






from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
							import torch

if is_vision_available():
							from PIL import Image


__UpperCamelCase					:		Optional[Any]	  =						["""text""", """image""", """audio"""]
def      a_ (      _A  )			->			List[str]:







				"""simple docstring"""
				snake_case__									=     []

				for input_type in input_types:
								if input_type == "text":
												inputs.append('Text input'  )
								elif input_type == "image":
												inputs.append(
												    Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO'  )  ) / '000000039769.png'  ).resize((512, 512)  )  )
								elif input_type == "audio":
												inputs.append(torch.ones(3000  )  )
								elif isinstance(_A      ,   _A  ):
												inputs.append(create_inputs(_A  )  )
								else:
												raise ValueError(f'''Invalid type requested: {input_type}'''  )

				return inputs
def      a_ (      _A  )			->			Dict:







				"""simple docstring"""
				snake_case__									=     []

				for output in outputs:
								if isinstance(_A      ,   (str, AgentText)  ):
												output_types.append('text'  )
								elif isinstance(_A      ,   (Image.Image, AgentImage)  ):
												output_types.append('image'  )
								elif isinstance(_A      ,   (torch.Tensor, AgentAudio)  ):
												output_types.append('audio'  )
								else:
												raise ValueError(f'''Invalid output: {output}'''  )

				return output_types


@is_tool_test
class   __SCREAMING_SNAKE_CASE:
							def lowerCAmelCase_ (     self:      Tuple						)		->		List[Any]:
											self.assertTrue(hasattr(self.tool       ,	'inputs'						)						)
											self.assertTrue(hasattr(self.tool       ,	'outputs'						)						)

											snake_case__									=     self.tool.inputs
											for _input in inputs:
															if isinstance(_input       ,	UpperCamelCase						):
																			for __input in _input:
																							self.assertTrue(__input in authorized_types						)
															else:
																			self.assertTrue(_input in authorized_types						)

											snake_case__									=     self.tool.outputs
											for _output in outputs:
															self.assertTrue(_output in authorized_types						)
							def lowerCAmelCase_ (     self:      List[Any]						)		->		int:
											snake_case__									=     create_inputs(self.tool.inputs						)
											snake_case__									=     self.tool(*UpperCamelCase						)

											# There is a single output
											if len(self.tool.outputs						) == 1:
															snake_case__									=     [outputs]

											self.assertListEqual(output_types(UpperCamelCase						)       ,	self.tool.outputs						)
							def lowerCAmelCase_ (     self:      int						)		->		int:
											self.assertTrue(hasattr(self.tool       ,	'description'						)						)
											self.assertTrue(hasattr(self.tool       ,	'default_checkpoint'						)						)
											self.assertTrue(self.tool.description.startswith('This is a tool that'						)						)
							def lowerCAmelCase_ (     self:      Dict						)		->		List[str]:
											snake_case__									=     create_inputs(self.tool.inputs						)
											snake_case__									=     self.tool(*UpperCamelCase						)

											if not isinstance(UpperCamelCase       ,	UpperCamelCase						):
															snake_case__									=     [outputs]

											self.assertEqual(len(UpperCamelCase						)       ,	len(self.tool.outputs						)						)

											for output, output_type in zip(UpperCamelCase       ,	self.tool.outputs						):
															snake_case__									=     AGENT_TYPE_MAPPING[output_type]
															self.assertTrue(isinstance(UpperCamelCase       ,	UpperCamelCase						)						)


							def lowerCAmelCase_ (     self:      Dict						)		->		Optional[int]:
											snake_case__									=     create_inputs(self.tool.inputs						)

											snake_case__									=     []

											for _input, input_type in zip(UpperCamelCase       ,	self.tool.inputs						):
															if isinstance(UpperCamelCase       ,	UpperCamelCase						):
																			_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input						) for _input_type in input_type]						)
															else:
																			_inputs.append(AGENT_TYPE_MAPPING[input_type](_input						)						)

        # Should not raise an error
											snake_case__									=     self.tool(*UpperCamelCase						)

											if not isinstance(UpperCamelCase       ,	UpperCamelCase						):
															snake_case__									=     [outputs]

											self.assertEqual(len(UpperCamelCase						)       ,	len(self.tool.outputs						)						)












__UpperCamelCase					:		List[str]	  =						256
# Modulus to hash a string
__UpperCamelCase					:		int	  =						1000003
def      a_ (      _A      ,   _A  )			->			bool:







				"""simple docstring"""
				snake_case__									=     len(_A  )
				snake_case__									=     len(_A  )
				if p_len > t_len:
								return False

				snake_case__									=     0
				snake_case__									=     0
				snake_case__									=     1

				# Calculating the hash of pattern and substring of text
				for i in range(_A  ):
								snake_case__									=     (ord(pattern[i]  ) + p_hash * alphabet_size) % modulus
								snake_case__									=     (ord(text[i]  ) + text_hash * alphabet_size) % modulus
								if i == p_len - 1:
												continue
								snake_case__									=     (modulus_power * alphabet_size) % modulus

				for i in range(0      ,   t_len - p_len + 1  ):
								if text_hash == p_hash and text[i : i + p_len] == pattern:
												return True
								if i == t_len - p_len:
												continue
								# Calculate the https://en.wikipedia.org/wiki/Rolling_hash
								snake_case__									=     (
								    (text_hash - ord(text[i]  ) * modulus_power) * alphabet_size
								    + ord(text[i + p_len]  )
								) % modulus
				return False
def      a_ (      )			->			None:







				"""simple docstring"""
				snake_case__									=     'abc1abc12'
				snake_case__									=     'alskfjaldsabc1abc1abc12k23adsfabcabc'
				snake_case__									=     'alskfjaldsk23adsfabcabc'
				assert rabin_karp(_A      ,   _A  ) and not rabin_karp(_A      ,   _A  )

				# Test 2)
				snake_case__									=     'ABABX'
				snake_case__									=     'ABABZABABYABABX'
				assert rabin_karp(_A      ,   _A  )

				# Test 3)
				snake_case__									=     'AAAB'
				snake_case__									=     'ABAAAAAB'
				assert rabin_karp(_A      ,   _A  )

				# Test 4)
				snake_case__									=     'abcdabcy'
				snake_case__									=     'abcxabcdabxabcdabcdabcy'
				assert rabin_karp(_A      ,   _A  )

				# Test 5)
				snake_case__									=     'Lü'
				snake_case__									=     'Lüsai'
				assert rabin_karp(_A      ,   _A  )
				snake_case__									=     'Lue'
				assert not rabin_karp(_A      ,   _A  )
				print('Success.'  )


if __name__ == "__main__":
							test_rabin_karp()




