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import torch.nn as nn |
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import torch.nn.functional as F |
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class MLP(nn.Module): |
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""" Very simple multi-layer perceptron (also called FFN)""" |
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def __init__(self, input_dim, hidden_dim, output_dim, num_layers): |
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super(MLP, self).__init__() |
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self.output_dim = output_dim |
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self.num_layers = num_layers |
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h = [hidden_dim] * (num_layers - 1) |
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self.layers = nn.ModuleList(nn.Linear(n, k) for n, k in zip([input_dim] + h, h + [output_dim])) |
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def forward(self, x): |
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B, N, D = x.size() |
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x = x.reshape(B*N, D) |
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for i, layer in enumerate(self.layers): |
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x = F.relu(layer(x)) if i < self.num_layers - 1 else layer(x) |
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x = x.view(B, N, self.output_dim) |
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return x |
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