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TorchScale conflicts with timm: exact consumer pins are not fixed by upgrading everything

Two nodes can require different timm versions. Map the consumers and their supported ranges before deciding whether one environment can serve both.

Scope and symptoms

Two nodes can require different timm versions. Map the consumers and their supported ranges before deciding whether one environment can serve both.

Search fragments; wording and context vary:

torchscale
timm==0.6.13

Source-supported context

The inspected TorchScale setup.py identifies version 0.2.0 and declares timm==0.6.13 and fairscale==0.4.0 among its requirements. This establishes an exact pin in that source snapshot, not in every fork or future release. V04-TORCHSCALE V04-TIMM

Distinguish these cases

1. A TorchScale distribution requires a timm version outside another node's supported range.

2. A third-party fork changes dependencies and differs from the official revision the user thought was installed.

3. Metadata appears consistent but a consumer still calls an incompatible API at runtime.

Suggested diagnostic sequence

This sequence is editorial guidance, not a diagnosis of your machine.

1. Read installed torchscale and timm versions and each node's declarations. Record installation origins and range intersections rather than merely comparing which version is newer.

2. Test a mutually supported combination in a copy when one exists. Otherwise use a maintainer-supported implementation or separate the environments.

3. Removing an equality pin from requirements is not evidence of compatibility. Consumer-code changes need an upstream fix or explicit tests and should remain isolated from the stable installation.

4. Run the smallest model for the affected node and regress the other timm consumer. Check model names, weight loading and input/output behavior rather than import alone.

Completion checks

Dependency checks and both consumers' minimal operations pass. A successful final pip install does not prove the shared environment is consistent.

Limits and cautions

The observed historical source version is not a latest-version recommendation or an instruction to pin every installation to timm==0.6.13. Model and hardware conditions remain separate.

Source review: 2026-09-22. No installation, GPU inference or user-environment repair was executed.

Original sources

Didn't solve it?

Check the next possible cause

The same symptom can come from a different cause. Work through these related entries in order.

  1. ModuleNotFoundError in ComfyUI even though the package is installedModuleNotFoundErrorA successful installation in a terminal does not show that ComfyUI uses the same Python. Separate the import name, distribution name and running interpreter before changing dependencies.
  2. timm is missing, a model name is unknown, or weights will not downloadNo module named 'timm'A node imports the library, chooses an implementation and may then obtain pretrained weights. Determine which stage failed instead of treating every message as a missing package.
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Sources & references

Source-based editorial draft; no runtime verification. Version observations are scoped, and unknown wrapper identity is explicit.

01TorchScale setup.pySource checked: 2026-09-2202timm installation documentationSource checked: 2026-09-22

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