orhankislal commented on a change in pull request #368: DL: Add alternative
options for compile params
URL: https://github.com/apache/madlib/pull/368#discussion_r276027404
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File path: src/ports/postgres/modules/deep_learning/madlib_keras_wrapper.py_in
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@@ -120,15 +122,27 @@ def parse_compile_params(str_of_args):
compile_dict['metrics'] = ast.literal_eval(compile_dict['metrics']) if
'metrics' in compile_dict.keys() else None
compile_dict['loss_weights'] =
ast.literal_eval(compile_dict['loss_weights']) if 'loss_weights' in
compile_dict.keys() else None
- opt_name = compile_dict['optimizer'].split('(')[0]
+ opt_split = compile_dict['optimizer'].split('(')
+ opt_name = opt_split[0]
optimizers = get_optimizers()
_assert(opt_name in optimizers,
"model_keras error: invalid optimizer name: {0}".format(opt_name))
- opt_params = compile_dict['optimizer'].split('(')[1][:-1]
- opt_params_array = opt_params.split(',')
- opt_params_clean = map(split_and_strip, opt_params_array)
- key_value_params = { x[0] : x[1] for x in opt_params_clean}
- final_args = { key: bool(value) if value == 'True' or value == 'False'
else float(value) for key,value in key_value_params.iteritems() }
+ if len(opt_split) == 1:
+ final_args = None
+ else:
+ opt_params = compile_dict['optimizer'].split('(')[1][:-1]
+ opt_params_array = opt_params.split(',')
+ opt_params_clean = map(split_and_strip, opt_params_array)
+ key_value_params = { x[0] : x[1] for x in opt_params_clean}
+ final_args = { key: bool(value) if value == 'True' or value == 'False'
+ else float(value)
+ for key,value in key_value_params.iteritems() }
+
+ loss_split = compile_dict['loss'].split('.')
Review comment:
If we want to support individual loss functions, we have to import every
single one. It is possible that future versions of keras might change these or
add new ones. Instead of trying to update the code with every keras change, we
can import the losses as a whole and direct the user to use it.
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