Confusion about palette output dimensions

[BCL123456-BAL]

models/palette_tensoRF.py
class PLTRender(torch.nn.Module):
def init():
self.n_dim = 3 + len_palette
......
layer1 = torch.nn.Linear(self.in_mlpC, featureC)
layer2 = torch.nn.Linear(featureC, featureC)
layer3 = torch.nn.Linear(featureC, len_palette - 1)
torch.nn.init.constant_(layer3.bias, 0)
self.mlp = torch.nn.Sequential(
layer1, torch.nn.LeakyReLU(inplace=True),
layer2, torch.nn.LeakyReLU(inplace=True),
layer3)
self.n_dim += 1
I recently tried to integrate this work of yours on instant-ngp.
But I do not understand the role of self.n_dim, and why the output dimension of layer3 is len_palette - 1.
Besides，why is the activation function after each layer LeakyReLU, and the Relu function is also used in TensoRF.

Hope you can help me

Best wish！

[yuehaowang]

Thanks for your question.

1. n_dim is the total number of output channels, including color, palette weights, sparsity, etc.
2. Since the weight of the last palette color is computed from other weights through alpha blending, the MLP layers only need to output len_palette - 1 channels.
3. I think both LeakyReLU and ReLU could work.