





import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     str			    =       DownBlockaD  # noqa F405
					lowerCamelCase     :     List[Any]			    =       'down'





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.0232, -0.9869, 0.8054, -0.0637, -0.1688, -1.4264, 0.4470, -1.3394, 0.0904]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Any			    =       ResnetDownsampleBlockaD  # noqa F405
					lowerCamelCase     :     Dict			    =       'down'





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.0710, 0.2410, -0.7320, -1.0757, -1.1343, 0.3540, -0.0133, -0.2576, 0.0948]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     List[str]			    =       AttnDownBlockaD  # noqa F405
					lowerCamelCase     :     int			    =       'down'





					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.0636, 0.8964, -0.6234, -1.0131, 0.0844, 0.4935, 0.3437, 0.0911, -0.2957]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Union[str, Any]			    =       CrossAttnDownBlockaD  # noqa F405
					lowerCamelCase     :     List[str]			    =       'down'





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.2238, -0.7396, -0.2255, -0.3829, 0.1925, 1.1665, 0.0603, -0.7295, 0.1983]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Optional[int]			    =       SimpleCrossAttnDownBlockaD  # noqa F405
					lowerCamelCase     :     int			    =       'down'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						return super().get_dummy_input(include_encoder_hidden_states=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					@unittest.skipIf(torch_device == """mps""" ,					"""MPS result is not consistent"""		)
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.7921, -0.0992, -0.1962, -0.7695, -0.4242, 0.7804, 0.4737, 0.2765, 0.3338]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Dict			    =       SkipDownBlockaD  # noqa F405
					lowerCamelCase     :     int			    =       'down'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						return super().get_dummy_input(include_skip_sample=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.0845, -0.2087, -0.2465, 0.0971, 0.1900, -0.0484, 0.2664, 0.4179, 0.5069]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     List[str]			    =       AttnSkipDownBlockaD  # noqa F405
					lowerCamelCase     :     Optional[int]			    =       'down'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  List[str]		):






						'''simple docstring'''







						return super().get_dummy_input(include_skip_sample=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.5539, 0.1609, 0.4924, 0.0537, -0.1995, 0.4050, 0.0979, -0.2721, -0.0642]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Dict			    =       DownEncoderBlockaD  # noqa F405
					lowerCamelCase     :     Optional[Any]			    =       'down'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any]		):






						'''simple docstring'''







						return super().get_dummy_input(include_temb=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     {
						    """in_channels""": 32,
						    """out_channels""": 32,
						}
						UpperCAmelCase_								=     self.dummy_input
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [1.1102, 0.5302, 0.4872, -0.0023, -0.8042, 0.0483, -0.3489, -0.5632, 0.7626]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     int			    =       AttnDownEncoderBlockaD  # noqa F405
					lowerCamelCase     :     Tuple			    =       'down'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						return super().get_dummy_input(include_temb=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     {
						    """in_channels""": 32,
						    """out_channels""": 32,
						}
						UpperCAmelCase_								=     self.dummy_input
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.8966, -0.1486, 0.8568, 0.8141, -0.9046, -0.1342, -0.0972, -0.7417, 0.1538]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Any			    =       UNetMidBlockaD  # noqa F405
					lowerCamelCase     :     Dict			    =       'mid'





					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     {
						    """in_channels""": 32,
						    """temb_channels""": 1_28,
						}
						UpperCAmelCase_								=     self.dummy_input
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  List[str]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.1062, 1.7248, 0.3494, 1.4569, -0.0910, -1.2421, -0.9984, 0.6736, 1.0028]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Optional[int]			    =       UNetMidBlockaDCrossAttn  # noqa F405
					lowerCamelCase     :     Union[str, Any]			    =       'mid'





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.0187, 2.4220, 0.4484, 1.1203, -0.6121, -1.5122, -0.8270, 0.7851, 1.8335]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Union[str, Any]			    =       UNetMidBlockaDSimpleCrossAttn  # noqa F405
					lowerCamelCase     :     Union[str, Any]			    =       'mid'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						return super().get_dummy_input(include_encoder_hidden_states=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.7143, 1.9974, 0.5448, 1.3977, 0.1282, -1.1237, -1.4238, 0.5530, 0.8880]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Tuple			    =       UpBlockaD  # noqa F405
					lowerCamelCase     :     Optional[int]			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.2041, -0.4165, -0.3022, 0.0041, -0.6628, -0.7053, 0.1928, -0.0325, 0.0523]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     int			    =       ResnetUpsampleBlockaD  # noqa F405
					lowerCamelCase     :     List[Any]			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.2287, 0.3549, -0.1346, 0.4797, -0.1715, -0.9649, 0.7305, -0.5864, -0.6244]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     str			    =       CrossAttnUpBlockaD  # noqa F405
					lowerCamelCase     :     Optional[int]			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.1403, -0.3515, -0.0420, -0.1425, 0.3167, 0.5094, -0.2181, 0.5931, 0.5582]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Optional[Any]			    =       SimpleCrossAttnUpBlockaD  # noqa F405
					lowerCamelCase     :     Optional[Any]			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase ,					include_encoder_hidden_states=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_						,	UpperCAmelCase_								=     super().prepare_init_args_and_inputs_for_common()
						UpperCAmelCase_								=     32
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.2645, 0.1480, 0.0909, 0.8044, -0.9758, -0.9083, 0.0994, -1.1453, -0.7402]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Union[str, Any]			    =       AttnUpBlockaD  # noqa F405
					lowerCamelCase     :     int			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					@unittest.skipIf(torch_device == """mps""" ,					"""MPS result is not consistent"""		)
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.0979, 0.1326, 0.0021, 0.0659, 0.2249, 0.0059, 0.1132, 0.5952, 0.1033]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Dict			    =       SkipUpBlockaD  # noqa F405
					lowerCamelCase     :     Dict			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     [-0.0893, -0.1234, -0.1506, -0.0332, 0.0123, -0.0211, 0.0566, 0.0143, 0.0362]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Any			    =       AttnSkipUpBlockaD  # noqa F405
					lowerCamelCase     :     Tuple			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						return super().get_dummy_input(include_res_hidden_states_tuple=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.0361, 0.0617, 0.2787, -0.0350, 0.0342, 0.3421, -0.0843, 0.0913, 0.3015]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Optional[Any]			    =       UpDecoderBlockaD  # noqa F405
					lowerCamelCase     :     Dict			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						return super().get_dummy_input(include_temb=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						UpperCAmelCase_								=     {"""in_channels""": 32, """out_channels""": 32}

						UpperCAmelCase_								=     self.dummy_input
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.4404, 0.1998, -0.9886, -0.3320, -0.3128, -0.7034, -0.6955, -0.2338, -0.3137]
						super().test_output(__lowercase		)







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     List[Any]			    =       AttnUpDecoderBlockaD  # noqa F405
					lowerCamelCase     :     Union[str, Any]			    =       'up'





					@property
					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						return super().get_dummy_input(include_temb=__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     {"""in_channels""": 32, """out_channels""": 32}

						UpperCAmelCase_								=     self.dummy_input
						return init_dict, inputs_dict





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						UpperCAmelCase_								=     [0.6738, 0.4491, 0.1055, 1.0710, 0.7316, 0.3339, 0.3352, 0.1023, 0.3568]
						super().test_output(__lowercase		)









from argparse import ArgumentParser, Namespace

from ..utils import logging
from . import BaseTransformersCLICommand




def    A_(			A   ):
	return ConvertCommand(
	    args.model_type				,      args.tf_checkpoint				,      args.pytorch_dump_output				,      args.config				,      args.finetuning_task_name   )


UpperCamelCase__   : Any					  = """
transformers can only be used from the commandline to convert TensorFlow models in PyTorch, In that case, it requires
TensorFlow to be installed. Please see https://www.tensorflow.org/install/ for installation instructions.
"""







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					@staticmethod
					def        SCREAMING_SNAKE_CASE							(						__lowercase    :  ArgumentParser		):






						'''simple docstring'''







						UpperCAmelCase_								=     parser.add_parser(
						    """convert""" ,					help="""CLI tool to run convert model from original author checkpoints to Transformers PyTorch checkpoints.""" ,					)
						train_parser.add_argument("""--model_type""" ,					type=__lowercase ,					required=__lowercase ,					help="""Model's type."""		)
						train_parser.add_argument(
						    """--tf_checkpoint""" ,					type=__lowercase ,					required=__lowercase ,					help="""TensorFlow checkpoint path or folder."""		)
						train_parser.add_argument(
						    """--pytorch_dump_output""" ,					type=__lowercase ,					required=__lowercase ,					help="""Path to the PyTorch saved model output."""		)
						train_parser.add_argument("""--config""" ,					type=__lowercase ,					default="""""" ,					help="""Configuration file path or folder."""		)
						train_parser.add_argument(
						    """--finetuning_task_name""" ,					type=__lowercase ,					default=__lowercase ,					help="""Optional fine-tuning task name if the TF model was a finetuned model.""" ,					)
						train_parser.set_defaults(func=__lowercase		)





					def __init__(						self    :  Optional[int] ,					__lowercase    :  str ,					__lowercase    :  str ,					__lowercase    :  str ,					__lowercase    :  str ,					__lowercase    :  str ,					*__lowercase    :  Tuple ,					):






						'''simple docstring'''







						UpperCAmelCase_								=     logging.get_logger("""transformers-cli/converting"""		)

						self._logger.info(F"""Loading model {model_type}"""		)
						UpperCAmelCase_								=     model_type
						UpperCAmelCase_								=     tf_checkpoint
						UpperCAmelCase_								=     pytorch_dump_output
						UpperCAmelCase_								=     config
						UpperCAmelCase_								=     finetuning_task_name





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						if self._model_type == "albert":
							try:
								from ..models.albert.convert_albert_original_tf_checkpoint_to_pytorch import (
								    convert_tf_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							convert_tf_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "bert":
							try:
								from ..models.bert.convert_bert_original_tf_checkpoint_to_pytorch import (
								    convert_tf_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							convert_tf_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "funnel":
							try:
								from ..models.funnel.convert_funnel_original_tf_checkpoint_to_pytorch import (
								    convert_tf_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							convert_tf_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "t5":
							try:
								from ..models.ta.convert_ta_original_tf_checkpoint_to_pytorch import convert_tf_checkpoint_to_pytorch
							except ImportError:
								raise ImportError(__lowercase		)

							convert_tf_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "gpt":
							from ..models.openai.convert_openai_original_tf_checkpoint_to_pytorch import (
							    convert_openai_checkpoint_to_pytorch,
							)

							convert_openai_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "transfo_xl":
							try:
								from ..models.transfo_xl.convert_transfo_xl_original_tf_checkpoint_to_pytorch import (
								    convert_transfo_xl_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							if "ckpt" in self._tf_checkpoint.lower():
								UpperCAmelCase_								=     self._tf_checkpoint
								UpperCAmelCase_								=     """"""
							else:
								UpperCAmelCase_								=     self._tf_checkpoint
								UpperCAmelCase_								=     """"""
							convert_transfo_xl_checkpoint_to_pytorch(
							    __lowercase ,					self._config ,					self._pytorch_dump_output ,					__lowercase		)
						elif self._model_type == "gpt2":
							try:
								from ..models.gpta.convert_gpta_original_tf_checkpoint_to_pytorch import (
								    convert_gpta_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							convert_gpta_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						elif self._model_type == "xlnet":
							try:
								from ..models.xlnet.convert_xlnet_original_tf_checkpoint_to_pytorch import (
								    convert_xlnet_checkpoint_to_pytorch,
								)
							except ImportError:
								raise ImportError(__lowercase		)

							convert_xlnet_checkpoint_to_pytorch(
							    self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output ,					self._finetuning_task_name		)
						elif self._model_type == "xlm":
							from ..models.xlm.convert_xlm_original_pytorch_checkpoint_to_pytorch import (
							    convert_xlm_checkpoint_to_pytorch,
							)

							convert_xlm_checkpoint_to_pytorch(self._tf_checkpoint ,					self._pytorch_dump_output		)
						elif self._model_type == "lxmert":
							from ..models.lxmert.convert_lxmert_original_tf_checkpoint_to_pytorch import (
							    convert_lxmert_checkpoint_to_pytorch,
							)

							convert_lxmert_checkpoint_to_pytorch(self._tf_checkpoint ,					self._pytorch_dump_output		)
						elif self._model_type == "rembert":
							from ..models.rembert.convert_rembert_tf_checkpoint_to_pytorch import (
							    convert_rembert_tf_checkpoint_to_pytorch,
							)

							convert_rembert_tf_checkpoint_to_pytorch(self._tf_checkpoint ,					self._config ,					self._pytorch_dump_output		)
						else:
							raise ValueError(
							    """--model_type should be selected in the list [bert, gpt, gpt2, t5, transfo_xl, xlnet, xlm, lxmert]"""		)


