From 96d787f5a8cf13d7cf650a3fe88bdfc16f548b51 Mon Sep 17 00:00:00 2001
From: lucas_miranda <lucasmiranda42@gmail.com>
Date: Tue, 13 Apr 2021 20:40:21 +0200
Subject: [PATCH] Added extra branch to main autoencoder for rule_based
prediction
---
deepof/train_model.py | 4 ++--
deepof/train_utils.py | 15 +++++++++------
tests/test_train_utils.py | 20 ++++++++++++--------
3 files changed, 23 insertions(+), 16 deletions(-)
diff --git a/deepof/train_model.py b/deepof/train_model.py
index b32449b4..e7fe0010 100644
--- a/deepof/train_model.py
+++ b/deepof/train_model.py
@@ -397,8 +397,8 @@ else:
variational=variational,
entropy_samples=entropy_samples,
entropy_knn=entropy_knn,
- phenotype_class=pheno_class,
- predictor=predictor,
+ phenotype_prediction=pheno_class,
+ next_sequence_prediction=predictor,
loss=loss,
logparam=logparam,
outpath=output_path,
diff --git a/deepof/train_utils.py b/deepof/train_utils.py
index 951e0cf6..1230498a 100644
--- a/deepof/train_utils.py
+++ b/deepof/train_utils.py
@@ -69,8 +69,9 @@ def get_callbacks(
X_train: np.array,
batch_size: int,
variational: bool,
- phenotype_class: float,
- predictor: float,
+ phenotype_prediction: float,
+ next_sequence_prediction: float,
+ rule_based_prediction: float,
loss: str,
X_val: np.array = None,
cp: bool = False,
@@ -97,8 +98,9 @@ def get_callbacks(
run_ID = "{}{}{}{}{}{}{}_{}".format(
("GMVAE" if variational else "AE"),
- ("_Pred={}".format(predictor) if predictor > 0 and variational else ""),
- ("_Pheno={}".format(phenotype_class) if phenotype_class > 0 else ""),
+ ("_NextSeqPred={}".format(next_sequence_prediction) if next_sequence_prediction > 0 and variational else ""),
+ ("_PhenoPred={}".format(phenotype_prediction) if phenotype_prediction > 0 else ""),
+ ("_RuleBasedPred={}".format(rule_based_prediction) if rule_based_prediction > 0 else ""),
("_loss={}".format(loss) if variational else ""),
("_encoding={}".format(logparam["encoding"]) if logparam is not None else ""),
("_k={}".format(logparam["k"]) if logparam is not None else ""),
@@ -295,8 +297,9 @@ def autoencoder_fitting(
batch_size=batch_size,
cp=save_checkpoints,
variational=variational,
- phenotype_class=phenotype_prediction,
- predictor=next_sequence_prediction,
+ next_sequence_prediction=next_sequence_prediction,
+ phenotype_prediction=phenotype_prediction,
+ rule_based_prediction=rule_based_prediction,
loss=loss,
entropy_samples=entropy_samples,
entropy_knn=entropy_knn,
diff --git a/tests/test_train_utils.py b/tests/test_train_utils.py
index b30d3f67..47c34232 100644
--- a/tests/test_train_utils.py
+++ b/tests/test_train_utils.py
@@ -42,24 +42,27 @@ def test_load_treatments():
),
batch_size=st.integers(min_value=128, max_value=512),
loss=st.one_of(st.just("test_A"), st.just("test_B")),
- predictor=st.floats(min_value=0.0, max_value=1.0),
- pheno_class=st.floats(min_value=0.0, max_value=1.0),
+ next_sequence_prediction=st.floats(min_value=0.0, max_value=1.0),
+ phenotype_prediction=st.floats(min_value=0.0, max_value=1.0),
+ rule_based_prediction=st.floats(min_value=0.0, max_value=1.0),
variational=st.booleans(),
)
def test_get_callbacks(
X_train,
batch_size,
variational,
- predictor,
- pheno_class,
+ next_sequence_prediction,
+ phenotype_prediction,
+ rule_based_prediction,
loss,
):
callbacks = deepof.train_utils.get_callbacks(
X_train=X_train,
batch_size=batch_size,
variational=variational,
- phenotype_class=pheno_class,
- predictor=predictor,
+ next_sequence_prediction=next_sequence_prediction,
+ phenotype_prediction=phenotype_prediction,
+ rule_based_prediction=rule_based_prediction,
loss=loss,
X_val=X_train,
cp=True,
@@ -174,8 +177,9 @@ def test_tune_search(
X_train=X_train,
batch_size=batch_size,
variational=(hypermodel == "S2SGMVAE"),
- phenotype_class=0,
- predictor=predictor,
+ next_sequence_prediction=next_sequence_prediction,
+ phenotype_prediction=phenotype_prediction,
+ rule_based_prediction=rule_based_prediction,
loss=loss,
X_val=X_train,
cp=False,
--
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