



from typing import List

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


SCREAMING_SNAKE_CASE__       =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       =      {
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}


class      __lowerCAmelCase     (		__lowerCAmelCase      ):
					"""simple docstring"""






					A__				:		str			       =    "efficientformer"



					def __init__(     self					:       Any				,					_snake_case					:       List[int] = [3, 2, 6, 4]				,					_snake_case					:       List[int] = [48, 96, 2_24, 4_48]				,					_snake_case					:       List[bool] = [True, True, True, True]				,					_snake_case					:       int = 4_48				,					_snake_case					:       int = 32				,					_snake_case					:       int = 4				,					_snake_case					:       int = 7				,					_snake_case					:       int = 5				,					_snake_case					:       int = 8				,					_snake_case					:       int = 4				,					_snake_case					:       float = 0.0				,					_snake_case					:       int = 16				,					_snake_case					:       int = 3				,					_snake_case					:       int = 3				,					_snake_case					:       int = 3				,					_snake_case					:       int = 2				,					_snake_case					:       int = 1				,					_snake_case					:       float = 0.0				,					_snake_case					:       int = 1				,					_snake_case					:       bool = True				,					_snake_case					:       bool = True				,					_snake_case					:       float = 1E-5				,					_snake_case					:       str = "gelu"				,					_snake_case					:       float = 0.02				,					_snake_case					:       float = 1E-12				,					_snake_case					:       int = 2_24				,					_snake_case					:       float = 1E-05				,					**_snake_case					:       str				,					):






								"""simple docstring"""


								super().__init__(**lowerCamelCase__					)

								A__       =    hidden_act
								A__       =    hidden_dropout_prob
								A__       =    hidden_sizes
								A__       =    num_hidden_layers
								A__       =    num_attention_heads
								A__       =    initializer_range
								A__       =    layer_norm_eps
								A__       =    patch_size
								A__       =    num_channels
								A__       =    depths
								A__       =    mlp_expansion_ratio
								A__       =    downsamples
								A__       =    dim
								A__       =    key_dim
								A__       =    attention_ratio
								A__       =    resolution
								A__       =    pool_size
								A__       =    downsample_patch_size
								A__       =    downsample_stride
								A__       =    downsample_pad
								A__       =    drop_path_rate
								A__       =    num_metaad_blocks
								A__       =    distillation
								A__       =    use_layer_scale
								A__       =    layer_scale_init_value
								A__       =    image_size
								A__       =    batch_norm_eps





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__       =      '''sshleifer/bart-tiny-random'''
SCREAMING_SNAKE_CASE__       =      '''patrickvonplaten/t5-tiny-random'''


@require_torch
class      __lowerCAmelCase     (		unittest.TestCase      ):
					"""simple docstring"""






					@cached_property
					def     _a							(     self					:       Optional[int]					):






								"""simple docstring"""


								return AutoConfig.from_pretrained(_snake_case					)



					def     _a							(     self					:       Optional[Any]					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=1					)
								self.assertEqual(student.config.num_hidden_layers				,					1					)



					def     _a							(     self					:       Optional[int]					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=_snake_case					)



					def     _a							(     self					:       int					):






								"""simple docstring"""


								A__     , *A__       =    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     _a							(     self					:       str					):






								"""simple docstring"""


								A__     , *A__       =    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     _a							(     self					:       str					):






								"""simple docstring"""


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




