Use SELU instead of ReLU
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6d31ab3a13
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@ -36,14 +36,10 @@ class ConstellationNet(nn.Module):
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for layer_size in encoder_layers_sizes:
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for layer_size in encoder_layers_sizes:
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encoder_layers.append(nn.Linear(prev_layer_size, layer_size))
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encoder_layers.append(nn.Linear(prev_layer_size, layer_size))
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encoder_layers.append(nn.ReLU())
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encoder_layers.append(nn.SELU())
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prev_layer_size = layer_size
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prev_layer_size = layer_size
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encoder_layers += [
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encoder_layers.append(nn.Linear(prev_layer_size, 2))
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nn.Linear(prev_layer_size, 2),
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nn.ReLU(),
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nn.BatchNorm1d(2),
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]
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self.encoder = nn.Sequential(*encoder_layers)
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self.encoder = nn.Sequential(*encoder_layers)
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self.channel = channel_model
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self.channel = channel_model
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@ -57,7 +53,7 @@ class ConstellationNet(nn.Module):
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for layer_size in decoder_layers_sizes:
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for layer_size in decoder_layers_sizes:
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decoder_layers.append(nn.Linear(prev_layer_size, layer_size))
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decoder_layers.append(nn.Linear(prev_layer_size, layer_size))
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decoder_layers.append(nn.ReLU())
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decoder_layers.append(nn.SELU())
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prev_layer_size = layer_size
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prev_layer_size = layer_size
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# Softmax is not used at the end of the network because the
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# Softmax is not used at the end of the network because the
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