Commit 30d5c30e authored by lucas_miranda's avatar lucas_miranda
Browse files

Added extra branch to main autoencoder for rule_based prediction

parent ff1f28eb
Pipeline #98491 canceled with stages
in 6 minutes and 1 second
......@@ -71,7 +71,9 @@ def test_one_cycle_scheduler():
max_rate=0.005,
)
fit = test_model.fit(X, y, callbacks=[onecycle], epochs=10, batch_size=100)
fit = test_model.fit(
X, y, callbacks=[onecycle], epochs=10, batch_size=100, verbose=0
)
assert isinstance(fit, tf.keras.callbacks.History)
assert onecycle.history["lr"][4] > onecycle.history["lr"][1]
assert onecycle.history["lr"][4] > onecycle.history["lr"][-1]
......@@ -101,7 +103,7 @@ def test_uncorrelated_features_constraint():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, y, epochs=25, batch_size=100)
fit = test_model.fit(X, y, epochs=25, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
correlations.append(np.mean(np.corrcoef(test_model.get_weights()[0])))
......@@ -123,7 +125,7 @@ def test_MCDropout():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, y, epochs=10, batch_size=100)
fit = test_model.fit(X, y, epochs=10, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
......@@ -144,7 +146,7 @@ def test_dense_transpose():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, y, epochs=10, batch_size=100)
fit = test_model.fit(X, y, epochs=10, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
......@@ -188,7 +190,7 @@ def test_KLDivergenceLayer():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, [y, y], epochs=1, batch_size=100)
fit = test_model.fit(X, [y, y], epochs=1, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
assert test_model.losses[0] == test_model.losses[1]
......@@ -233,7 +235,7 @@ def test_MMDiscrepancyLayer():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, y, epochs=10, batch_size=100)
fit = test_model.fit(X, y, epochs=10, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
......@@ -251,7 +253,7 @@ def test_dead_neuron_control():
optimizer=tf.keras.optimizers.SGD(),
)
fit = test_model.fit(X, y, epochs=10, batch_size=100)
fit = test_model.fit(X, y, epochs=10, batch_size=100, verbose=0)
assert isinstance(fit, tf.keras.callbacks.History)
......@@ -281,6 +283,6 @@ def test_neighbor_latent_entropy():
X,
X,
callbacks=deepof.model_utils.neighbor_latent_entropy(
k=10, encoding_dim=6, validation_data=X, variational=True
k=10, encoding_dim=6, validation_data=X, variational=True, verbose=0
),
)
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