'''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_     :						Tuple    							='''sshleifer/bart-tiny-random'''
A_     :						Dict    							='''patrickvonplaten/t5-tiny-random'''


@require_torch
class     __UpperCAmelCase       ( unittest.TestCase		):





  @cached_property
  def 						UpperCAmelCase_	(	self ):
     return AutoConfig.from_pretrained(_lowerCamelCase )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_	,*lowerCAmelCase_			=      create_student_by_copying_alternating_layers(_lowerCamelCase    ,     tempfile.mkdtemp()    ,     e=1    ,     d=1 )
     self.assertEqual(student.config.num_hidden_layers    ,     1 )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_	,*lowerCAmelCase_			=      create_student_by_copying_alternating_layers(_lowerCamelCase    ,     tempfile.mkdtemp()    ,     e=1    ,     d=_lowerCamelCase )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_	,*lowerCAmelCase_			=      create_student_by_copying_alternating_layers(_lowerCamelCase    ,     tempfile.mkdtemp()    ,     e=1    ,     d=_lowerCamelCase )
     self.assertEqual(student.config.encoder_layers    ,     1 )
     self.assertEqual(student.config.decoder_layers    ,     self.teacher_config.encoder_layers )





  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_	,*lowerCAmelCase_			=      create_student_by_copying_alternating_layers(_lowerCamelCase    ,     tempfile.mkdtemp()    ,     e=1    ,     d=1 )
     self.assertEqual(student.config.encoder_layers    ,     1 )
     self.assertEqual(student.config.decoder_layers    ,     1 )







  def 						UpperCAmelCase_	(	self ):
     with self.assertRaises(_lowerCamelCase ):
        create_student_by_copying_alternating_layers(_lowerCamelCase    ,     tempfile.mkdtemp()    ,     e=_lowerCamelCase    ,     d=_lowerCamelCase )






'''simple docstring'''

from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_     :						Tuple    							=logging.get_logger(__name__)

A_     :						Dict    							={
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}


class     __UpperCAmelCase       ( __a		):
  __A :				Union[str, Any]											= 'efficientnet'





  def __init__(	self    ,     _lowerCamelCase = 3    ,     _lowerCamelCase = 600    ,     _lowerCamelCase = 2.0    ,     _lowerCamelCase = 3.1    ,     _lowerCamelCase = 8    ,     _lowerCamelCase = [3, 3, 5, 3, 5, 5, 3]    ,     _lowerCamelCase = [32, 16, 24, 40, 80, 112, 192]    ,     _lowerCamelCase = [16, 24, 40, 80, 112, 192, 320]    ,     _lowerCamelCase = []    ,     _lowerCamelCase = [1, 2, 2, 2, 1, 2, 1]    ,     _lowerCamelCase = [1, 2, 2, 3, 3, 4, 1]    ,     _lowerCamelCase = [1, 6, 6, 6, 6, 6, 6]    ,     _lowerCamelCase = 0.25    ,     _lowerCamelCase = "swish"    ,     _lowerCamelCase = 2560    ,     _lowerCamelCase = "mean"    ,     _lowerCamelCase = 0.02    ,     _lowerCamelCase = 0.0_01    ,     _lowerCamelCase = 0.99    ,     _lowerCamelCase = 0.5    ,     _lowerCamelCase = 0.2    ,     **_lowerCamelCase    ,     ):
     super().__init__(**_lowerCamelCase )

     lowerCAmelCase_			=      num_channels
     lowerCAmelCase_			=      image_size
     lowerCAmelCase_			=      width_coefficient
     lowerCAmelCase_			=      depth_coefficient
     lowerCAmelCase_			=      depth_divisor
     lowerCAmelCase_			=      kernel_sizes
     lowerCAmelCase_			=      in_channels
     lowerCAmelCase_			=      out_channels
     lowerCAmelCase_			=      depthwise_padding
     lowerCAmelCase_			=      strides
     lowerCAmelCase_			=      num_block_repeats
     lowerCAmelCase_			=      expand_ratios
     lowerCAmelCase_			=      squeeze_expansion_ratio
     lowerCAmelCase_			=      hidden_act
     lowerCAmelCase_			=      hidden_dim
     lowerCAmelCase_			=      pooling_type
     lowerCAmelCase_			=      initializer_range
     lowerCAmelCase_			=      batch_norm_eps
     lowerCAmelCase_			=      batch_norm_momentum
     lowerCAmelCase_			=      dropout_rate
     lowerCAmelCase_			=      drop_connect_rate
     lowerCAmelCase_			=      sum(_lowerCamelCase ) * 4






class     __UpperCAmelCase       ( __a		):
  __A :				str											= version.parse('1.11'		)





  @property
  def 						UpperCAmelCase_	(	self ):
     return OrderedDict(
         [
             ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
         ] )







  @property
  def 						UpperCAmelCase_	(	self ):
     return 1E-5





