keplr-io/picard

Easily declare large spaces of (keras) neural networks and run (hyperopt) optimization experiments on them.

picard's Issues

my thoughts

Hi! I just had a quick look over Picard and had some thoughts + constructive criticism as someone who uses keras + hyperopt.

the json syntax you use is very cumbersome.. soo many levels of depth. It's also not clear why you do/dont use the built-in keras json model configs.. in fact your project seems to have no relation at all to keras/hyperopt (other than assumably using it in the backend) and instead you just invented a new configuration format. In general, it feels like it'd take longer to write those config files than it would be to just write a keras model and some for loops or learn hyperopt itself.

I guess i'm saying that for me personally, this syntax seems too complex. just my constructive opinion :)

for instance, this really scares me for having just two layers:

{
    "operators": {
        ...,
        "feedforward": {
          "#repeat": {
            "operator": {
              "#compose": [
                {
                  "layer": "Dense",
                  "config": {
                    "output_dim": 512,
                    "activation": {
                      "&choice": {
                        "options": [
                          "relu",
                          "sigmoid"
                        ]
                      }
                    }
                  }
                },
                {
                  "#optional": {
                    "layer": "Dropout",
                    "config": {
                      "p": {
                        "&uniform": {
                          "high": 0.6,
                          "low": 0.3
                        }
                      }
                    }
                  }
                }
              ]
            },
            "+times": {
              "&choice": {
                "options": [
                  2,
                  3,
                  4,
                  5
                ]
              }
            }
          }
        }
    }
}
}