Mercurial > repos > bgruening > create_tool_recommendation_model
diff main.py @ 1:12764915e1c5 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/recommendation_training/tools/tool_recommendation_model commit edeb85d311990eabd65f3c4576fbeabc6d9165c9"
| author | bgruening |
|---|---|
| date | Wed, 25 Sep 2019 06:42:40 -0400 |
| parents | 9bf25dbe00ad |
| children | 76251d1ccdcc |
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--- a/main.py Wed Aug 28 07:19:38 2019 -0400 +++ b/main.py Wed Sep 25 06:42:40 2019 -0400 @@ -112,7 +112,6 @@ arg_parser.add_argument("-lr", "--learning_rate", required=True, help="learning rate") arg_parser.add_argument("-ar", "--activation_recurrent", required=True, help="activation function for recurrent layers") arg_parser.add_argument("-ao", "--activation_output", required=True, help="activation function for output layers") - arg_parser.add_argument("-lt", "--loss_type", required=True, help="type of the loss/error function") # get argument values args = vars(arg_parser.parse_args()) tool_usage_path = args["tool_usage_file"] @@ -134,7 +133,6 @@ learning_rate = args["learning_rate"] activation_recurrent = args["activation_recurrent"] activation_output = args["activation_output"] - loss_type = args["loss_type"] config = { 'cutoff_date': cutoff_date, @@ -152,8 +150,7 @@ 'recurrent_dropout': recurrent_dropout, 'learning_rate': learning_rate, 'activation_recurrent': activation_recurrent, - 'activation_output': activation_output, - 'loss_type': loss_type + 'activation_output': activation_output } # Extract and process workflows