


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


A			:						Tuple        =  ['text', 'image', 'audio']






def 					UpperCamelCase   (      __magic_name__	:				List[str]	)  ->    Optional[Any]:
		"""simple docstring"""




		lowercase__	     =						[]

		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(__magic_name__       ,       __magic_name__	):
						inputs.append(create_inputs(__magic_name__	)	)
				else:
						raise ValueError(f'''Invalid type requested: {input_type}'''	)

		return inputs






def 					UpperCamelCase   (      __magic_name__	:				List	)  ->    Tuple:
		"""simple docstring"""




		lowercase__	     =						[]

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

		return output_types







@is_tool_test
class 				A       :
					'''simple docstring'''






					def     lowerCamelCase__	(self       :		List[Any]						)		->  Union[str, Any]:




							"""simple docstring"""


							self.assertTrue(hasattr(self.tool ,   """inputs"""						)						)
							self.assertTrue(hasattr(self.tool ,   """outputs"""						)						)

							lowercase__	     =						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						)

							lowercase__	     =						self.tool.outputs
							for _output in outputs:
									self.assertTrue(_output in authorized_types						)

					def     lowerCamelCase__	(self       :		List[Any]						)		->  int:




							"""simple docstring"""


							lowercase__	     =						create_inputs(self.tool.inputs						)
							lowercase__	     =						self.tool(*_UpperCAmelCase						)

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

							self.assertListEqual(output_types(_UpperCAmelCase						) ,   self.tool.outputs						)

					def     lowerCamelCase__	(self       :		Any						)		->  Any:




							"""simple docstring"""


							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       :		Optional[int]						)		->  List[str]:




							"""simple docstring"""


							lowercase__	     =						create_inputs(self.tool.inputs						)
							lowercase__	     =						self.tool(*_UpperCAmelCase						)

							if not isinstance(_UpperCAmelCase ,   _UpperCAmelCase						):
									lowercase__	     =						[outputs]

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

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


					def     lowerCamelCase__	(self       :		List[Any]						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__	     =						create_inputs(self.tool.inputs						)

							lowercase__	     =						[]

							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
							lowercase__	     =						self.tool(*_UpperCAmelCase						)

							if not isinstance(_UpperCAmelCase ,   _UpperCAmelCase						):
									lowercase__	     =						[outputs]

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







'''simple docstring'''


from collections import defaultdict
def 						lowerCamelCase__   (				a    ,	a							):
						__snake_case						 =   first_str.lower().strip()
						__snake_case						 =   second_str.lower().strip()

						# Remove whitespace
						__snake_case						 =   first_str.replace(' '    ,	''							)
						__snake_case						 =   second_str.replace(' '    ,	''							)

						# Strings of different lengths are not anagrams
						if len(a							) != len(a							):
												return False

						# Default values for count should be 0
						__snake_case						 =   defaultdict(a							)

						# For each character in input strings,
						# increment count in the corresponding
						for i in range(len(a							)							):
												count[first_str[i]] += 1
												count[second_str[i]] -= 1

						return all(_count == 0 for _count in count.values()							)


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	_lowercase  =			input("""Enter the first string """).strip()
	_lowercase  =			input("""Enter the second string """).strip()

	_lowercase  =			check_anagrams(input_a, input_b)
	print(f'''{input_a} and {input_b} are {'' if status else 'not '}anagrams.''')

