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Commit 30d50a18 authored by Geoffrey Yu's avatar Geoffrey Yu
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remove some the printed out messages

parent 1b4fc115
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openfold/utils/loss.py
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...@@ -1606,7 +1606,6 @@ def masked_msa_loss(logits, true_msa, bert_mask, num_classes, eps=1e-8, **kwargs ...@@ -1606,7 +1606,6 @@ def masked_msa_loss(logits, true_msa, bert_mask, num_classes, eps=1e-8, **kwargs
Returns: Returns:
Masked MSA loss Masked MSA loss
""" """
print(f"line 1609 logits shape: {logits.shape} and num_classes: {num_classes}")
errors = softmax_cross_entropy( errors = softmax_cross_entropy(
logits, torch.nn.functional.one_hot(true_msa, num_classes=num_classes) logits, torch.nn.functional.one_hot(true_msa, num_classes=num_classes)
) )
...@@ -1997,7 +1996,6 @@ class AlphaFoldLoss(nn.Module): ...@@ -1997,7 +1996,6 @@ class AlphaFoldLoss(nn.Module):
loss = loss.new_tensor(0., requires_grad=True) loss = loss.new_tensor(0., requires_grad=True)
cum_loss = cum_loss + weight * loss cum_loss = cum_loss + weight * loss
losses[loss_name] = loss.detach().clone() losses[loss_name] = loss.detach().clone()
losses["unscaled_loss"] = cum_loss.detach().clone() losses["unscaled_loss"] = cum_loss.detach().clone()
# Scale the loss by the square root of the minimum of the crop size and # Scale the loss by the square root of the minimum of the crop size and
......
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