
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__		:List[Any]   =    "sshleifer/bart-tiny-random"
lowercase__		:Union[str, Any]   =    "patrickvonplaten/t5-tiny-random"







@require_torch
class 				lowercase		(					unittest.TestCase		):




							@cached_property
							def  A__      (				self):
												return AutoConfig.from_pretrained(A__)




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




							def  A__      (				self):
												lowercase	,						*lowercase							=						create_student_by_copying_alternating_layers(A__   ,tempfile.mkdtemp()   ,e=1   ,d=A__)




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




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





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






import os
import sys

lowercase__		:Tuple   =    os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowercase__		:List[Any]   =    [
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]



@add_start_docstrings(AutoConfig.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoConfig.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoTokenizer.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoTokenizer.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModel.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModel.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForCausalLM.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForCausalLM.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForMaskedLM.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForMaskedLM.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForSequenceClassification.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForSequenceClassification.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForQuestionAnswering.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForQuestionAnswering.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)




