





"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_			=      {
    """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_			=      [
							    """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_			=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)











"""simple docstring"""



from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


a_			=      {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_			=      ["""GPTNeoXTokenizerFast"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_			=      [
           """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """GPTNeoXForCausalLM""",
           """GPTNeoXForQuestionAnswering""",
           """GPTNeoXForSequenceClassification""",
           """GPTNeoXForTokenClassification""",
           """GPTNeoXLayer""",
           """GPTNeoXModel""",
           """GPTNeoXPreTrainedModel""",
       ]


if TYPE_CHECKING:
       from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_gpt_neox import (
                  GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GPTNeoXForCausalLM,
                  GPTNeoXForQuestionAnswering,
                  GPTNeoXForSequenceClassification,
                  GPTNeoXForTokenClassification,
                  GPTNeoXLayer,
                  GPTNeoXModel,
                  GPTNeoXPreTrainedModel,
              )


else:
       import sys

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




