---

name: pytorch-models description: "Use ResNeSt's PyTorch package and Torch Hub models, Split-Attention layers, safe no-pretrained inference, ImageNet config interpretation, and PyTorch troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

PyTorch Models

Use this sub-skill when the task is about the PyTorch side of ResNeSt: package imports, Torch Hub loading, model factories, Split-Attention layers, safe smoke checks, or PyTorch training/config interpretation.

Read first

• Read references/api-reference.md when you need model names, signatures, registry behavior, or Torch Hub entry points.
• Read references/workflows.md when you need a safe no-pretrained smoke, a Torch Hub loading recipe, or a distilled ImageNet verification flow.
• Read references/training-and-configs.md when you need the bundled training config keys, dataset layout, loss selection, or launcher semantics.
• Read references/troubleshooting.md when imports, pretrained weights, tensor shapes, cache behavior, or dataset layout fail.
• Run scripts/pytorch_tiny_inference.py for a safe offline-first model smoke and optional Split-Attention check.

Covers

• Public PyTorch factories: resnest50, resnest101, resnest200, resnest269, and the fast variants resnest50_fast_1s1x64d, resnest50_fast_2s1x64d, resnest50_fast_4s1x64d, resnest50_fast_1s2x40d, resnest50_fast_2s2x40d, resnest50_fast_4s2x40d, resnest50_fast_1s4x24d.
• Registry-backed builders and internals: get_model, ResNet, Bottleneck, SplAtConv2d, and rSoftMax.
• Safe pretrained=False inference by default, with explicit warnings for any weight download attempt.
• ImageNet transform, loss, scheduler, and config interpretation at the level needed for future agents.
• PyTorch-specific troubleshooting for optional dependencies, pretrained cache, classifier-head mismatch, and unsupported layer settings.

Does not cover

• Gluon / MXNet model zoo workflows.
• Detectron2 backbone and COCO workflows.
• Full ImageNet extraction or training launchers.

When a task leaves the classification path and moves into Gluon or Detectron2, route it to the sibling sub-skill for that backend instead of extending this one.