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@ -53,7 +53,6 @@ class KPCNN(nn.Module):
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break
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break
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# Apply the good block function defining tf ops
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# Apply the good block function defining tf ops
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print(block, r)
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self.block_ops.append(block_decider(block,
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self.block_ops.append(block_decider(block,
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r,
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r,
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in_dim,
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in_dim,
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@ -331,7 +330,6 @@ class KPFCNN(nn.Module):
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if block_i in self.encoder_skips:
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if block_i in self.encoder_skips:
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skip_x.append(x)
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skip_x.append(x)
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x = block_op(x, batch)
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x = block_op(x, batch)
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print(block_op)
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for block_i, block_op in enumerate(self.decoder_blocs):
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for block_i, block_op in enumerate(self.decoder_blocs):
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if block_i in self.decoder_concats:
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if block_i in self.decoder_concats:
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@ -356,7 +356,9 @@ class KPConv(nn.Module):
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return torch.sum(kernel_outputs, dim=0)
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return torch.sum(kernel_outputs, dim=0)
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def __repr__(self):
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def __repr__(self):
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return "KPConv(radius: %.2f, in_feat: %i, out_feat: %i)"% (self.radius, self.in_channels, self.out_channels)
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return 'KPConv(radius: {:.2f}, in_feat: {:d}, out_feat: {:d})'.format(self.radius,
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self.in_channels,
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self.out_channels)
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# ----------------------------------------------------------------------------------------------------------------------
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# ----------------------------------------------------------------------------------------------------------------------
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#
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#
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