Skills
.Work. You
Rest

keras-ops

Community

Backend-agnostic tensor math for BayesFlow.

Software Engineering#jax#pytorch#tensorflow#keras#bayesflow#tensor math#backend agnostic
Authormatthiaskloft
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill ensures that all tensor operations within BayesFlow extensions are compatible across different backends (PyTorch, JAX, TensorFlow) by enforcing the use of keras.ops.*.

Core Features & Use Cases

  • Backend Agnosticism: Guarantees code runs seamlessly on PyTorch, JAX, or TensorFlow.
  • Standardized Operations: Provides a consistent interface for common tensor manipulations like sum, mean, exp, reshape, and more.
  • Use Case: When developing a custom Keras layer for a BayesFlow model, use keras.ops.sum instead of torch.sum to ensure your layer works regardless of the chosen backend.

Quick Start

Use the keras-ops skill to perform a sum operation on a tensor using keras.ops.sum.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: keras-ops
Download link: https://github.com/matthiaskloft/claude-skills/archive/main.zip#keras-ops

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
View Source Repository

Agent Skills Search Helper

Install a tiny helper to your Agent, search and equip skill from 223,000+ vetted skills library on demand.