makemebitter commented on a change in pull request #425: DL: Add training for
multiple models
URL: https://github.com/apache/madlib/pull/425#discussion_r311280150
##########
File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
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@@ -403,49 +408,84 @@ def should_compute_metrics_this_iter(curr_iter,
metrics_compute_frequency,
return (curr_iter)%metrics_compute_frequency == 0 or \
curr_iter == num_iterations
+
def fit_transition(state, dependent_var, independent_var, model_architecture,
compile_params, fit_params, current_seg_id, seg_ids,
images_per_seg, gpus_per_host, segments_per_host,
- prev_serialized_weights, **kwargs):
+ prev_serialized_weights, is_final=True,
Review comment:
Because these functions are also used in madlib_keras_fit and there we
didn't modify anything. So these function default to single model data-parallel
training via model averaging.
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