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