Safran/KPConv-PyTorch
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HuguesTHOMAS 2020-04-02 17:44:27 -04:00
parent 755317d83a
commit c131638fa7
2 changed files with 3 additions and 3 deletions
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2
models/architectures.py
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@ -53,7 +53,6 @@ class KPCNN(nn.Module):
break break
# Apply the good block function defining tf ops # Apply the good block function defining tf ops
print(block, r)
self.block_ops.append(block_decider(block, self.block_ops.append(block_decider(block,
r, r,
in_dim, in_dim,
@ -331,7 +330,6 @@ class KPFCNN(nn.Module):
if block_i in self.encoder_skips: if block_i in self.encoder_skips:
skip_x.append(x) skip_x.append(x)
x = block_op(x, batch) x = block_op(x, batch)
print(block_op)
for block_i, block_op in enumerate(self.decoder_blocs): for block_i, block_op in enumerate(self.decoder_blocs):
if block_i in self.decoder_concats: if block_i in self.decoder_concats:

4
models/blocks.py
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@ -356,7 +356,9 @@ class KPConv(nn.Module):
return torch.sum(kernel_outputs, dim=0) return torch.sum(kernel_outputs, dim=0)
def __repr__(self): def __repr__(self):
return "KPConv(radius: %.2f, in_feat: %i, out_feat: %i)"% (self.radius, self.in_channels, self.out_channels) return 'KPConv(radius: {:.2f}, in_feat: {:d}, out_feat: {:d})'.format(self.radius,
self.in_channels,
self.out_channels)
# ---------------------------------------------------------------------------------------------------------------------- # ----------------------------------------------------------------------------------------------------------------------
# #