def forward(ctx, input, roi, output_size, spatial_scale, sampling_ratio, aligned):
ctx.save_for_backward(roi)
ctx.output_size = _pair(output_size)
ctx.spatial_scale = spatial_scale
ctx.sampling_ratio = sampling_ratio
ctx.input_shape = input.size()
ctx.aligned = aligned
output = _C.roi_align_forward(
input, roi, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned
)
return output
def bench():
_C.roi_align_forward(input, boxes, 1.0, 7, 7, 0, True)
torch.cuda.synchronize()
