reductionista commented on a change in pull request #524:
URL: https://github.com/apache/madlib/pull/524#discussion_r583245581
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File path: src/ports/postgres/modules/deep_learning/madlib_keras_wrapper.py_in
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@@ -287,27 +298,50 @@ def parse_optimizer(compile_dict):
# Parse the fit parameters into a dictionary.
-def parse_and_validate_fit_params(fit_param_str):
+def parse_and_validate_fit_params(fit_param_str, current_seg_id=0):
if fit_param_str:
- fit_params_dict = convert_string_of_args_to_dict(fit_param_str)
-
- literal_eval_fit_params = ['batch_size','epochs','verbose',
+ fit_params_dict = convert_string_of_args_to_dict(fit_param_str,
strip_quotes=False)
+ literal_eval_fit_params = ['batch_size','epochs','verbose', 'shuffle',
'class_weight','initial_epoch','steps_per_epoch']
- accepted_fit_params = literal_eval_fit_params + ['shuffle']
+ accepted_fit_params = literal_eval_fit_params + ['callbacks']
fit_params_dict = validate_and_literal_eval_keys(fit_params_dict,
literal_eval_fit_params,
accepted_fit_params)
- if 'shuffle' in fit_params_dict:
- shuffle_value = fit_params_dict['shuffle']
- if shuffle_value == 'True' or shuffle_value == 'False':
- fit_params_dict['shuffle'] = bool(shuffle_value)
+
+ if 'callbacks' in fit_params_dict:
+ fit_params_dict['callbacks'] =
parse_callbacks(fit_params_dict['callbacks'], current_seg_id)
return fit_params_dict
else:
return {}
+# Parse the callback fit params and create the TensorBoard object in the
dictionary
+def parse_callbacks(callbacks, current_seg_id=0):
+ callbacks = callbacks.strip("'")
+ if not is_superuser(current_user()):
+ plpy.error("Only a superuser may use callbacks.")
+ try:
+ tree = ast.parse(callbacks, mode='eval')
+ assert(type(tree.body) == ast.List)
+ assert(len(tree.body.elts) == 1)
+ assert(type(tree.body.elts[0]) == ast.Call)
+ assert(tree.body.elts[0].func.id == 'TensorBoard')
+ tb_params = tree.body.elts[0].keywords
+ tb_params_dict = { tb_params[i].arg : tb_params[i].value \
+ for i in range(len(tb_params)) }
+ except:
+ plpy.error("Invalid callbacks fit param. Currently, "
+ "only TensorBoard callbacks are accepted.")
+
+ accepted_tb_params = [ 'log_dir', 'histogram_freq', 'batch_size',
'update_freq',
+ 'write_graph', 'write_grad', 'write_images' ]
+ tb_params_dict = validate_and_literal_eval_keys(tb_params_dict,
accepted_tb_params, accepted_tb_params)
+ tb_params_dict['log_dir'] =
tb_params_dict['log_dir']+"{0}".format(current_seg_id)
Review comment:
If we're going to split up the logs into separate directorys, shouldn't
the directory names be based on model_id rather than current_seg_id? At least
for fit multiple, not sure what the best behavior would be for fit.
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