





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=""   ):
   a__	:						Any      		=  tempfile.mkdtemp()
   return os.path.join(lowerCamelCase							, str(uuid.uuida()   ) + suffix   )







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





   def 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      a__	:						Optional[int]      		=  torch.rand(12					,			dtype=torch.floataa      ) - 0.5
      a__	:						int      		=  AgentAudio(snake_case      )
      a__	:						int      		=  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
      a__		,     a__	:						List[str]      		=  sf.read(snake_case      )
      self.assertTrue(torch.allclose(snake_case					,			torch.tensor(snake_case      )					,			atol=1E-4      )      )





   def 	_snake_case ( self      )				->  Optional[Any]:
      """simple docstring"""





      a__	:						List[str]      		=  torch.rand(12					,			dtype=torch.floataa      ) - 0.5
      a__	:						Any      		=  get_new_path(suffix=".wav"      )
      sf.write(snake_case					,			snake_case					,			16_000      )

      a__	:						Dict      		=  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   __lowerCAmelCase			(					unittest.TestCase  ):





   def 	_snake_case ( self      )				->  Optional[Any]:
      """simple docstring"""





      a__	:						Any      		=  torch.randint(0					,			256					,			(64, 64, 3)      )
      a__	:						int      		=  AgentImage(snake_case      )
      a__	:						Union[str, Any]      		=  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 	_snake_case ( self      )				->  Dict:
      """simple docstring"""





      a__	:						Dict      		=  Path(get_tests_dir("fixtures/tests_samples/COCO"      )      ) / "000000039769.png"
      a__	:						str      		=  Image.open(snake_case      )
      a__	:						Any      		=  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 	_snake_case ( self      )				->  str:
      """simple docstring"""





      a__	:						Optional[int]      		=  Path(get_tests_dir("fixtures/tests_samples/COCO"      )      ) / "000000039769.png"
      a__	:						List[Any]      		=  Image.open(snake_case      )
      a__	:						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   __lowerCAmelCase			(					unittest.TestCase  ):





   def 	_snake_case ( self      )				->  List[Any]:
      """simple docstring"""





      a__	:						List[str]      		=  "Hey!"
      a__	:						Dict      		=  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 tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


SCREAMING_SNAKE_CASE__       :			List[Any]			      =						"""sshleifer/bart-tiny-random"""
SCREAMING_SNAKE_CASE__       :			Tuple			      =						"""patrickvonplaten/t5-tiny-random"""







@require_torch
class   __lowerCAmelCase			(					unittest.TestCase  ):





   @cached_property
   def 	_snake_case ( self      )				->  List[Any]:
      """simple docstring"""





      return AutoConfig.from_pretrained(snake_case      )





   def 	_snake_case ( self      )				->  Any:
      """simple docstring"""





      a__		,     *a__	:						int      		=  create_student_by_copying_alternating_layers(snake_case					,			tempfile.mkdtemp()					,			e=1					,			d=1      )
      self.assertEqual(student.config.num_hidden_layers					,			1      )





   def 	_snake_case ( self      )				->  str:
      """simple docstring"""





      a__		,     *a__	:						int      		=  create_student_by_copying_alternating_layers(snake_case					,			tempfile.mkdtemp()					,			e=1					,			d=snake_case      )





   def 	_snake_case ( self      )				->  List[str]:
      """simple docstring"""





      a__		,     *a__	:						Any      		=  create_student_by_copying_alternating_layers(snake_case					,			tempfile.mkdtemp()					,			e=1					,			d=snake_case      )
      self.assertEqual(student.config.encoder_layers					,			1      )
      self.assertEqual(student.config.decoder_layers					,			self.teacher_config.encoder_layers      )





   def 	_snake_case ( self      )				->  Optional[int]:
      """simple docstring"""





      a__		,     *a__	:						List[str]      		=  create_student_by_copying_alternating_layers(snake_case					,			tempfile.mkdtemp()					,			e=1					,			d=1      )
      self.assertEqual(student.config.encoder_layers					,			1      )
      self.assertEqual(student.config.decoder_layers					,			1      )





   def 	_snake_case ( self      )				->  int:
      """simple docstring"""





      with self.assertRaises(snake_case      ):
         create_student_by_copying_alternating_layers(snake_case					,			tempfile.mkdtemp()					,			e=snake_case					,			d=snake_case      )

