RuntimeError: Given input size: (576x27x27). Calculated output size: (576x-1x-1). Output size is too small

[Lily1992]

I got the error when i use the model of mobilenetv3_small to train,and i used my own dataset like as VOC. Would you give me some advice?
And,would you tell me the torch version and torchvision version?

[aviaisr]

I'm having the same issue. Were you able to overcome that?

[Mr Rotten peach]

Maybe you need to modify here, mobilenetv3_seg.py script
around 60 line

class _LRASPP(nn.Module):
"""Lite R-ASPP"""

def __init__(self, in_channels, norm_layer, **kwargs):
    super(_LRASPP, self).__init__()
    out_channels = 128
    self.b0 = nn.Sequential(
        nn.Conv2d(in_channels, out_channels, 1, bias=False),
        norm_layer(out_channels),
        nn.ReLU(True)
    )
    self.b1 = nn.Sequential(
        nn.AdaptiveAvgPool2d((8, 8)),  
        # nn.AvgPool2d(kernel_size=(49, 49), stride=(16, 20)),  # check it
        nn.Conv2d(in_channels, out_channels, 1, bias=False),
        nn.Sigmoid(),
    )

[aviaisr]

@raysue Thanks! This has fixed the issue!

[Yuan]

I encountered same error and have no idea why and modify it according @raysue then it works.

[sungh66]

When i exported onnx model, onnx cannot surpport adaptive_avg_pool2d.How can i fix the problem?

[Mr Rotten peach]

When i exported onnx model, onnx cannot surpport adaptive_avg_pool2d.How can i fix the problem?

upgrade your onnx version, use opset=13 or fix your input size use nn.AvgPool2d with suitable parameters : kernel_size and stride