          # Be conservative to avoid OOM.
          self.vram = None
  
          # For detectors that support batching, this should be set to
          # the calculated batch size that the amount of available VRAM
          # will support. It is also used for holding the number of threads/
          # processes for parallel processing plugins
          self.batch_size = 1
 
</s> remove             # OpenCL loads and unloads VRAM as required, so this returns the global memory size
            # less the maximum allowed allocation size. It's not particularly useful
            vram = [self.plaid.vram[idx] - self.plaid.max_alloc[idx]
                    for idx in range(self.device_count)]
 </s> add             # OpenCL loads and unloads VRAM as required, so this returns 0
            # It's not particularly useful
            vram = [0 for idx in range(self.device_count)] </s> remove             # OpenCL loads and unloads VRAM as required, so this returns the maximum allowed
            # allocation size. It's not particularly useful
            vram = self.plaid.max_alloc
 </s> add             # OpenCL loads and unloads VRAM as required, so this returns the total memory
            # It's not particularly useful
            vram = self.plaid.vram </s> remove     @staticmethod
    def get_vram_free():
 </s> add     def get_vram_free(self): </s> remove         if not multiprocess:
            logger.debug("Parallel processing disabled by cli.")
            return False

 </s> add 
        # Set to true if the plugin supports PlaidML
        self.supports_plaidml = False

          # Be conservative to avoid OOM.
          self.vram = None
  
        # Set to true if the plugin supports PlaidML
        self.supports_plaidml = False

          # For detectors that support batching, this should be set to
          # the calculated batch size that the amount of available VRAM
          # will support. It is also used for holding the number of threads/
          # processes for parallel processing plugins
          self.batch_size = 1
keep keep add keep keep keep keep keep
 Fix Active Devices for plaidML. Add Supports PlaidML to Extractors 
plugins/extract/detect/_base.py