



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase__					  =  {
    '''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:
				lowerCAmelCase__					  =  [
				    '''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

				lowerCAmelCase__					  =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









from typing import Union

import fire
import torch
from tqdm import tqdm


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__ = "cpu"					,			lowerCamelCase__ = None						):

				"""simple docstring"""


				lowercase__					:   Any													=					torch.load(lowerCamelCase__					,			map_location=lowerCamelCase__						)
				for k, v in tqdm(state_dict.items()						):
								if not isinstance(lowerCamelCase__					,			torch.Tensor						):
												raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"						)
								lowercase__					:   int													=					v.half()
				if save_path is None:  # overwrite src_path
								lowercase__					:   Optional[Any]													=					src_path
				torch.save(lowerCamelCase__					,			lowerCamelCase__						)


if __name__ == "__main__":
				fire.Fire(convert)




