Commit 60cb0f7b authored by lucas_miranda's avatar lucas_miranda
Browse files

Updated requirements.txt

parent 90a9c9df
Pipeline #87999 failed with stage
in 14 minutes and 44 seconds
......@@ -106,31 +106,21 @@ class SEQ_2_SEQ_GMVAE(HyperModel):
"""Retrieve hyperparameters to tune"""
# Architectural hyperparameters
clipvalue = hp.Float(
"clipvalue", min_value=0.0, max_value=1.0, default=0.5, sampling="Linear"
)
conv_filters = hp.Int(
"units_conv", min_value=128, max_value=160, step=16, default=128,
)
dense_2 = hp.Int(
"units_dense2", min_value=120, max_value=180, step=10, default=150,
)
dense_activation = hp.Choice("dense_activation", values=["elu", "relu"])
dense_layers_per_branch = hp.Int("dense_layers_per_branch", min_value=1, max_value=3, default=1)
dropout_rate = hp.Float(
"dropout_rate",
min_value=0.0,
max_value=0.15,
default=0.0,
sampling="linear",
bidirectional_merge = hp.Choice(
"bidirectional_merge", values=["sum", "mul", "concat", "ave"]
)
clipvalue = hp.Choice("clipvalue", values=[1.0, None])
conv_filters = 160
dense_2 = 120
dense_activation = "relu"
dense_layers_per_branch = 1
dropout_rate = 1e-3
encoding = 16
k = self.number_of_components
lstm_units_1 = hp.Int(
"units_lstm", min_value=300, max_value=350, step=10, default=320,
)
lstm_units_1 = 300
return (
bidirectional_merge,
clipvalue,
conv_filters,
dense_2,
......@@ -147,6 +137,7 @@ class SEQ_2_SEQ_GMVAE(HyperModel):
# Hyperparameters to tune
(
bidirectional_merge,
clipvalue,
conv_filters,
dense_2,
......@@ -160,10 +151,11 @@ class SEQ_2_SEQ_GMVAE(HyperModel):
gmvaep, kl_warmup_callback, mmd_warmup_callback = deepof.models.SEQ_2_SEQ_GMVAE(
architecture_hparams={
"bidirectional_merge": "concat",
"clipvalue": clipvalue,
"dense_activation": dense_activation,
"dropout_rate": dropout_rate,
"dense_layers_per_branch": dense_layers_per_branch,
"dropout_rate": dropout_rate,
"encoding": encoding,
"units_conv": conv_filters,
"units_dense_2": dense_2,
......
......@@ -314,15 +314,15 @@ class SEQ_2_SEQ_GMVAE:
"""Sets the default parameters for the model. Overwritable with a dictionary"""
defaults = {
"clipvalue": 0.5,
"dense_activation": "elu",
"clipvalue": 1.0,
"dense_activation": "relu",
"dense_layers_per_branch": 1,
"dropout_rate": 0.15,
"dropout_rate": 1e-3,
"encoding": 16,
"learning_rate": 1e-3,
"units_conv": 256,
"units_dense2": 64,
"units_lstm": 256,
"units_conv": 160,
"units_dense2": 120,
"units_lstm": 300,
}
for k, v in params.items():
......@@ -555,7 +555,7 @@ class SEQ_2_SEQ_GMVAE:
tfd.Independent(
tfd.Normal(
loc=gauss[1][..., : self.ENCODING, k],
scale=softplus(gauss[1][..., self.ENCODING:, k]),
scale=softplus(gauss[1][..., self.ENCODING :, k]),
),
reinterpreted_batch_ndims=1,
)
......
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