first commit

MobileNetV3/models/regressor.py

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+import torch
+import torch.nn as nn
+import torch.optim as optim
+
+from . import utils
+
+@utils.register_model(name='MLPRegressor')
+class MLPRegressor(nn.Module):
+    # def __init__(self, input_size, hidden_size, output_size):
+    def __init__(self, config):
+        super().__init__()
+        input_size = int(config.data.max_node * config.data.n_vocab)
+        hidden_size = config.model.hidden_size
+        output_size = config.model.output_size
+        self.fc1 = nn.Linear(input_size, hidden_size)
+        self.fc2 = nn.Linear(hidden_size, hidden_size)
+        self.fc3 = nn.Linear(hidden_size, hidden_size)
+        self.fc4 = nn.Linear(hidden_size, output_size)
+        self.activation = nn.ReLU()
+
+    def forward(self, X, time_cond, maskX):
+        x = X.view(X.size(0), -1)
+        x = self.activation(self.fc1(x))
+        x= self.activation(self.fc2(x))
+        x= self.activation(self.fc3(x))
+        x= self.fc4(x)
+        return x