Home / yeaight7 / agent-powerups · plugins/machine-learning-ops/skills/training-pipeline-debugging/SKILL.md · GitHub

training-pipeline-debugging skillA

training-pipeline-debugging is agent-read markdown (skill) from yeaight7/agent-powerups: Use when an ML training run fails or misbehaves -- NaN losses, out-of-memory errors, shape mismatches, or a model that cannot fit even a single batch..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

## Purpose

ML training bugs are often silent mathematical errors rather than explicit code crashes. This protocol localizes the standard failure classes quickly.

## When to Use

- Loss becomes NaN or diverges
- Training crashes with out-of-memory errors
- Shape/dimension errors at matrix multiplications or loss computation
- The pipeline runs but the model never learns

## Inputs

- The failing training script and its error output or loss curve

## Workflow

1. **Run the overfit test first**: fit a single batch of ~10 examples. If the model cannot achieve near-zero loss on a single batch, the pipeline is fundamentally broken — do not debug full runs until the single-batch test passes.
2. **NaN losses** — check:
   - Learning rate too high?
   - Missing data (NaNs in input)?
   - Log/Exp/Divide-by-zero in custom loss functions?
   - Exploding gradients (clip gradients)?
3. **OOM (out of memory)**:
   - Reduce batch size.
   - Check for memory leaks in the training loop (e.g., accumulating history across epochs without `.detach()`).
4. **Shape mismatches**:
   - Add temporary print statements or assertions on `tensor.shape` before matrix multiplications and loss calculations.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add yeaight7/agent-powerups/training-pipeline-debugging@git:20260605.2671f86
Exact content
mdr add yeaight7/agent-powerups/training-pipeline-debugging@sha256:accac340a4a8defb

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

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Versions

versioncommittedcommitsizeaudit
git:20260605.2671f86 latest2026-06-05 2671f86 2,404 BA view · diff
git:20260502.647df102026-05-02 647df10 1,080 BA view · diff
git:20260502.317ce782026-05-02 317ce78 148 BB view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (2404 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

yeaight7/agent-powerups · 6 stars · license Apache-2.0 · pushed 2026-09-21 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_3mefdvr4utwlykhi
GET https://markdownregistry.com/api/v1/resolve?ref=yeaight7/agent-powerups/training-pipeline-debugging
GET https://markdownregistry.com/api/v1/blob/accac340a4a8defb789352f92d05abf50adf94054fd59b8e3aeb975d62767bb1

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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