





"""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											=						"""sshleifer/bart-tiny-random"""
__A											=						"""patrickvonplaten/t5-tiny-random"""






@require_torch
class    _lowerCAmelCase  (	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__     :List[str]											=				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__     :Optional[int]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :List[Any]											=				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__     :Optional[int]											=				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"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A											=						{
    """configuration_x_clip""": [
        """XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XCLIPConfig""",
        """XCLIPTextConfig""",
        """XCLIPVisionConfig""",
    ],
    """processing_x_clip""": ["""XCLIPProcessor"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A											=						[
      """XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """XCLIPModel""",
      """XCLIPPreTrainedModel""",
      """XCLIPTextModel""",
      """XCLIPVisionModel""",
  ]

if TYPE_CHECKING:
  from .configuration_x_clip import (
      XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
      XCLIPConfig,
      XCLIPTextConfig,
      XCLIPVisionConfig,
  )
  from .processing_x_clip import XCLIPProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_x_clip import (
        XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        XCLIPModel,
        XCLIPPreTrainedModel,
        XCLIPTextModel,
        XCLIPVisionModel,
    )

else:
  import sys

  __A											=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
