code: def test(table, kernel_size, block_ratio=5, device=None):
      x = th.randn(32, 32, 1024 * 10).to(device)
      w = th.randn(64, 32, kernel_size).to(device)
  
      with Chrono() as chrono_ref:
          y_ref = F.conv1d(x, w)
  
      with Chrono() as chrono_fft:
          y_fft = fft_conv1d(x, w, block_ratio=block_ratio)
  
      delta = format((y_ref - y_fft).abs().mean(), ".1e")
      table.line(
          [
              kernel_size,
              int(1000 * chrono_fft.duration),
              int(1000 * chrono_ref.duration),
              delta,
          ]
      )
  
imports: import argparse
  import torch
  from torch.nn import functional
  from julius import fft_conv1d
  from julius.utils import Chrono, MarkdownTable
label_desc: Use image node_id 1 for calling a global function with example usage: test(table, kernel_size, block_ratio, device) without return types