Parameters Configuration

Faknow supports two types of parameter configurations: Parameter Dicts and YAML Config Files. The former receives the parameters as dict keyword arguments and the latter reads them from the yaml configuration file.

Parameter Dicts

Parameter Dict is realized by the dict data structure in python, where the key is the parameter name, and the value is the parameter value. The users can write their parameters into a dict, and pass it into run.

An example is as follows:

from faknow.run import run

model = 'mdfend'  # lowercase short name of models
kargs = {'train_path': 'train.json', 'test_path': 'test.json'}  # dict arguments
run(model, **kargs)

The json file for mdfend should be like:

[
    {
        "text": "this is a sentence.",
        "domain": 9
    },
    {
        "text": "this is a sentence.",
        "domain": 1
    }
]

Config Files

Config Files should be organized in the format of yaml. The users should write their parameters according to the rules aligned with yaml, and pass them into run_from_yaml.

An example is as follows:

from faknow.run import run_from_yaml

model = 'mdfend'  # lowercase short name of models
config_path = 'mdfend.yaml'  # config file path
run_from_yaml(model, config_path)

Your yaml config file should be like:

train_path: train.json # the path of training set file
test_path: test.json # the path of testing set file