kaknikhil commented on a change in pull request #393: DL: Add support for
reporting various metrics in fit/evaluate
URL: https://github.com/apache/madlib/pull/393#discussion_r286268486
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File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
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@@ -637,13 +642,21 @@ def internal_keras_eval_transition(state, dependent_var,
independent_var,
with K.tf.device(device_name):
res = model.evaluate(x_val, y_val)
- loss, metric = res
+ # if metric is None, model.evaluate will only return loss as a scalar
+ # Otherwise, it will return a list which has loss and metric
+ if type(res) is list:
+ loss, metric = res
+ else:
+ loss = res
+ metric = None
image_count = len(dependent_var)
agg_image_count += image_count
agg_loss += (image_count * loss)
- agg_metric += (image_count * metric)
+ plpy.info("agg_metric is {}".format(agg_metric))
Review comment:
again do we need this information to be printed to the console ? there are a
few more plpy infos that need to be removed.
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