From d207cd1d5689f8ff95e9395a24c13f4e17425d83 Mon Sep 17 00:00:00 2001
From: lucas_miranda <lucasmiranda42@gmail.com>
Date: Mon, 16 Nov 2020 22:14:31 +0100
Subject: [PATCH] Updated train_model.py to be compatible with phenotype
classification
---
deepof/train_model.py | 3 +--
deepof/train_utils.py | 28 +++++++++++++++++++---------
2 files changed, 20 insertions(+), 11 deletions(-)
diff --git a/deepof/train_model.py b/deepof/train_model.py
index 2448108a..122555f0 100644
--- a/deepof/train_model.py
+++ b/deepof/train_model.py
@@ -411,8 +411,7 @@ else:
)
best_hyperparameters, best_model = tune_search(
- X_train,
- X_val,
+ data=[X_train, y_train, X_val, y_val],
bayopt_trials=bayopt_trials,
hypermodel=hyp,
k=k,
diff --git a/deepof/train_utils.py b/deepof/train_utils.py
index 000f52ad..b545268f 100644
--- a/deepof/train_utils.py
+++ b/deepof/train_utils.py
@@ -97,8 +97,7 @@ def get_callbacks(
def tune_search(
- train: np.array,
- test: np.array,
+ data: List[np.array],
bayopt_trials: int,
hypermodel: str,
k: int,
@@ -139,12 +138,14 @@ def tune_search(
"""
+ X_train, y_train, X_val, y_val = data
+
if hypermodel == "S2SAE": # pragma: no cover
- hypermodel = deepof.hypermodels.SEQ_2_SEQ_AE(input_shape=train.shape)
+ hypermodel = deepof.hypermodels.SEQ_2_SEQ_AE(input_shape=X_train.shape)
elif hypermodel == "S2SGMVAE":
hypermodel = deepof.hypermodels.SEQ_2_SEQ_GMVAE(
- input_shape=train.shape,
+ input_shape=X_train.shape,
loss=loss,
number_of_components=k,
overlap_loss=overlap_loss,
@@ -168,13 +169,22 @@ def tune_search(
print(tuner.search_space_summary())
+ Xs, ys = [X_train], [X_train]
+ Xvals, yvals = [X_val], [X_val]
+
+ if predictor > 0.0:
+ Xs, ys = X_train[:-1], [X_train[:-1], X_train[1:]]
+ Xvals, yvals = X_val[:-1], [X_val[:-1], X_val[1:]]
+
+ if pheno_class > 0.0:
+ ys += [y_train]
+ yvals += [y_val]
+
tuner.search(
- train if predictor == 0 else [train[:-1]],
- train if predictor == 0 else [train[:-1], train[1:]],
+ Xs,
+ ys,
epochs=n_epochs,
- validation_data=(
- (test, test) if predictor == 0 else (test[:-1], [test[:-1], test[1:]])
- ),
+ validation_data=(Xvals, yvals),
verbose=1,
batch_size=256,
callbacks=callbacks,
--
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