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Lucas Miranda
deepOF
Commits
ff091f9a
Commit
ff091f9a
authored
Feb 12, 2021
by
lucas_miranda
Browse files
Added latent regularization control to deepof.data.coordinates.deep_unsupervised_embedding()
parent
33a4fa0a
Pipeline
#93315
canceled with stage
in 9 minutes and 30 seconds
Changes
5
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
deepof/train_model.py
View file @
ff091f9a
...
...
@@ -183,14 +183,6 @@ parser.add_argument(
type
=
float
,
default
=
0.99
,
)
parser
.
add_argument
(
"--stability-check"
,
"-s"
,
help
=
"Sets the number of times that the model is trained and initialised. "
"If greater than 1 (the default), saves the cluster assignments to a dataframe on disk"
,
type
=
int
,
default
=
1
,
)
parser
.
add_argument
(
"--train-path"
,
"-tp"
,
help
=
"set training set path"
,
type
=
str
)
parser
.
add_argument
(
"--val-num"
,
...
...
@@ -243,7 +235,6 @@ output_path = os.path.join(args.output_path)
overlap_loss
=
args
.
overlap_loss
pheno_class
=
float
(
args
.
phenotype_classifier
)
predictor
=
float
(
args
.
predictor
)
runs
=
args
.
stability_check
smooth_alpha
=
args
.
smooth_alpha
train_path
=
os
.
path
.
abspath
(
args
.
train_path
)
tune
=
args
.
hyperparameter_tuning
...
...
@@ -287,7 +278,7 @@ project_coords = project(
animal_ids
=
tuple
([
animal_id
]),
arena
=
"circular"
,
arena_dims
=
tuple
([
arena_dims
]),
enable_iterative_imputation
=
Tru
e
,
enable_iterative_imputation
=
Fals
e
,
exclude_bodyparts
=
exclude_bodyparts
,
exp_conditions
=
treatment_dict
,
path
=
train_path
,
...
...
@@ -357,6 +348,10 @@ print("Done!")
# as many times as specified by runs
if
not
tune
:
print
(
latent_reg
)
print
((
"categorical"
in
latent_reg
))
print
((
"variance"
in
latent_reg
))
trained_models
=
project_coords
.
deep_unsupervised_embedding
(
(
X_train
,
y_train
,
X_val
,
y_val
),
batch_size
=
batch_size
,
...
...
deepof/train_utils.py
View file @
ff091f9a
...
...
@@ -430,7 +430,7 @@ def autoencoder_fitting(
)
if
save_weights
:
ae
.
save_weights
(
"{}_final_weights.h5"
.
format
(
run_ID
))
ae
.
save_weights
(
"{}
{}
_final_weights.h5"
.
format
(
output_path
,
run_ID
))
if
log_hparams
:
# Logparams to tensorboard
...
...
deepof_experiments.smk
View file @
ff091f9a
...
...
@@ -99,9 +99,8 @@ rule latent_regularization_experiments:
"--encoding-size {wildcards.encs} "
"--batch-size 256 "
"--window-size 24 "
"--window-step
6
"
"--window-step
12
"
"--exclude-bodyparts Tail_base,Tail_1,Tail_2,Tail_tip "
"--stability-check 3 "
"--output-path {outpath}latent_regularization_experiments"
#
#
...
...
tests/test_build_hypermodels.py
View file @
ff091f9a
...
...
@@ -35,7 +35,7 @@ def test_SEQ_2_SEQ_AE_hypermodel_build(input_shape):
@
given
(
encoding_size
=
st
.
integers
(
min_value
=
2
,
max_value
=
16
),
loss
=
st
.
one_of
(
st
.
just
(
"ELBO"
),
st
.
just
(
"MMD"
),
st
.
just
(
"ELBO+MMD"
)),
number_of_components
=
st
.
integers
(
min_value
=
1
,
max_value
=
5
),
n
o
umber_of_components
=
st
.
integers
(
min_value
=
1
,
max_value
=
5
),
)
def
test_SEQ_2_SEQ_GMVAE_hypermodel_build
(
encoding_size
,
...
...
tests/test_train_utils.py
View file @
ff091f9a
...
...
@@ -75,7 +75,16 @@ def test_get_callbacks(
loss
,
):
runID
,
tbc
,
cycle1c
,
cpc
=
deepof
.
train_utils
.
get_callbacks
(
X_train
,
batch_size
,
True
,
variational
,
pheno_class
,
predictor
,
loss
,
None
X_train
,
batch_size
,
True
,
variational
,
pheno_class
,
predictor
,
loss
,
True
,
True
,
None
,
)
assert
type
(
runID
)
==
str
assert
type
(
tbc
)
==
tf
.
keras
.
callbacks
.
TensorBoard
...
...
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