


'''simple docstring'''

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


a_  :				List[str]						= """sshleifer/bart-tiny-random"""
a_  :				Union[str, Any]						= """patrickvonplaten/t5-tiny-random"""





@require_torch
class      snake_case    (    unittest.TestCase			):





  """simple docstring"""




  @cached_property
  def   snake_case		(    self     ):







   """simple docstring"""
   return AutoConfig.from_pretrained(UpperCamelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_ ,*lowerCamelCase_      =  create_student_by_copying_alternating_layers(UpperCamelCase			,  tempfile.mkdtemp()			,  e=1			,  d=1     )
   self.assertEqual(student.config.num_hidden_layers			,  1     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_ ,*lowerCamelCase_      =  create_student_by_copying_alternating_layers(UpperCamelCase			,  tempfile.mkdtemp()			,  e=1			,  d=UpperCamelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_ ,*lowerCamelCase_      =  create_student_by_copying_alternating_layers(UpperCamelCase			,  tempfile.mkdtemp()			,  e=1			,  d=UpperCamelCase     )
   self.assertEqual(student.config.encoder_layers			,  1     )
   self.assertEqual(student.config.decoder_layers			,  self.teacher_config.encoder_layers     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_ ,*lowerCamelCase_      =  create_student_by_copying_alternating_layers(UpperCamelCase			,  tempfile.mkdtemp()			,  e=1			,  d=1     )
   self.assertEqual(student.config.encoder_layers			,  1     )
   self.assertEqual(student.config.decoder_layers			,  1     )







  def   snake_case		(    self     ):







   """simple docstring"""
   with self.assertRaises(UpperCamelCase     ):
    create_student_by_copying_alternating_layers(UpperCamelCase			,  tempfile.mkdtemp()			,  e=UpperCamelCase			,  d=UpperCamelCase     )







'''simple docstring'''

a_  :				str						= """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

a_  :				Any						= [{"""type""": """code""", """content""": INSTALL_CONTENT}]
a_  :				int						= {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}



