neptune_init: Starts a new tracked run, and append it to the top of the...

In neptune: MLOps Metadata Store - Experiment Tracking and Model Registry for Production Teams

Starts a new tracked run, and append it to the top of the Runs table view.

Description

Starts a new tracked run, and append it to the top of the Runs table view. All parameters are optional, hence minimal invocation: run <- neptune_init().

Usage

neptune_init(project = NULL,
            api_token = NULL,
            run = NULL,
            python = NULL,
            python_path,
            source_files = NULL,
            mode = "async",
            custom_run_id = NULL,
            name = NULL,
            description = NULL,
            tags = NULL,
            capture_stdout = TRUE,
            capture_stderr = TRUE,
            capture_hardware_metrics = TRUE,
            capture_traceback = TRUE,
            monitoring_namespace = NULL,
            fail_on_exception = TRUE,
            flush_period = 5,
            proxies = NULL)

Arguments

project	character – Name of a project in a form of namespace/project_name. If NULL, the value of NEPTUNE_PROJECT environment variable will be taken.
api_token	character – User’s API token. If NULL, the value of NEPTUNE_API_TOKEN environment variable will be taken. Note: It is strongly recommended to use NEPTUNE_API_TOKEN environment variable rather than placing your API token in plain text in your source code.
run	character – An existing run's identifier like'SAN-1' in case of resuming a tracked run. A run with such identifier must exist. If NULL is passed, starts a new tracked run. See Resume run guide.
python	character - one of python, conda, miniconda, venv. Specifies which type of python's backend should be used.
python_path	character - path to python executable.
source_files	character vector – List of source files to be uploaded. Must be list of str or single str. Uploaded sources are displayed in the run’s Source code tab. If NULL is passed, for non-interactive sessions the R script from which the method is called will be uploaded. Unix style pathname pattern expansion is supported. For example, you can pass '*.py' to upload all python source files from the current directory. For Python 3.5 or later, paths of uploaded files on server are resolved as relative to the calculated common root of all uploaded source files. For older Python versions, paths on server are resolved always as relative to the current directory. For recursion lookup use '**/*.py' (for Python 3.5 and later). For more information see glob library.
mode	character – Connection mode in which the tracking will work. Possible values "async", "sync", "offline", and "debug", "read-only". See Connection modes guide.
custom_run_id	character – A unique identifier that can be used to log metadata to a single run from multiple files or processes. The maximum length of the identifier is 32 characters. Make sure you are using the same identifier everywhere. See Pipelines guide. If NULL and the NEPTUNE_CUSTOM_RUN_ID environment variable is set Neptune will use its value as custom_run_id.
name	character – Editable name of the run. Name is displayed in the run's Details and in Runs table as a column.
description	character – Editable description of the run. Description is displayed in the run's Details and can be displayed in the runs view as a column.
tags	character vector – Tags of the run. They are editable after run is created. Tags are displayed in the run's Details and can be viewed in Runs table view as a column.
capture_stdout	logical – Whether to send python's stdout. Tracked metadata will be stored inside monitoring_namespace.
capture_stderr	logical – Whether to send python’s stderr. Tracked metadata will be stored inside monitoring_namespace.
capture_hardware_metrics	logical – Whether to send hardware monitoring logs (CPU, GPU, Memory utilization). Tracked metadata will be stored inside monitoring_namespace.
capture_traceback	logical – Whether to send run’s traceback in case of an exception on Python's side.
monitoring_namespace	character - Namespace inside which all monitoring logs be stored.
fail_on_exception	logical – Whether to set run's as True, if an uncaught exception on python's side happens.
flush_period	numeric - how often asynchronous thread should synchronize data with Neptune servers. Value in seconds.
proxies	named list (python's dict) - Argument passed to HTTP calls made via the python's Requests library. For more information see their proxies section.

Value

Run object that is used to manage the tracked run and log metadata to it.

Author(s)

Authors:

• Mateusz Dominiak

• Maintainer: Neptune DevTeam [e-mail]

See Also

Useful links:

• https://neptune.ai/

• Documentation https://docs.neptune.ai/

• Report bugs at https://github.com/neptune-ai/neptune-r/issues

Examples

## Not run: 
# We are using api token for an anonymous user neptuner. For your projects use your private token.
run <- neptune_init(api_token = 'ANONYMOUS',
                    project = "common-r/quickstarts")

## End(Not run)

neptune documentation built on April 13, 2022, 5:14 p.m.