





from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_						       =	{"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	["""DPTFeatureExtractor"""]
      SCREAMING_SNAKE_CASE_						       =	["""DPTImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """DPTForDepthEstimation""",
          """DPTForSemanticSegmentation""",
          """DPTModel""",
          """DPTPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_dpt import DPTFeatureExtractor
            from .image_processing_dpt import DPTImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_dpt import (
                DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DPTForDepthEstimation,
                DPTForSemanticSegmentation,
                DPTModel,
                DPTPreTrainedModel,
            )


else:
      import sys

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









from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_						       =	{
    """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
    """tokenization_mvp""": ["""MvpTokenizer"""],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """MVP_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MvpForCausalLM""",
          """MvpForConditionalGeneration""",
          """MvpForQuestionAnswering""",
          """MvpForSequenceClassification""",
          """MvpModel""",
          """MvpPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
      from .tokenization_mvp import MvpTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_mvp_fast import MvpTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mvp import (
                MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                MvpForCausalLM,
                MvpForConditionalGeneration,
                MvpForQuestionAnswering,
                MvpForSequenceClassification,
                MvpModel,
                MvpPreTrainedModel,
            )

else:
      import sys

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


