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import torch.nn as nn
class EmbeddingNetwork1(nn.Module):
def __init__(self, dim=5):
super().__init__()
self.emb = nn.Embedding(10, dim)
self.lin1 = nn.Linear(dim, 1)
self.seq = nn.Sequential(
self.emb,
self.lin1,
)
def forward(self, input):
return self.seq(input)
class EmbeddingNetwork2(nn.Module):
def __init__(self, in_space=10, dim=3):
super().__init__()
self.embedding = nn.Embedding(in_space, dim)
self.seq = nn.Sequential(self.embedding, nn.Linear(dim, 1), nn.Sigmoid())
def forward(self, indices):
return self.seq(indices)
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