






from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__       :			Optional[Any]			      =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       :			str			      =						{
    'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}







class   __lowerCAmelCase			(					_A  ):
   _UpperCamelCase :						str     		=				"""mra"""





   def __init__( self					,			snake_case=50_265					,			snake_case=768					,			snake_case=12					,			snake_case=12					,			snake_case=3_072					,			snake_case="gelu"					,			snake_case=0.1					,			snake_case=0.1					,			snake_case=512					,			snake_case=1					,			snake_case=0.02					,			snake_case=1E-5					,			snake_case="absolute"					,			snake_case=4					,			snake_case="full"					,			snake_case=0					,			snake_case=0					,			snake_case=1					,			snake_case=0					,			snake_case=2					,			**snake_case					,			)				->  List[Any]:
      """simple docstring"""





      super().__init__(pad_token_id=UpperCamelCase__					,			bos_token_id=UpperCamelCase__					,			eos_token_id=UpperCamelCase__					,			**UpperCamelCase__      )

      a__	:						List[str]      		=  vocab_size
      a__	:						Dict      		=  max_position_embeddings
      a__	:						Dict      		=  hidden_size
      a__	:						Any      		=  num_hidden_layers
      a__	:						List[Any]      		=  num_attention_heads
      a__	:						Dict      		=  intermediate_size
      a__	:						str      		=  hidden_act
      a__	:						Optional[Any]      		=  hidden_dropout_prob
      a__	:						int      		=  attention_probs_dropout_prob
      a__	:						Union[str, Any]      		=  initializer_range
      a__	:						str      		=  type_vocab_size
      a__	:						Any      		=  layer_norm_eps
      a__	:						int      		=  position_embedding_type
      a__	:						Dict      		=  block_per_row
      a__	:						Dict      		=  approx_mode
      a__	:						int      		=  initial_prior_first_n_blocks
      a__	:						List[str]      		=  initial_prior_diagonal_n_blocks








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      )

