Refactored train_utils.py

deepof/train_utils.py

@@ -139,7 +139,7 @@ def get_callbacks(
     return callbacks
 
 
-def log_hyperparameters():
+def log_hyperparameters(phenotype_class):
     """Blueprint for hyperparameter and metric logging in tensorboard during hyperparameter tuning"""
 
     logparams = [
@@ -288,7 +288,7 @@ def autoencoder_fitting(
 
     # Logs hyperparameters to tensorboard
     if log_hparams:
-        logparams, metrics = log_hyperparameters()
+        logparams, metrics = log_hyperparameters(phenotype_class)
 
         with tf.summary.create_file_writer(
             os.path.join(output_path, "hparams", run_ID)

tests/test_train_utils.py

@@ -9,7 +9,7 @@ Testing module for deepof.train_utils
 """
 
 from hypothesis import given
-from hypothesis import settings
+from hypothesis import settings, reproduce_failure
 from hypothesis import strategies as st
 from hypothesis.extra.numpy import arrays
 import deepof.data
@@ -127,10 +127,11 @@ def test_autoencoder_fitting(
         batch_size=batch_size,
         encoding_size=encoding_size,
         epochs=1,
+        log_history=True,
         log_hparams=True,
         n_components=k,
         loss=loss,
-        phenotype_class=pheno_class,
+        phenotype_class=0,
         predictor=predictor,
         variational=variational,
     )