
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        A__					(						lowerCamelCase=""						)  ->	str:
				UpperCamelCase_:							List[str]	=						tempfile.mkdtemp()
				return os.path.join(lowerCamelCase     ,    str(uuid.uuida()						) + suffix						)

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






			'''simple docstring'''

			def       lowerCAmelCase__	(       self :       int      ):
							UpperCamelCase_:							Optional[int]	=						torch.rand(12						,	dtype=torch.floataa      ) - 0.5
							UpperCamelCase_:							List[Any]	=						AgentAudio(snake_case_      )
							UpperCamelCase_:							str	=						str(agent_type.to_string()      )

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

							del agent_type

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

							# Ensure that the file contains the same value as the original tensor
							UpperCamelCase_,   UpperCamelCase_:							Optional[Any]	=						sf.read(snake_case_      )
							self.assertTrue(torch.allclose(snake_case_						,	torch.tensor(snake_case_      )						,	atol=1e-4      )      )




			def       lowerCAmelCase__	(       self :       Optional[int]      ):
							UpperCamelCase_:							List[Any]	=						torch.rand(12						,	dtype=torch.floataa      ) - 0.5
							UpperCamelCase_:							Optional[Any]	=						get_new_path(suffix=""".wav"""      )
							sf.write(snake_case_						,	snake_case_						,	1_6000      )

							UpperCamelCase_:							Optional[Any]	=						AgentAudio(snake_case_      )

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




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






			'''simple docstring'''

			def       lowerCAmelCase__	(       self :       Any      ):
							UpperCamelCase_:							Any	=						torch.randint(0						,	256						,	(64, 64, 3)      )
							UpperCamelCase_:							Tuple	=						AgentImage(snake_case_      )
							UpperCamelCase_:							Dict	=						str(agent_type.to_string()      )

							# Ensure that the tensor and the agent_type's tensor are the same
							self.assertTrue(torch.allclose(snake_case_						,	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(snake_case_      )      )

			def       lowerCAmelCase__	(       self :       List[Any]      ):
							UpperCamelCase_:							Any	=						Path(get_tests_dir("""fixtures/tests_samples/COCO"""      )      ) / """000000039769.png"""
							UpperCamelCase_:							Dict	=						Image.open(snake_case_      )
							UpperCamelCase_:							List[str]	=						AgentImage(snake_case_      )

							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(snake_case_      )      )




			def       lowerCAmelCase__	(       self :       Union[str, Any]      ):
							UpperCamelCase_:							Optional[int]	=						Path(get_tests_dir("""fixtures/tests_samples/COCO"""      )      ) / """000000039769.png"""
							UpperCamelCase_:							List[Any]	=						Image.open(snake_case_      )
							UpperCamelCase_:							int	=						AgentImage(snake_case_      )

							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(snake_case_      )      )




class        _UpperCamelCase				(					unittest.TestCase  ):






			'''simple docstring'''

			def       lowerCAmelCase__	(       self :       Dict      ):
							UpperCamelCase_:							Optional[Any]	=						"""Hey!"""
							UpperCamelCase_:							int	=						AgentText(snake_case_      )

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








import warnings

from ..trainer import Trainer
from ..utils import logging


lowerCamelCase_						: Dict         =  logging.get_logger(__name__)

class        _UpperCamelCase				(					_A  ):






			'''simple docstring'''

			def __init__(       self :       List[str]						,	snake_case_ :       Tuple=None						,	**snake_case_ :       List[str]      ):
							warnings.warn(
							    """`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` """
							    """instead."""						,	snake_case_						,	)
							super().__init__(args=snake_case_						,	**snake_case_      )






