Commit a7d35d3a authored by lucas_miranda's avatar lucas_miranda
Browse files

Updated hyperparameter_tuning.py to use the latest version of hypermodels.py

parent 93397d23
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......@@ -265,11 +265,12 @@ class SEQ_2_SEQ_GMVAE(HyperModel):
Model_B3 = BatchNormalization()
Model_B4 = BatchNormalization()
Model_D1 = Dense(DENSE_2, activation="relu", kernel_initializer=he_uniform())
Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=DENSE_1,)
Model_D2 = Dense(DENSE_1, activation="relu", kernel_initializer=he_uniform())
# Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=DENSE_1,)
Model_D3 = RepeatVector(self.input_shape[1])
Model_D4 = Bidirectional(
LSTM(
LSTM_units_1,
LSTM_units_2,
activation="tanh",
return_sequences=True,
kernel_constraint=UnitNorm(axis=1),
......@@ -427,4 +428,4 @@ class SEQ_2_SEQ_GMVAE(HyperModel):
experimental_run_tf_function=False,
)
return gmvaep, kl_warmup_callback, mmd_warmup_callback
return gmvaep # , kl_warmup_callback, mmd_warmup_callback
......@@ -251,11 +251,13 @@ class SEQ_2_SEQ_GMVAE:
Model_D1 = Dense(
self.DENSE_2, activation="relu", kernel_initializer=he_uniform()
)
Model_D2 = DenseTranspose(Model_E3, activation="relu", output_dim=self.DENSE_1,)
Model_D2 = Dense(
self.DENSE_1, activation="relu", kernel_initializer=he_uniform()
)
Model_D3 = RepeatVector(self.input_shape[1])
Model_D4 = Bidirectional(
LSTM(
self.LSTM_units_1,
self.LSTM_units_2,
activation="tanh",
return_sequences=True,
kernel_constraint=UnitNorm(axis=1),
......
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