




'''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 		__magic_name__    (	__UpperCAmelCase=""	)		->					str:

					'''simple docstring'''

					snake_case_									=				tempfile.mkdtemp()
					return os.path.join(__UpperCAmelCase,      str(uuid.uuida()	) + suffix	)






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


				def   A_ (		self    :					int					):
									snake_case_									=				torch.rand(12       ,				dtype=torch.floataa					) - 0.5
									snake_case_									=				AgentAudio(lowercase_					)
									snake_case_									=				str(agent_type.to_string()					)

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

									del agent_type

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

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


				def   A_ (		self    :					Optional[int]					):
									snake_case_									=				torch.rand(12       ,				dtype=torch.floataa					) - 0.5
									snake_case_									=				get_new_path(suffix='''.wav'''					)
									sf.write(lowercase_       ,				lowercase_       ,				1_6000					)

									snake_case_									=				AgentAudio(lowercase_					)

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







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


				def   A_ (		self    :					List[Any]					):
									snake_case_									=				torch.randint(0       ,				256       ,				(64, 64, 3)					)
									snake_case_									=				AgentImage(lowercase_					)
									snake_case_									=				str(agent_type.to_string()					)

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


				def   A_ (		self    :					Tuple					):
									snake_case_									=				Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''
									snake_case_									=				Image.open(lowercase_					)
									snake_case_									=				AgentImage(lowercase_					)

									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(lowercase_					)					)


				def   A_ (		self    :					Dict					):
									snake_case_									=				Path(get_tests_dir('''fixtures/tests_samples/COCO'''					)					) / '''000000039769.png'''
									snake_case_									=				Image.open(lowercase_					)
									snake_case_									=				AgentImage(lowercase_					)

									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(lowercase_					)					)







class 						a				(   unittest.TestCase     ):


				def   A_ (		self    :					int					):
									snake_case_									=				'''Hey!'''
									snake_case_									=				AgentText(lowercase_					)

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








"""simple docstring"""




import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict


@dataclass
class        __UpperCamelCase				(						a__						):
							lowerCamelCase   :					List[str]      					=ComputeEnvironment.AMAZON_SAGEMAKER
							lowerCamelCase   :					str      					=True
							lowerCamelCase   :					Union[str, Any]      					="""ml.p3.2xlarge"""
							lowerCamelCase   :					str      					="""accelerate_sagemaker_execution_role"""
							lowerCamelCase   :					int      					="""hf-sm"""
							lowerCamelCase   :					int      					="""us-east-1"""
							lowerCamelCase   :					Tuple      					=1
							lowerCamelCase   :					Any      					="""accelerate-sagemaker-1"""
							lowerCamelCase   :					str      					="""1.6"""
							lowerCamelCase   :					Tuple      					="""4.4"""
							lowerCamelCase   :					Optional[int]      					="""train.py"""
							lowerCamelCase   :					Optional[Any]      					=[
							    """--model_name_or_path""",
							    """bert""",
							    """--do_train""",
							    """False""",
							    """--epochs""",
							    """3""",
							    """--learning_rate""",
							    """5e-5""",
							    """--max_steps""",
							    """50.5""",
							]
							lowerCamelCase   :					Union[str, Any]      					=[
							    """--model_name_or_path""",
							    """bert""",
							    """--do_train""",
							    """--do_test""",
							    """False""",
							    """--do_predict""",
							    """--epochs""",
							    """3""",
							    """--learning_rate""",
							    """5e-5""",
							    """--max_steps""",
							    """50.5""",
							]


class        __UpperCamelCase				(						unittest.TestCase						):






							def     __a   (   self      )	-> List[str]:
								# If no defaults are changed, `to_kwargs` returns an empty dict.
								a      :		str	=				_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args      )
								assert isinstance(converted_args["model_name_or_path"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["do_train"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["epochs"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["learning_rate"]      ,					lowerCAmelCase__      )
								assert isinstance(converted_args["max_steps"]      ,					lowerCAmelCase__      )

								with pytest.raises(lowerCAmelCase__      ):
									_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args      )


