DriftAI CLI¶
The Command Line Interface to improve DriftAI use experience
dai new¶
The DriftAI CLI makes easy to create the project structure.
Usage:
$ dai new <project-name>
Example:
$ dai new iris-project
dai add¶
Add a new element to the project
Usage:
$ dai add --help
Usage: dai add [OPTIONS] [dataset]
Options:
-p, --path TEXT Path of dataset's datasource
--heading / --no-heading If the first line of CSV is the header or not
-l, --label TEXT The column name of the label. By default, the
label is the last column
--parsing-pattern TEXT Pattern to read the files inside the directory
-d, --datatype [img] Data type of files inside the directory
Dataset¶
Adds a new dataset to project.
Usage:
$ dai add dataset --path <dataset_path>
Examples:
Adding a csv file as Dataset:
$ dai add dataset --path path/to/dataset/Iris.csv
Dataset with id Iris created
Adding a directory as Dataset:
$ dai add dataset --path path/to/dataset/MNIST/ --parsing-pattern {class}/{}.[png|jpg] --datatype img
Dataset with id Iris created
dai generate¶
Generates a new element based on the existent ones. For example: Crates a Subdataset from an existing Dataset.
Usage:
$ dai generate --help
Usage: dai generate [OPTIONS] [subdataset|approach] IDENTIFIER
Options:
-s, --subdataset TEXT In case item=approach. ID of the subdataset
where approach will retrieve the data
-m, --method [k_fold|train_test]
--by TEXT In case method=k_fold, by is the number of
folds. If method=train_test, by is the
percentage of training instance
-d, --dataset TEXT ID of the dataset which new subdataset will
be generated from
--help Show this message and exit.
Subdataset¶
Generates a dataset’s partitions using K-folds or train test split.
Usage:
$ dai generate subdataset <dataset_id> --method <k_fold|train_test> --by <number of folds|train %>
Example:
# Creates a partition of a dataset where 25% of the instances belongs to the test set
$ dai generate subdataset Iris --method train_test --by 0.75
Subdataset with id Iris_train_test_0.75 created
# Creates a partition of a dataset with 5 folds
$ dai generate subdataset Iris --method k_fold --by 5
Subdataset with id Iris_k_fold_5 created
Approach¶
Creates a new file containing the RunnableApproach class with the specified name (Name should be written in camel_case).
Usage:
$ dai generate approach <approach_name> --subdataset <subdataset containing the data to tune the approach model>
Example:
$ dai generate approach random_forest --subdataset Iris_k_fold_5
dai status¶
Check the status of a running approach.
Usage:
$ dai status <approach_name>
Example:
$ dai status random_forest
Loading approach data...
Approach random_forest is still running
[===>-------------------------------------] 7 % Done runs: 118 Total runs: 1520
dai evaluate¶
Evaluate approach’s results and generates a csv file named <approach_name>_evaluation.csv where each line corresponds to a Run, and contains the ground truth and predicted labels, the metrics and the set of parameters used in each .
Usage:
$ dai evaluate <approach_name> -m <metric_1> -m <metric_2> ....