package reference

pyhectiqlab

Main objects

Run

Check the methods of the main class to communicate with the lab.

Config

An abstract object to store your experiment settings.

Utils

Below is a list of methods that do not use the core classes. They can be executed out of import pyhectiqlab. For instance,

import pyhectiqlab
pyhectiqlab.download_run_artifact("1234")

pyhectiqlab

pyhectiqlab.utils.download_run_artifact(artifact_uuid: str, save_path: str = ./)

Download an existing artifact.

Parameters

Property	Type	Default	Description
`artifact_uuid`	`str`	`-`	Unique artifact id. Available with the web application.
`save_path`	`str`	`./`	Save path.

pyhectiqlab.datasets.download_dataset(dataset_name: str, project: str, version: str, save_path: str = ./, overwrite: str = False)

Download an existing dataset without a run context.

Parameters

Property	Type	Default	Description
`dataset_name`	`str`	`-`	Dataset name
`project`	`str`	`-`	Project name
`version`	`str`	`-`	Specific version of the dataset. If `None`, the latest version is fetched.
`save_path`	`str`	`./`	Save path.
`overwrite`	`str`	`False`	Set to `True` if you want to download the dataset again even if it is already saved on your machine.

pyhectiqlab.mlmodels.download_mlmodel(mlmodel_name: str, project: str, version: str, save_path: str = ./, overwrite: str = False)

Download an existing mlmodel without a run context.

Parameters

Property	Type	Default	Description
`mlmodel_name`	`str`	`-`	MLModel name
`project`	`str`	`-`	Project name
`version`	`str`	`-`	Specific version of the mlmodel. If `None`, the latest version is fetched.
`save_path`	`str`	`./`	Save path.
`overwrite`	`str`	`False`	Set to `True` if you want to download the mlmodel again even if it is already saved on your machine.

pyhectiqlab.callbacks.KerasCallback(run: pyhectiqlab.Run, level: str = batch, exclude_train_metrics: bool = False, exclude_val_metrics: bool = False, exclude_predict_metrics: bool = False, exclude_metrics: List[str] = [])

A custom callback object for keras models.

Parameters

Property	Type	Default	Description
`run`	`pyhectiqlab.Run`	`-`	The target run to host the metrics
`level`	`str`	`batch`	Either 'batch' or 'epoch'. If 'batch', the metrics are pushed on every batch and the stepstamp incremented on every batch. If 'epoch', the metrics are pushed every epoch.
`exclude_train_metrics`	`bool`	`False`	Set to true to exclude the training metrics.
`exclude_val_metrics`	`bool`	`False`	Set to true to exclude the validation metrics.
`exclude_predict_metrics`	`bool`	`False`	Set to true to exclude the prediction metrics.
`exclude_metrics`	`List[str]`	`[]`	List the metrics to remove from tracking. For validation metrics, add 'val_'. For instance, use `exclude_metrics=['mse', 'val_mse']` to exclude the `mse` metrics in training and validation.