diff --git a/source/hypermodels.py b/source/hypermodels.py index 6ff6daf768c3b05bcbe5f2a68c0d95ab77ebd454..23f4f482b713fa6835ef568e67460ac2162e67e5 100644 --- a/source/hypermodels.py +++ b/source/hypermodels.py @@ -72,9 +72,9 @@ class SEQ_2_SEQ_AE(HyperModel): ) # Decoder layers - Model_D0 = DenseTranspose(Model_E5, activation="relu", input_shape=(ENCODING,), output_dim=64) - Model_D1 = DenseTranspose(Model_E4, activation="relu", output_dim=128) - Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=256) + Model_D0 = DenseTranspose(Model_E5, activation="relu", output_dim=ENCODING) + Model_D1 = DenseTranspose(Model_E4, activation="relu", output_dim=DENSE_2) + Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=DENSE_1) Model_D3 = RepeatVector(self.input_shape[1]) Model_D4 = Bidirectional( LSTM( diff --git a/source/models.py b/source/models.py index 572445aa659304e38dcfd43274b8bb9f181e9d66..49e196ba350b844c33d31184c2a693b54b1204e9 100644 --- a/source/models.py +++ b/source/models.py @@ -72,9 +72,9 @@ class SEQ_2_SEQ_AE: ) # Decoder layers - Model_D0 = Dense(self.DENSE_2, activation="relu") - Model_D1 = Dense(self.DENSE_1, activation="relu") - Model_D2 = Dense(self.DENSE_1, activation="relu") + Model_D0 = DenseTranspose(Model_E5, activation="relu", output_dim=self.ENCODING) + Model_D1 = DenseTranspose(Model_E4, activation="relu", output_dim=self.DENSE_2) + Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=self.DENSE_1) Model_D3 = RepeatVector(self.input_shape[1]) Model_D4 = Bidirectional( LSTM( @@ -189,9 +189,9 @@ class SEQ_2_SEQ_VAE: # Decoder layers - Model_D0 = Dense(self.DENSE_2, activation="relu") - Model_D1 = Dense(self.DENSE_1, activation="relu") - Model_D2 = Dense(self.DENSE_1, activation="relu") + Model_D0 = DenseTranspose(Model_E5, activation="relu", output_dim=self.ENCODING) + Model_D1 = DenseTranspose(Model_E4, activation="relu", output_dim=self.DENSE_2) + Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=self.DENSE_1) Model_D3 = RepeatVector(self.input_shape[1]) Model_D4 = Bidirectional( LSTM(