



"""simple docstring"""






import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
	import torch

if is_soundfile_availble():
	import soundfile as sf

if is_vision_available():
	from PIL import Image


def     _lowercase       (						__snake_case=""			)		->     Union[str, Any]:
			__lowerCAmelCase				= tempfile.mkdtemp()
			return os.path.join(lowerCamelCase_      ,str(uuid.uuida()			) + suffix			)



@require_soundfile
@require_torch
class     A__     (						unittest.TestCase							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase				= torch.rand(12 ,    dtype=torch.floataa) - 0.5
				__lowerCAmelCase				= AgentAudio(lowerCamelCase_)
				__lowerCAmelCase				= str(agent_type.to_string())

				# Ensure that the tensor and the agent_type's tensor are the same
				self.assertTrue(torch.allclose(lowerCamelCase_ ,    agent_type.to_raw() ,    atol=1e-4))

				del agent_type

				# Ensure the path remains even after the object deletion
				self.assertTrue(os.path.exists(lowerCamelCase_))

				# Ensure that the file contains the same value as the original tensor
				__lowerCAmelCase				= sf.read(lowerCamelCase_)
				self.assertTrue(torch.allclose(lowerCamelCase_ ,    torch.tensor(lowerCamelCase_) ,    atol=1e-4))







	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> Dict:

				"""simple docstring"""

				__lowerCAmelCase				= torch.rand(12 ,    dtype=torch.floataa) - 0.5
				__lowerCAmelCase				= get_new_path(suffix=".wav")
				sf.write(lowerCamelCase_ ,    lowerCamelCase_ ,    1_6000)

				__lowerCAmelCase				= AgentAudio(lowerCamelCase_)

				self.assertTrue(torch.allclose(lowerCamelCase_ ,    agent_type.to_raw() ,    atol=1e-4))
				self.assertEqual(agent_type.to_string() ,    lowerCamelCase_)






@require_vision
@require_torch
class     A__     (						unittest.TestCase							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE     (  self:	List[str])       -> Tuple:

				"""simple docstring"""

				__lowerCAmelCase				= torch.randint(0 ,    256 ,    (64, 64, 3))
				__lowerCAmelCase				= AgentImage(lowerCamelCase_)
				__lowerCAmelCase				= str(agent_type.to_string())

				# Ensure that the tensor and the agent_type's tensor are the same
				self.assertTrue(torch.allclose(lowerCamelCase_ ,    agent_type._tensor ,    atol=1e-4))

				self.assertIsInstance(agent_type.to_raw() ,    Image.Image)

				# Ensure the path remains even after the object deletion
				del agent_type
				self.assertTrue(os.path.exists(lowerCamelCase_))

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

				"""simple docstring"""

				__lowerCAmelCase				= Path(get_tests_dir("fixtures/tests_samples/COCO")) / """000000039769.png"""
				__lowerCAmelCase				= Image.open(lowerCamelCase_)
				__lowerCAmelCase				= AgentImage(lowerCamelCase_)

				self.assertTrue(path.samefile(agent_type.to_string()))
				self.assertTrue(image == agent_type.to_raw())

				# Ensure the path remains even after the object deletion
				del agent_type
				self.assertTrue(os.path.exists(lowerCamelCase_))







	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase				= Path(get_tests_dir("fixtures/tests_samples/COCO")) / """000000039769.png"""
				__lowerCAmelCase				= Image.open(lowerCamelCase_)
				__lowerCAmelCase				= AgentImage(lowerCamelCase_)

				self.assertFalse(path.samefile(agent_type.to_string()))
				self.assertTrue(image == agent_type.to_raw())

				# Ensure the path remains even after the object deletion
				del agent_type
				self.assertTrue(os.path.exists(lowerCamelCase_))






class     A__     (						unittest.TestCase							):




	'''simple docstring'''





	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any])       -> Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase				= """Hey!"""
				__lowerCAmelCase				= AgentText(lowerCamelCase_)

				self.assertEqual(lowerCamelCase_ ,    agent_type.to_string())
				self.assertEqual(lowerCamelCase_ ,    agent_type.to_raw())
				self.assertEqual(lowerCamelCase_ ,    lowerCamelCase_)




"""simple docstring"""






import string
from math import logaa


def     _lowercase       (						__snake_case      ,__snake_case			)		->     int:
			__lowerCAmelCase   :						int				= document.translate(
			    str.maketrans(""      ,""      ,string.punctuation			)			).replace("\n"      ,""			)
			__lowerCAmelCase   :						Dict				= document_without_punctuation.split(" "			)  # word tokenization
			return len([word for word in tokenize_document if word.lower() == term.lower()]			)


def     _lowercase       (						__snake_case      ,__snake_case			)		->     tuple[int, int]:
			__lowerCAmelCase   :						Optional[Any]				= corpus.lower().translate(
			    str.maketrans(""      ,""      ,string.punctuation			)			)  # strip all punctuation and replace it with ''
			__lowerCAmelCase   :						List[str]				= corpus_without_punctuation.split("\n"			)
			__lowerCAmelCase   :						str				= term.lower()
			return (len([doc for doc in docs if term in doc]			), len(__snake_case			))


def     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case=False			)		->     float:
			if smoothing:
						if n == 0:
									raise ValueError("log10(0) is undefined."			)
						return round(1 + logaa(n / (1 + df)			)      ,3			)

			if df == 0:
						raise ZeroDivisionError("df must be > 0"			)
			elif n == 0:
						raise ValueError("log10(0) is undefined."			)
			return round(logaa(n / df			)      ,3			)





def     _lowercase       (						__snake_case      ,__snake_case			)		->     float:
			return round(tf * idf      ,3			)