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Lucas Miranda
deepOF
Commits
f0902fce
Commit
f0902fce
authored
Apr 16, 2021
by
lucas_miranda
Browse files
Added extra branch to main autoencoder for rule_based prediction
parent
b35d840c
Pipeline
#99821
failed with stages
in 17 minutes and 25 seconds
Changes
5
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deepof/models.py
View file @
f0902fce
...
...
@@ -341,11 +341,11 @@ class SEQ_2_SEQ_GMVAE:
"bidirectional_merge"
:
"concat"
,
"clipvalue"
:
1.0
,
"dense_activation"
:
"relu"
,
"dense_layers_per_branch"
:
1
,
"dense_layers_per_branch"
:
3
,
"dropout_rate"
:
0.05
,
"learning_rate"
:
1e-3
,
"units_conv"
:
64
,
"units_dense2"
:
64
,
"units_dense2"
:
32
,
"units_lstm"
:
128
,
}
...
...
@@ -399,23 +399,15 @@ class SEQ_2_SEQ_GMVAE:
use_bias
=
True
,
)
# Nested list comprehension adding a series of dense and batch norm layers
Model_E4
=
[
i
for
s
in
[
[
Dense
(
self
.
DENSE_2
,
activation
=
self
.
dense_activation
,
# kernel_constraint=UnitNorm(axis=0),
kernel_initializer
=
he_uniform
(),
use_bias
=
True
,
),
BatchNormalization
(),
]
for
_
in
range
(
self
.
dense_layers_per_branch
)
]
for
i
in
s
Dense
(
self
.
DENSE_2
,
activation
=
self
.
dense_activation
,
# kernel_constraint=UnitNorm(axis=0),
kernel_initializer
=
he_uniform
(),
use_bias
=
True
,
)
for
_
in
range
(
self
.
dense_layers_per_branch
)
]
# Decoder layers
...
...
deepof/train_utils.py
View file @
f0902fce
...
...
@@ -103,6 +103,7 @@ def get_callbacks(
run_ID
=
"{}{}{}{}{}{}{}{}{}{}{}{}"
.
format
(
(
"GMVAE"
if
variational
else
"AE"
),
(
"_input_type={}"
.
format
(
input_type
)
if
input_type
else
"coords"
),
(
"_window_size={}"
,
format
(
X_train
.
shape
[
1
])),
(
"_NextSeqPred={}"
.
format
(
next_sequence_prediction
)
if
variational
else
""
),
(
"_PhenoPred={}"
.
format
(
phenotype_prediction
)
if
variational
else
""
),
(
"_RuleBasedPred={}"
.
format
(
rule_based_prediction
)
if
variational
else
""
),
...
...
deepof_experiments.smk
View file @
f0902fce
...
...
@@ -23,6 +23,7 @@ entropy_knn = [100]
next_sequence_pred_weights = [0.0, 0.15]
phenotype_pred_weights = [0.0]
rule_based_pred_weights = [0.0, 0.15]
window_lengths = range(11,56,11)
input_types = ["coords"]
run = list(range(1, 11))
...
...
@@ -47,6 +48,7 @@ rule deepof_experiments:
expand(
outpath + "train_models/trained_weights/"
"GMVAE_input_type={input_type}_"
"window_size={window_size}_"
"NextSeqPred={nspredweight}_"
"PhenoPred={phenpredweight}_"
"RuleBasedPred={rulesweight}_"
...
...
@@ -58,6 +60,7 @@ rule deepof_experiments:
"run={run}_"
"final_weights.h5",
input_type=input_types,
window_size=window_lengths,
loss=losses,
encs=encodings,
k=cluster_numbers,
...
...
@@ -121,6 +124,7 @@ rule train_models:
output:
trained_models=outpath + "train_models/trained_weights/"
"GMVAE_input_type={input_type}_"
"window_size={window_size}_"
"NextSeqPred={nspredweight}_"
"PhenoPred={phenpredweight}_"
"RuleBasedPred={rulesweight}_"
...
...
@@ -149,7 +153,7 @@ rule train_models:
"--encoding-size {wildcards.encs} "
"--entropy-knn {wildcards.entknn} "
"--batch-size 256 "
"--window-size
24
"
"--window-step 1
2
"
"--window-size
{window_size}
"
"--window-step 1
1
"
"--run {wildcards.run} "
"--output-path {outpath}train_models"
supplementary_notebooks/deepof_explore_model_stability.ipynb
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f0902fce
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supplementary_notebooks/deepof_model_evaluation.ipynb
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f0902fce
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