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Hi Kai,
Thanks for your great work! I m quite confused that why you still use the MSE loss before the NNFM loss in the style transfer stage in opt_style.py.
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http://codegolf.stackexchange.com/questions/102548/make-me-a-fake-loader
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Can save two bytes if end of program output does not matter.…
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运行到Epoch: 1/50, step: 11/1713, loss: 1.68236, accuracy: 0.13500, mse: 0.32271
就报出下面的错误：
ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray).
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This gives a confusing error message:
{code:r}
> g2 = h2o.getGrid(g, "mse")
Error in as.character.default() :
no method for coercing this S4 class to a vector
{code}
It is expecting g2 = …
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Whenever I try to use a custom VAE I get this error. How do I fix this. This is the custom VAE vae-ft-mse-840000-ema-pruned.safetensors directly from stability.
) that is different to the
input size (torch.Size([10, 1])). This will likely lead to incorrect result…
mw66 updated
4 months ago
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错误：
Epoch: [1003/10] step: [1003/1] G_init time: 0.30186986923217773s, mse: 0.029376816004514694 2019-07-27 20:02:30.701958: W tensorflow/core/framework/op_kernel.cc:1431] OP_REQUIRES failed at itera…
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```python
loss_x = torch.sum(BCELoss(x, tx) / bs * box_loss_scale * mask)
loss_y = torch.sum(BCELoss(y, ty) / bs * box_loss_scale * mask)
```
为什么用MSE来计算，作者用BCE算是有什么考虑吗。