

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase__       = {
    "configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxConfig"],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase__       = ["MobileViTFeatureExtractor"]
      lowerCAmelCase__       = ["MobileViTImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase__       = [
          "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "MobileViTForImageClassification",
          "MobileViTForSemanticSegmentation",
          "MobileViTModel",
          "MobileViTPreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase__       = [
          "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFMobileViTForImageClassification",
          "TFMobileViTForSemanticSegmentation",
          "TFMobileViTModel",
          "TFMobileViTPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_mobilevit import MobileViTFeatureExtractor
            from .image_processing_mobilevit import MobileViTImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mobilevit import (
                MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                MobileViTForImageClassification,
                MobileViTForSemanticSegmentation,
                MobileViTModel,
                MobileViTPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_mobilevit import (
                TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFMobileViTForImageClassification,
                TFMobileViTForSemanticSegmentation,
                TFMobileViTModel,
                TFMobileViTPreTrainedModel,
            )


else:
      import sys

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






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__       = logging.get_logger(__name__)

lowerCAmelCase__       = {
    "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}






class 						__magic_name__    (       _snake_case    ):
 UpperCAmelCase							    =						"""lxmert"""
 UpperCAmelCase							    =						{}


 def __init__(						self		: int			,						lowerCAmelCase__		: Any=3_0_5_2_2			,						lowerCAmelCase__		: List[str]=7_6_8			,						lowerCAmelCase__		: Union[str, Any]=1_2			,						lowerCAmelCase__		: List[Any]=9_5_0_0			,						lowerCAmelCase__		: Any=1_6_0_0			,						lowerCAmelCase__		: Union[str, Any]=4_0_0			,						lowerCAmelCase__		: Tuple=3_0_7_2			,						lowerCAmelCase__		: Dict="gelu"			,						lowerCAmelCase__		: Tuple=0.1			,						lowerCAmelCase__		: Tuple=0.1			,						lowerCAmelCase__		: int=5_1_2			,						lowerCAmelCase__		: List[str]=2			,						lowerCAmelCase__		: List[str]=0.02			,						lowerCAmelCase__		: str=1e-1_2			,						lowerCAmelCase__		: str=9			,						lowerCAmelCase__		: int=5			,						lowerCAmelCase__		: Optional[int]=5			,						lowerCAmelCase__		: List[Any]=2_0_4_8			,						lowerCAmelCase__		: Any=4			,						lowerCAmelCase__		: Dict=6.67			,						lowerCAmelCase__		: Any=True			,						lowerCAmelCase__		: Union[str, Any]=True			,						lowerCAmelCase__		: Any=True			,						lowerCAmelCase__		: Tuple=True			,						lowerCAmelCase__		: Optional[Any]=True			,						lowerCAmelCase__		: Optional[int]=True			,						lowerCAmelCase__		: Tuple=True			,						**lowerCAmelCase__		: List[Any]			,						)    ->      Dict:
   UpperCAmelCase					      =  vocab_size
   UpperCAmelCase					      =  hidden_size
   UpperCAmelCase					      =  num_attention_heads
   UpperCAmelCase					      =  hidden_act
   UpperCAmelCase					      =  intermediate_size
   UpperCAmelCase					      =  hidden_dropout_prob
   UpperCAmelCase					      =  attention_probs_dropout_prob
   UpperCAmelCase					      =  max_position_embeddings
   UpperCAmelCase					      =  type_vocab_size
   UpperCAmelCase					      =  initializer_range
   UpperCAmelCase					      =  layer_norm_eps
   UpperCAmelCase					      =  num_qa_labels
   UpperCAmelCase					      =  num_object_labels
   UpperCAmelCase					      =  num_attr_labels
   UpperCAmelCase					      =  l_layers
   UpperCAmelCase					      =  x_layers
   UpperCAmelCase					      =  r_layers
   UpperCAmelCase					      =  visual_feat_dim
   UpperCAmelCase					      =  visual_pos_dim
   UpperCAmelCase					      =  visual_loss_normalizer
   UpperCAmelCase					      =  task_matched
   UpperCAmelCase					      =  task_mask_lm
   UpperCAmelCase					      =  task_obj_predict
   UpperCAmelCase					      =  task_qa
   UpperCAmelCase					      =  visual_obj_loss
   UpperCAmelCase					      =  visual_attr_loss
   UpperCAmelCase					      =  visual_feat_loss
   UpperCAmelCase					      =  {"vision": r_layers, "cross_encoder": x_layers, "language": l_layers}
   super().__init__(**lowerCAmelCase__    )



