Application settings are managed by Flask. This means you can use environment variables or a configuration file.

To specify your own configuration, use the PICASSO_SETTINGS environment variable. Let’s look at the Tensorflow MNIST example.

export PICASSO_SETTINGS=/absolute/path/to/repo/picasso/picasso/examples/tensorflow/

Tells the app to use this configuration instead of the default one. Inside, we have:

import os

base_dir = os.path.split(os.path.abspath(__file__))[0]

MODEL_CLS_PATH = os.path.join(base_dir, '')
MODEL_CLS_NAME = 'TensorflowMNISTModel'
    'data_dir': os.path.join(base_dir, 'data-volume'),
    'tf_input_var': 'convolution2d_input_1:0',
    'tf_predict_var': 'Softmax:0',

Any lowercase line is ignored for the purposes of determining a setting. MODEL_LOAD_ARGS will pass the arguments along to the model’s load function.

For explanations of each setting, see picasso.config.