[GitHub] [madlib] kaknikhil commented on a change in pull request #388: DL: Add new param metrics_compute_frequency to madlib_keras_fit()

[GitBox <gi...@apache.org>]

kaknikhil commented on a change in pull request #388:  DL: Add new param metrics_compute_frequency to madlib_keras_fit()
URL: https://github.com/apache/madlib/pull/388#discussion_r283052553
 
 

 ##########
 File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
 ##########
 @@ -313,6 +316,61 @@ def fit(schema_madlib, source_table, model,model_arch_table,
     #TODO add a unit test for this in a future PR
     reset_cuda_env(original_cuda_env)
 
+def compute_loss_and_metrics(schema_madlib, table, dependent_varname,
+                             independent_varname, compile_params, model_arch,
+                             model_state, gpus_per_host, segments_per_host,
+                             seg_ids_val, rows_per_seg_val,
+                             gp_segment_id_col, metrics_list, loss_list,
+                             curr_iter, dataset_name):
+    """
+    Compute the loss and metric using a given model (model_state) on the
+    given dataset (table.)
+    """
+    start_val = time.time()
+    evaluate_result = get_loss_acc_from_keras_eval(schema_madlib,
+                                                   table,
+                                                   dependent_varname,
+                                                   independent_varname,
+                                                   compile_params,
+                                                   model_arch, model_state,
+                                                   gpus_per_host,
+                                                   segments_per_host,
+                                                   seg_ids_val,
+                                                   rows_per_seg_val,
+                                                   gp_segment_id_col)
+    end_val = time.time()
+    plpy.info("Time for evaluation in iteration {0}: {1} sec.". format(
+        curr_iter + 1, end_val - start_val))
+    if len(evaluate_result) < 2:
+        plpy.error('Calling evaluate on table {0} returned < 2 '
+                   'metrics. Expected both loss and a metric.'.format(
+            table))
+    loss = evaluate_result[0]
+    metric = evaluate_result[1]
+    plpy.info("{0} set metric after iteration {1}: {2}.".
+              format(dataset_name, curr_iter + 1, metric))
+    plpy.info("{0} set loss after iteration {1}: {2}.".
+              format(dataset_name, curr_iter + 1, loss))
+    metrics_list.append(metric)
+    loss_list.append(loss)
+
+def should_compute_metrics_this_iter(
 
 Review comment:
   I think it is more readable if the current iteration is one indexed

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


With regards,
Apache Git Services