The interface is localized. Skill descriptions and documents are machine-translated by AI into your language; code, commands, paths and technical terms stay in the original, and the author's document governs.
Explore skills
Development · SKILL.md

meta-optimizer-api

meta-optimizer-api

Route graph construction, unroll, save/load, and debugging work for MetaOptimizer.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill documentation

GitHub

name: meta-optimizer-api description: "Route graph construction, unroll, save/load, and debugging work for MetaOptimizer." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Meta Optimizer API

Use this sub-skill when a task needs to build, inspect, unroll, save, load, or debug meta.MetaOptimizer, meta_loss, or meta_minimize.

Start here

Covered responsibilities

  • MetaOptimizer(**kwargs) network registry setup
  • meta_loss(make_loss, len_unroll, net_assignments=None, second_derivatives=False)
  • meta_minimize(make_loss, len_unroll, learning_rate=0.01, **kwargs)
  • MetaLoss and MetaStep field semantics
  • variable interception and optimizee-variable ordering
  • net_assignments rules, including exact names and overlapping mappings
  • .l2l save/load behavior for optimizer state

Route elsewhere

  • Optimizer network classes and preprocessing details -> optimizer-networks
  • Built-in/custom problem factories and dataset setup -> problem-factories
  • CLI train/eval loops and saved-optimizer workflows -> training-evaluation

Working rule of thumb

  1. Make make_loss pure graph construction.
  2. Match variable names exactly when assigning nets.
  3. Call reset before each new epoch or task.
  4. Call update after each unroll if the live optimizee state should advance.
  5. Use the smoke script before deeper debugging.
Saved skills