


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCAmelCase							=						{
    """configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Data2VecAudioConfig"""],
    """configuration_data2vec_text""": [
        """DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Data2VecTextConfig""",
        """Data2VecTextOnnxConfig""",
    ],
    """configuration_data2vec_vision""": [
        """DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Data2VecVisionConfig""",
        """Data2VecVisionOnnxConfig""",
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase							=						[
				    """DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """Data2VecAudioForAudioFrameClassification""",
				    """Data2VecAudioForCTC""",
				    """Data2VecAudioForSequenceClassification""",
				    """Data2VecAudioForXVector""",
				    """Data2VecAudioModel""",
				    """Data2VecAudioPreTrainedModel""",
				]
				lowerCAmelCase							=						[
				    """DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """Data2VecTextForCausalLM""",
				    """Data2VecTextForMaskedLM""",
				    """Data2VecTextForMultipleChoice""",
				    """Data2VecTextForQuestionAnswering""",
				    """Data2VecTextForSequenceClassification""",
				    """Data2VecTextForTokenClassification""",
				    """Data2VecTextModel""",
				    """Data2VecTextPreTrainedModel""",
				]
				lowerCAmelCase							=						[
				    """DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """Data2VecVisionForImageClassification""",
				    """Data2VecVisionForMaskedImageModeling""",
				    """Data2VecVisionForSemanticSegmentation""",
				    """Data2VecVisionModel""",
				    """Data2VecVisionPreTrainedModel""",
				]

if is_tf_available():
				lowerCAmelCase							=						[
				    """TFData2VecVisionForImageClassification""",
				    """TFData2VecVisionForSemanticSegmentation""",
				    """TFData2VecVisionModel""",
				    """TFData2VecVisionPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
				from .configuration_dataavec_text import (
				    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    DataaVecTextConfig,
				    DataaVecTextOnnxConfig,
				)
				from .configuration_dataavec_vision import (
				    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    DataaVecVisionConfig,
				    DataaVecVisionOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_dataavec_audio import (
								    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DataaVecAudioForAudioFrameClassification,
								    DataaVecAudioForCTC,
								    DataaVecAudioForSequenceClassification,
								    DataaVecAudioForXVector,
								    DataaVecAudioModel,
								    DataaVecAudioPreTrainedModel,
								)
								from .modeling_dataavec_text import (
								    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DataaVecTextForCausalLM,
								    DataaVecTextForMaskedLM,
								    DataaVecTextForMultipleChoice,
								    DataaVecTextForQuestionAnswering,
								    DataaVecTextForSequenceClassification,
								    DataaVecTextForTokenClassification,
								    DataaVecTextModel,
								    DataaVecTextPreTrainedModel,
								)
								from .modeling_dataavec_vision import (
								    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DataaVecVisionForImageClassification,
								    DataaVecVisionForMaskedImageModeling,
								    DataaVecVisionForSemanticSegmentation,
								    DataaVecVisionModel,
								    DataaVecVisionPreTrainedModel,
								)
				if is_tf_available():
								from .modeling_tf_dataavec_vision import (
								    TFDataaVecVisionForImageClassification,
								    TFDataaVecVisionForSemanticSegmentation,
								    TFDataaVecVisionModel,
								    TFDataaVecVisionPreTrainedModel,
								)

else:
				import sys

				lowerCAmelCase							=						_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


lowerCAmelCase							=						"""sshleifer/bart-tiny-random"""
lowerCAmelCase							=						"""patrickvonplaten/t5-tiny-random"""




@require_torch
class        lowerCamelCase      (     unittest.TestCase   ):


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


	def    A(						self):
							__UpperCAmelCase						,			*__UpperCAmelCase :       Dict  						=  create_student_by_copying_alternating_layers(lowercase__							,    tempfile.mkdtemp()							,    e=1							,    d=1)
							self.assertEqual(student.config.num_hidden_layers							,    1)


	def    A(						self):
							__UpperCAmelCase						,			*__UpperCAmelCase :       Union[str, Any]  						=  create_student_by_copying_alternating_layers(lowercase__							,    tempfile.mkdtemp()							,    e=1							,    d=lowercase__)


	def    A(						self):
							__UpperCAmelCase						,			*__UpperCAmelCase :       Tuple  						=  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    A(						self):
							__UpperCAmelCase						,			*__UpperCAmelCase :       Dict  						=  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    A(						self):
							with self.assertRaises(lowercase__):
													create_student_by_copying_alternating_layers(lowercase__							,    tempfile.mkdtemp()							,    e=lowercase__							,    d=lowercase__)

