jsonboard

Fancy interface for ML experiments based on JSON/JSONL log files.

Install

pip install jsonboard

Logging directory

JsonBoard expects the logging directory to be structured like the following:

main_directory
├── experiment_name_1
│   ├── version_0
│   │   ├── hparams.json
│   │   ├── meta.json
│   │   └── data.jsonl
│   └── version_1
│       ├── hparams.json
│       └── data.jsonl
├── experiment_name_1
│   └── version_0
│       └── data.jsonl
└── ...

data.jsonl is not just a JSON to enable easy appending of new results.

Examples

Follow a few log files to take as example.

hparams.json

{

    "learning_rate": 1e-05,
    "batch_size": 32,
    "devices": 8,
    "accelerator": "gpu",
    "num_warmup_steps": 10000,
    "max_steps": 100000,
    "alpha": 0.5,
    "train_filepath": "datasets/wikiqa"
}

meta.json

{
    "environment": "google_cloud"
}

data.jsonl

Some field may even be null, the corresponding points will not be plotted.

{ "step": 1000, "training/accuracy": 0.9 }
{ "step": 2000, "training/accuracy": 0.7 }
{ "step": 3000, "training/accuracy": 0.6 }
{ "step": 4000, "training/accuracy": 0.4 }
{ "step": 5000, "training/accuracy": 0.3 }
{ "step": 6000, "training/accuracy": 0.1 }
{ "step": 7000, "training/accuracy": null }
{ "step": 7000 }

An example of loggings directory is examples/.

Run the server

Start the server with:

jsonboard --input /path/to/logging/dir

or just try our framework by running the following (you must download the examples/ folder):

jsonboard --input examples/

Additional parameters

List additional CLI parameters with:

jsonboard --help