"""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,
				    BertTokenizerFast,
				    BlipImageProcessor,
				    GPTaTokenizer,
				    InstructBlipProcessor,
				    PreTrainedTokenizerFast,
				)
@require_vision
class 						__UpperCAmelCase    (unittest.TestCase     ):







			'''simple docstring'''





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			tempfile.mkdtemp()

										A__       :     Any								=			BlipImageProcessor()
										A__       :     Tuple								=			GPTaTokenizer.from_pretrained("""hf-internal-testing/tiny-random-GPT2Model"""							)
										A__       :     Optional[Any]								=			BertTokenizerFast.from_pretrained("""hf-internal-testing/tiny-random-bert"""							)

										A__       :     int								=			InstructBlipProcessor(snake_case_   ,      snake_case_   ,      snake_case_							)

										processor.save_pretrained(self.tmpdirname							)





			def 		lowerCamelCase					(			self   ,      **snake_case_							):







										'''simple docstring'''


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





			def 		lowerCamelCase					(			self   ,      **snake_case_							):







										'''simple docstring'''


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





			def 		lowerCamelCase					(			self   ,      **snake_case_							):







										'''simple docstring'''


										return AutoProcessor.from_pretrained(self.tmpdirname   ,      **snake_case_							).qformer_tokenizer





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										shutil.rmtree(self.tmpdirname							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


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

										A__       :     Optional[Any]								=			[Image.fromarray(np.moveaxis(snake_case_   ,      0   ,      -1							)							) for x in image_inputs]

										return image_inputs





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			InstructBlipProcessor(
										    tokenizer=self.get_tokenizer()   ,      image_processor=self.get_image_processor()   ,      qformer_tokenizer=self.get_qformer_tokenizer()   ,      )
										processor.save_pretrained(self.tmpdirname							)

										A__       :     Optional[int]								=			self.get_tokenizer(bos_token="""(BOS)"""   ,      eos_token="""(EOS)"""							)
										A__       :     Dict								=			self.get_image_processor(do_normalize=snake_case_   ,      padding_value=1.0							)

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

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

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





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     str								=			self.get_image_processor()
										A__       :     Dict								=			self.get_tokenizer()
										A__       :     int								=			self.get_qformer_tokenizer()

										A__       :     Tuple								=			InstructBlipProcessor(
										    tokenizer=snake_case_   ,      image_processor=snake_case_   ,      qformer_tokenizer=snake_case_							)

										A__       :     Any								=			self.prepare_image_inputs()

										A__       :     Any								=			image_processor(snake_case_   ,      return_tensors="""np"""							)
										A__       :     int								=			processor(images=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							):







										'''simple docstring'''


										A__       :     Tuple								=			self.get_image_processor()
										A__       :     int								=			self.get_tokenizer()
										A__       :     Dict								=			self.get_qformer_tokenizer()

										A__       :     Union[str, Any]								=			InstructBlipProcessor(
										    tokenizer=snake_case_   ,      image_processor=snake_case_   ,      qformer_tokenizer=snake_case_							)

										A__       :     Optional[Any]								=			"""lower newer"""

										A__       :     Dict								=			processor(text=snake_case_							)

										A__       :     Any								=			tokenizer(snake_case_   ,      return_token_type_ids=snake_case_							)
										A__       :     Optional[int]								=			qformer_tokenizer(snake_case_   ,      return_token_type_ids=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							):







										'''simple docstring'''


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

										A__       :     List[str]								=			InstructBlipProcessor(
										    tokenizer=snake_case_   ,      image_processor=snake_case_   ,      qformer_tokenizer=snake_case_							)

										A__       :     List[str]								=			"""lower newer"""
										A__       :     Any								=			self.prepare_image_inputs()

										A__       :     Optional[int]								=			processor(text=snake_case_   ,      images=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(snake_case_							):
																	processor()





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Union[str, Any]								=			self.get_image_processor()
										A__       :     int								=			self.get_tokenizer()
										A__       :     Any								=			self.get_qformer_tokenizer()

										A__       :     Union[str, Any]								=			InstructBlipProcessor(
										    tokenizer=snake_case_   ,      image_processor=snake_case_   ,      qformer_tokenizer=snake_case_							)

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

										A__       :     List[Any]								=			processor.batch_decode(snake_case_							)
										A__       :     List[Any]								=			tokenizer.batch_decode(snake_case_							)

										self.assertListEqual(snake_case_   ,      snake_case_							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Tuple								=			self.get_image_processor()
										A__       :     str								=			self.get_tokenizer()
										A__       :     List[Any]								=			self.get_qformer_tokenizer()

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

										A__       :     Dict								=			"""lower newer"""
										A__       :     Dict								=			self.prepare_image_inputs()

										A__       :     Optional[Any]								=			processor(text=snake_case_   ,      images=snake_case_							)

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






"""simple docstring"""



from collections.abc import Sequence

def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase							)							)

def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							A__       :     str								=			0.0
							for coeff in reversed(lowerCAmelCase							):
														A__       :     Optional[int]								=			result * x + coeff
							return result


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





