


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A			:						str        =  {
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A			:						int        =  [
	    'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'MegatronBertForCausalLM',
	    'MegatronBertForMaskedLM',
	    'MegatronBertForMultipleChoice',
	    'MegatronBertForNextSentencePrediction',
	    'MegatronBertForPreTraining',
	    'MegatronBertForQuestionAnswering',
	    'MegatronBertForSequenceClassification',
	    'MegatronBertForTokenClassification',
	    'MegatronBertModel',
	    'MegatronBertPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_megatron_bert import (
		    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MegatronBertForCausalLM,
		    MegatronBertForMaskedLM,
		    MegatronBertForMultipleChoice,
		    MegatronBertForNextSentencePrediction,
		    MegatronBertForPreTraining,
		    MegatronBertForQuestionAnswering,
		    MegatronBertForSequenceClassification,
		    MegatronBertForTokenClassification,
		    MegatronBertModel,
		    MegatronBertPreTrainedModel,
		)

else:
	import sys

	A			:						Dict        =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


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


_lowercase:	str       			=		'''sshleifer/bart-tiny-random'''
_lowercase:	Union[str, Any]       			=		'''patrickvonplaten/t5-tiny-random'''



@require_torch
class        lowerCamelCase__				(   unittest.TestCase				):





			@cached_property
			def   SCREAMING_SNAKE_CASE__     (       self	:	Tuple						):
										return AutoConfig.from_pretrained(lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	int						):
										_lowerCAmelCase			,		*_lowerCAmelCase							=							create_student_by_copying_alternating_layers(lowercase__  ,  tempfile.mkdtemp()  ,  e=1  ,  d=1						)
										self.assertEqual(student.config.num_hidden_layers  ,  1						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Dict						):
										_lowerCAmelCase			,		*_lowerCAmelCase							=							create_student_by_copying_alternating_layers(lowercase__  ,  tempfile.mkdtemp()  ,  e=1  ,  d=lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Union[str, Any]						):
										_lowerCAmelCase			,		*_lowerCAmelCase							=							create_student_by_copying_alternating_layers(lowercase__  ,  tempfile.mkdtemp()  ,  e=1  ,  d=lowercase__						)
										self.assertEqual(student.config.encoder_layers  ,  1						)
										self.assertEqual(student.config.decoder_layers  ,  self.teacher_config.encoder_layers						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	str						):
										_lowerCAmelCase			,		*_lowerCAmelCase							=							create_student_by_copying_alternating_layers(lowercase__  ,  tempfile.mkdtemp()  ,  e=1  ,  d=1						)
										self.assertEqual(student.config.encoder_layers  ,  1						)
										self.assertEqual(student.config.decoder_layers  ,  1						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	List[str]						):
										with self.assertRaises(lowercase__						):
																	create_student_by_copying_alternating_layers(lowercase__  ,  tempfile.mkdtemp()  ,  e=lowercase__  ,  d=lowercase__						)






