



import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


__SCREAMING_SNAKE_CASE         =  ["""small""", """medium""", """large"""]

__SCREAMING_SNAKE_CASE         =  """lm_head.decoder.weight"""
__SCREAMING_SNAKE_CASE         =  """lm_head.weight"""




def 	UpperCAmelCase   (						_lowerCamelCase ,    _lowerCamelCase    ):
			A							:					Optional[int]              =						torch.load(_lowerCAmelCase    )
			A							:					Tuple              =						d.pop(_lowerCAmelCase    )
			os.makedirs(_lowerCAmelCase ,    exist_ok=_lowerCAmelCase    )
			torch.save(_lowerCAmelCase ,    os.path.join(_lowerCAmelCase ,    _lowerCAmelCase    )    )


if __name__ == "__main__":
							__SCREAMING_SNAKE_CASE         =  argparse.ArgumentParser()
							parser.add_argument("""--dialogpt_path""", default=""".""", type=str)
							__SCREAMING_SNAKE_CASE         =  parser.parse_args()
							for MODEL in DIALOGPT_MODELS:
														__SCREAMING_SNAKE_CASE         =  os.path.join(args.dialogpt_path, F"""{MODEL}_ft.pkl""")
														__SCREAMING_SNAKE_CASE         =  F"""./DialoGPT-{MODEL}"""
														convert_dialogpt_checkpoint(
														    checkpoint_path,
														    pytorch_dump_folder_path,
														)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE           =  {
    """configuration_instructblip""": [
        """INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """InstructBlipConfig""",
        """InstructBlipQFormerConfig""",
        """InstructBlipVisionConfig""",
    ],
    """processing_instructblip""": ["""InstructBlipProcessor"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE           =  [
							    """INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """InstructBlipQFormerModel""",
							    """InstructBlipPreTrainedModel""",
							    """InstructBlipForConditionalGeneration""",
							    """InstructBlipVisionModel""",
							]

if TYPE_CHECKING:
							from .configuration_instructblip import (
							    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    InstructBlipConfig,
							    InstructBlipQFormerConfig,
							    InstructBlipVisionConfig,
							)
							from .processing_instructblip import InstructBlipProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_instructblip import (
														    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    InstructBlipForConditionalGeneration,
														    InstructBlipPreTrainedModel,
														    InstructBlipQFormerModel,
														    InstructBlipVisionModel,
														)

else:
							import sys

							__SCREAMING_SNAKE_CASE           =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)