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About

Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. The FfDL platform uses a microservices architecture to reduce coupling between components, keep each component simple and as stateless as possible, isolate component failures, and allow each component to be developed, tested, deployed, scaled, and upgraded independently. Leveraging the power of Kubernetes, FfDL provides a scalable, resilient, and fault-tolerant deep-learning framework. The platform uses a distribution and orchestration layer that facilitates learning from a large amount of data in a reasonable amount of time across compute nodes.

About

tensorViz helps developers explore PyTorch models and JAX/Flax programs as interactive graphs. For PyTorch, users can expand nested modules, inspect tensor shapes captured from one forward pass, jump to Python source, and review architecture changes beside code diffs. The website offers recorded model graphs to explore without installation. The free VS Code extension is available from the Visual Studio Marketplace and Open VSX. Local capture requires Python, model dependencies, and example inputs. Standalone coding-agent plugins are an Apple Silicon macOS preview; MCP agents can also connect to the extension. JAX/Flax graphs use CPU tracing with inferred shapes, and PyTorch source edits are unavailable for them.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Neural networks experts looking for a solution to run deep-learning frameworks as a service on Kubernetes

Audience

Machine learning engineers, PyTorch developers, researchers and students exploring model architecture, tensor shapes and architecture changes.

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

$0
The VS Code extension is free to install. Core graph exploration and source-edit forms work without an agent or provider API key; connecting a coding agent is optional.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

IBM
Founded: 1911
United States
developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/

Company Information

tensorViz
tensorviz.dev/

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Deep Learning Supported
Neural Network Supported

Categories

Deep Learning Supported
Machine Learning Supported

Integrations

Caffe Supported
Claude Code Not Supported
Codex CLI Not Supported
Cursor Not Supported
GitHub Not Supported
Kubernetes Supported
Model Context Protocol (MCP) Not Supported
PyTorch Supported
T3 Code Not Supported
TensorFlow Supported
Torch Supported
Visual Studio Code Not Supported

Integrations

Caffe Not Supported
Claude Code Supported
Codex CLI Supported
Cursor Supported
GitHub Supported
Kubernetes Not Supported
Model Context Protocol (MCP) Supported
PyTorch Not Supported
T3 Code Supported
TensorFlow Not Supported
Torch Not Supported
Visual Studio Code Supported
Claim Fabric for Deep Learning (FfDL) and update features and information
Claim Fabric for Deep Learning (FfDL) and update features and information
Claim tensorViz and update features and information
Claim tensorViz and update features and information