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only train gnn

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luni
2023-02-26 23:24:47 +00:00
parent 716026f0a9
commit c294f1f0b7
4 changed files with 30 additions and 52 deletions
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models/gnn.py
+7 -8
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@@ -16,12 +16,11 @@ class Smoother(tf.keras.Model):
def __init__(self, ):
super().__init__()
self.a = sp_matrix_to_sp_tensor(sio.loadmat("custom_utils/ssmpl0.mat")['L'].tocoo())
self.conv1 = GeneralConv(channels=32, batch_norm=True, dropout=0.1, aggregate='mean', activation='prelu', use_bias=True)
self.conv2 = GeneralConv(channels=128, batch_norm=True, dropout=0.1, aggregate='mean', activation='prelu', use_bias=True)
self.conv3 = GeneralConv(channels=64, batch_norm=True, dropout=0.0, aggregate='mean', activation='prelu', use_bias=True)
self.conv4 = GeneralConv(channels=16, batch_norm=True, dropout=0.0, aggregate='mean', activation='prelu', use_bias=True)
self.conv5 = GCNConv(3, activation='tanh', use_bias=False)
self.conv1 = GCNConv(16, activation='tanh', use_bias=False)
self.conv2 = GCNConv(16, activation='tanh', use_bias=False)
self.conv3 = GCNConv(16, activation='tanh', use_bias=False)
# self.conv4 = GCNConv(16, activation='tanh', use_bias=False)
# self.conv5 = GCNConv(16, activation='tanh', use_bias=False)
self.conv6 = GCNConv(3, activation='tanh', use_bias=False)
def call(self, inputs, training=None):
@@ -29,8 +28,8 @@ class Smoother(tf.keras.Model):
x = self.conv1([x, self.a], training=training)
x = self.conv2([x, self.a], training=training)
x = self.conv3([x, self.a], training=training)
x = self.conv4([x, self.a], training=training)
x = self.conv5([x, self.a], training=training)
# x = self.conv4([x, self.a], training=training)
# x = self.conv5([x, self.a], training=training)
x = self.conv6([x, self.a], training=training)
return x