Gradient Docs
Gradient HomeHelp DeskCommunitySign up free
1.0.0
1.0.0
  • About Paperspace Gradient
  • Get Started
    • Quick Start
    • Core Concepts
    • Install the Gradient CLI
    • Common Errors
  • Tutorials
    • Tutorials List
      • Getting Started with Notebooks
      • Train a Model with the Web UI
      • Train a Model with the CLI
      • Advanced: Distributed training sample project
      • Registering Models in Gradient
      • Using Gradient Deployments
      • Using Custom Containers
  • Notebooks
    • Overview
    • Using Notebooks
      • The Notebook interface
      • Notebook metrics
      • Share a Notebook
      • Fork a Notebook
      • Notebook Directories
      • Notebook Containers
        • Building a Custom Container
      • Notebook Workspace Include Files
      • Community (Public) Notebooks
    • ML Showcase
    • Run on Gradient (GitHub badge)
  • Projects
    • Overview
    • Managing Projects
    • GradientCI
      • GradientCI V1 (Deprecated)
  • Workflows
    • Overview
      • Getting Started with Workflows
      • Workflow Spec
      • Gradient Actions
  • Experiments
    • Overview
    • Using Experiments
      • Containers
      • Single-node & multi-node CLI options
      • Experiment options
      • Gradient Config File
      • Environment variables
      • Experiment datasets
      • Git Commit Tracking
      • Experiment metrics
        • System Metrics
        • Custom Metrics
      • Experiment Logs
      • Experiment Ports
      • GradientCI Experiments
      • Diff Viewer
      • Hyperparameter Tuning
    • Distributed Training
      • Distributed Machine Learning with Tensorflow
      • Distributed Machine Learning with MPI
        • Distributed Training using Horovod
        • Distributed Training Using ChainerMN
  • Jobs
    • Overview
    • Using Jobs
      • Stop a Job
      • Delete a Job
      • List Jobs
      • Job Logs
      • Job Metrics
        • System Metrics
        • Custom Metrics
      • Job Artifacts
      • Public Jobs
      • Building Docker Containers with Jobs
  • Models
    • Overview
    • Managing Models
      • Example: Prepare a TensorFlow Model for Deployments
      • Model Path, Parameters, & Metadata
    • Public Models
  • Deployments
    • Overview
    • Managing Deployments
      • Deployment Containers
        • Custom Deployment Containers
      • Deployment States
      • Deployment Logs
      • Deployment Metrics
      • A Deployed Model's API Endpoint
        • Gradient + TensorFlow Serving
      • Deployment Autoscaling
      • Optimize Models for Inference
  • Data
    • Types of Storage
      • Managing Data in Gradient
        • Managing Persistent Storage with VMs
    • Storage Providers
    • Versioned Datasets
    • Public Datasets Repository
  • TensorBoards
    • Overview
    • Using Tensorboards
      • TensorBoards getting started with Tensorflow
  • Metrics
    • Metrics Overview
    • View and Query Metrics
    • Push Metrics
  • Secrets
    • Overview
    • Using Secrets
  • Gradient SDK
    • Gradient SDK Overview
      • Projects Client
      • Experiments Client
      • Models Client
      • Deployments Client
      • Jobs Client
    • End to end tutorial
    • Full SDK Reference
  • Instances
    • Instance Types
      • Free Instances (Free Tier)
      • Instance Tiers
  • Gradient Cluster
    • Overview
    • Setup
      • Managed Private Clusters
      • Self-Hosted Clusters
        • Pre-installation steps
        • Gradient Installer CLI
        • Terraform
          • Pre-installation steps
          • Install on AWS
          • Install on bare metal / VMs
          • Install on NVIDIA DGX
        • Let's Encrypt DNS Providers
        • Updating your cluster
    • Usage
  • Tags
    • Overview
    • Using Tags
  • Machines (Paperspace CORE)
    • Overview
    • Using Machines
      • Start a Machine
      • Stop a Machine
      • Restart a Machine
      • Update a Machine
      • Destroy a Machine
      • List Machines
      • Show a Machine
      • Wait For a Machine
      • Check a Machine's utilization
      • Check availability
  • Paperspace Account
    • Overview
    • Public Profiles
    • Billing & Subscriptions
    • Hotkeys
    • Teams
      • Creating a Team
      • Upgrading to a Team Plan
  • Release Notes
    • Product release notes
    • CLI/SDK Release notes
Powered by GitBook
On this page
  • Persistent Storage
  • Uploading
  • Downloading
  • Artifacts
  • Get
  • List
  • Destroy
  1. Data
  2. Types of Storage

Managing Data in Gradient

PreviousTypes of StorageNextManaging Persistent Storage with VMs

Last updated 4 years ago

Persistent Storage

is accessible across Paperspace VM instances and Gradient Experiments, Jobs, and Notebooks. Uploading and downloading data is possible from any of these endpoints.

Uploading

From A Notebook

When opening your notebook you will see a /storage folder. Clicking on the folder will take you to Persistent Storage where you can upload your data. If there are a large amount of files, it's advisable to zip them up first.

From a Virtual Machine (VM)

Downloading

Downloading data to /storage is as simple as using curl or wget from a Gradient Job or Notebook or Paperspace VM instance. Alternatively, you can use a browser from within a Paperspace VM instance to download files.

Artifacts

Get

Get the artifacts files for the job with the given id. The name of a particular file, or directory can be specified, and can include a wildcard character at the end, e.g., "myfiles"*. If no specifc file or directory is specified all artifact files will be retrieved.

Example Use

gradient jobs artifacts get --jobId <j123abc>

Properties

Name

Type

Attributes

Description

jobId

string

Id of the job to get artifacts for

files

string

<optional>

Optional; if getting only certain files, a wildcard pattern to match against, e.g., "myfiles*". Note: if you include a wildcard you must double-quote the files argument.

dest

string

<optional>

Optional; an existing directory to copy the artifacts files to.

json

boolean

<optional>

Optional; return JSON object instead of writing to standard out. '--json' with no value is equivalent to true.

List

List job artifact files for the specified job.

Example Use

gradient jobs artifacts list --jobId <j123abc> --size true

Properties

Name

Type

Attributes

Description

jobId

string

Id of the job to list artifacts for

files

string

<optional>

Optional; wildcard expression of file(s) to list, e.g., "myfiles*". Note: if you include a wildcard you must double-quote the files argument.

size

boolean

<optional>

Optional; include file size in bytes. '--size' with no value is equivalent to true.

links

boolean

<optional>

Optional; include https links to artifacts. Note: links are only valid for 8 hours. '--links' with no value is equivalent to true.

json

boolean

<optional>

Optional; return JSON object instead of writing to standard out. '--json' with no value is equivalent to true.

Destroy

Destroy artifact files of the job with the given id. The name of a particular file, or directory can be specified, and can include a wildcard character at the end, e.g., "myfiles*". If no specifc file or directory is specified all artifact files will be destroyed.

Example Use

gradient jobs artifacts destroy --jobId <j123abc> --files <myfiles*>

Properties

Name

Type

Attributes

Description

jobId

string

The id of the job to destroy artifacts for

files

string

<optional>

Optional; if destroying only certain files, a wildcard pattern to match against, e.g., "myfiles*". Note: if you include a wildcard you must double-quote the files argument.

To upload data into /storage , you can either SCP data from a local laptop/desktop to a Paperspace VM instance or use the upload functionality from within a Gradient Jupyter Notebook. See a tutorial .

This feature is only available in the hosted gradient Gradient version. to learn more.

here
Contact Sales
Persistent Storage