content: import logging
  from typing import Any, Callable, Dict
  
  from torch.fx.node import Target
  
  CONVERTERS: Dict[Target, Any] = {}
  NO_IMPLICIT_BATCH_DIM_SUPPORT = {}
  NO_EXPLICIT_BATCH_DIM_SUPPORT = {}
  
  
  logger = logging.getLogger(__name__)
  
  
  def tensorrt_converter(
      key: Target,
      no_implicit_batch_dim: bool = False,
      no_explicit_batch_dim: bool = False,
      enabled: bool = True,
  ) -> Callable[[Any], Any]:
      def register_converter(converter):
          CONVERTERS[key] = converter
          if no_implicit_batch_dim:
              NO_IMPLICIT_BATCH_DIM_SUPPORT[key] = converter
          if no_explicit_batch_dim:
              NO_EXPLICIT_BATCH_DIM_SUPPORT[key] = converter
  
          logger.debug(
              f"Converter for {key} added to FX Converter Registry "
              + f"{'without' if no_explicit_batch_dim else 'with'} Explicit Batch Dim Support + "
              + f"{'without' if no_implicit_batch_dim else 'with'} Implicit Batch Dim Support"
          )
  
          return converter
  
      def disable_converter(converter):
          return converter
  
      if enabled:
          return register_converter
      else:
          return disable_converter
  