text: import torch
  from torch2trt_dynamic.converters.roi_align import *
  import mmcv.ops
  
  
  @tensorrt_converter("mmcv.ops.RoIAlign.forward")
  def convert_mmcv_RoIAlign(ctx):
      module = ctx.method_args[0]
      input = get_arg(ctx, 'input', pos=1, default=None)
      boxes = get_arg(ctx, 'boxes', pos=2, default=None)
  
      output_size = module.output_size
      spatial_scale = module.spatial_scale
      sampling_ratio = module.sampling_ratio
      aligned = module.aligned
  
      old_method_args = ctx.method_args
      old_method_kwargs = ctx.method_kwargs
      new_method_args = [
          input, boxes, output_size, spatial_scale, sampling_ratio, aligned
      ]
      new_method_kwargs = {}
      ctx.method_args = new_method_args
      ctx.method_kwargs = new_method_kwargs
      convert_roi_align(ctx)
      ctx.method_args = old_method_args
      ctx.method_kwargs = old_method_kwargs
  