



'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A				:    Union[str, Any]     						={
    '''configuration_blip_2''': [
        '''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Blip2Config''',
        '''Blip2QFormerConfig''',
        '''Blip2VisionConfig''',
    ],
    '''processing_blip_2''': ['''Blip2Processor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_A				:    Optional[int]     						=[
		    '''BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''Blip2Model''',
		    '''Blip2QFormerModel''',
		    '''Blip2PreTrainedModel''',
		    '''Blip2ForConditionalGeneration''',
		    '''Blip2VisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_blip_a import (
		    BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BlipaConfig,
		    BlipaQFormerConfig,
		    BlipaVisionConfig,
		)
		from .processing_blip_a import BlipaProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip_a import (
				    BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipaForConditionalGeneration,
				    BlipaModel,
				    BlipaPreTrainedModel,
				    BlipaQFormerModel,
				    BlipaVisionModel,
				)

else:
		import sys

		_A				:    Optional[int]     						=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





'''simple docstring'''

_A				:    Dict     						='''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

_A				:    Dict     						=[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
_A				:    Dict     						={
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}
