			)


def 			_lowercase       (				UpperCamelCase__       :					Sequence[float],				UpperCamelCase__       :					float			):
 __A  :		Optional[Any]       =			0.0
 for coeff in reversed(UpperCamelCase__			):
  __A  :		List[str]       =			result * x + coeff
 return result


if __name__ == "__main__":
 UpperCAmelCase_ :     Any								=      (0.0, 0.0, 5.0, 9.3, 7.0)
 UpperCAmelCase_ :     Any								=      10.0
 print(evaluate_poly(poly, x))
 print(horner(poly, x))






