classifier: fix memory usage

inspire_classifier/api.py

@@ -151,24 +151,27 @@ def train():
     train_and_save_classifier()
 
 
-def predict_coreness(title, abstract):
+def initialize_classifier():
     """
-    Predicts class-wise probabilities given the title and abstract.
+    Initializes the classifier.
     """
-    text = title + " <ENDTITLE> " + abstract
-    categories = ["rejected", "non_core", "core"]
-    try:
-        classifier = Classifier(
-            cuda_device_id=current_app.config["CLASSIFIER_CUDA_DEVICE_ID"]
-        )
-    except IOError as error:
-        raise IOError("Data ITOS not found.") from error
-
+    classifier = Classifier(
+        cuda_device_id=current_app.config["CLASSIFIER_CUDA_DEVICE_ID"]
+    )
     try:
         classifier.load_trained_classifier_weights(path_for("trained_classifier"))
     except IOError as error:
-        raise IOError("Could not load the trained classifier weights.") from error
+        raise IOError("Could not load the trained classifier weights.", path_for("trained_classifier")) from error
+
+    return classifier
+
 
+def predict_coreness(classifier, title, abstract):
+    """
+    Predicts class-wise probabilities given the title and abstract.
+    """
+    text = title + " <ENDTITLE> " + abstract
+    categories = ["rejected", "non_core", "core"]
     class_probabilities = classifier.predict(
         text, temperature=current_app.config["CLASSIFIER_SOFTMAX_TEMPERATUR"]
     )

inspire_classifier/app.py

@@ -28,7 +28,7 @@
 from prometheus_flask_exporter.multiprocess import GunicornInternalPrometheusMetrics
 from webargs.flaskparser import use_args
 
-from inspire_classifier.api import predict_coreness
+from inspire_classifier.api import predict_coreness, initialize_classifier
 
 from . import serializers
 
@@ -55,6 +55,8 @@ def create_app():
     app.config["CLASSIFIER_BASE_PATH"] = app.instance_path
     app.config.from_object("inspire_classifier.config")
     app.config.from_pyfile("classifier.cfg", silent=True)
+    with app.app_context():
+        classifier = initialize_classifier()
 
     @app.route("/api/health")
     def date():
@@ -69,7 +71,7 @@ def date():
     )
     def core_classifier(args):
         """Endpoint for the CORE classifier."""
-        prediction = predict_coreness(args["title"], args["abstract"])
+        prediction = predict_coreness(classifier, args["title"], args["abstract"])
         response = coreness_schema.dump(prediction)
         return response
 
@@ -89,3 +91,4 @@ def page_not_found(e):
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0")
+