minor updates per review

Author: JamiesonWarner

covid_xprize/examples/predictors/conditional_lstm/train_predictor.py

@@ -66,7 +66,7 @@ def train_predictor(training_data: pd.DataFrame,
     :param context_column: Which column in the data df to use as context and outcome.
     :param arch: Which predictor architecture to use.
         Current options are 'conditional' and 'independent'.
-    :param return_all_trials: If set to True, then this function returns all trials as a list.
+    :param return_all_trials: If set to True, then this function returns all trials as a list of trained models.
     :param verbose: Verbosity level for model.fit() when training the predictor.
     :returns: (best_model, results_df)
     """

setup.py

@@ -7,7 +7,7 @@
 import sys
 from setuptools import setup, find_packages
 
-LIBRARY_VERSION = '2.0.2'
+LIBRARY_VERSION = '2.0.3'
 
 CURRENT_PYTHON = sys.version_info[:2]
 REQUIRED_PYTHON = (3, 10)
@@ -61,14 +61,14 @@ def read(fname):
         ]
     },
     install_requires=[
-        'keras==2.11.0',
         'neat-python==0.92',
         'numpy==1.24.2',
         'pandas==1.5.3',
         'scikit-learn==1.2.2',
         'scipy==1.10.1',
         'setuptools==67.6.0',
-        'tensorflow==2.11.1',
+        'tensorflow==2.13.0',
+        'keras==2.13.1',
         'h5py==3.8.0'
     ],
     description='Contains sample code and notebooks '