@jerryzh168
Hi
Is there a solution to fix this issue?
RuntimeError: Could not run 'aten::thnn_conv2d_forward' with arguments from the 'QuantizedCPU' backend.

I am facing the same issue.
efficientNet_unet(
  (pretrained): Module(
    (layer1): Sequential(
      (0): Conv2dSameExport(3, 32, kernel_size=(3, 3), stride=(2, 2), bias=False)
      (1): QuantizedBatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
      (2): QuantizedReLU6(inplace=True)
      (3): Sequential(
        (0): DepthwiseSeparableConv(
          (conv_dw): QuantizedConv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), scale=0.5102088451385498, zero_point=58, padding=(1, 1), groups=32, bias=False)
          (bn1): QuantizedBatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)
          (act1): QuantizedReLU6(inplace=True)
.......
)
  (quant): Quantize(scale=tensor([0.0375]), zero_point=tensor([57]), dtype=torch.quint8)
  (dequant): DeQuantize()

The log shows the issue happens at layer1.
Could this be related to Conv2dSameExport?