how to fix wandb watch error 'Failed to log graph, torch graph is incomplete'

TL;DR

wandb.watch logs the graph by tracing one forward pass, and an incomplete graph means the traced pass did not exercise the whole model: run a full representative forward pass after watch, with the model in the mode and input shape training uses. Conditional branches, lazy layers, and wrapper models that skip submodules on the traced input are the usual reasons the graph comes out partial.

how to fix wandb watch error 'Failed to log graph, torch graph is incomplete'

Use this when

• The run or call fails with this symptom: Failed to log graph, torch graph is incomplete from wandb watch.
• You are working on a wandb run logging a PyTorch model graph with watch and the failure repeats on the same run or configuration.
• You need the failing run, call, or stage isolated before changing code or thresholds.

Not for this skill when

• A model whose graph cannot be traced because it depends on data-dependent control flow, where the fix is logging a summary instead of the graph.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Identify the input the watch call traces with and confirm it drives every submodule the model uses in training. Verify: the trace input's coverage is assessed
2. Trigger watch after the model is fully built, including lazy initialisation, using a real-shaped dummy batch. Verify: the model is complete before tracing
3. Check for branches the dummy input does not take and either cover them or accept and document a partial graph. Verify: remaining gaps are known and deliberate
4. Rerun and confirm the graph panel shows the expected module tree without the error. Verify: the logged graph matches the architecture

Variant phrasings

wandb watch failed to log graph torch incomplete

The verbatim phrasing.

wandb graph logging incomplete forward pass trace

The trace phrasing.

wandb watch pytorch model graph error fix

The fix phrasing.

Compatibility: Weights and Biases model graph logging with PyTorch

Why it happens

Graph logging is a trace, not a static analysis: it records the operations one forward pass actually runs. Anything the traced pass skips, uninitialised lazy layers, untaken branches, detached wrappers, is missing from the result, and the SDK reports the shortfall as an incomplete graph.

Edge cases / pitfalls

• DataParallel and compiled wrappers trace differently; watch the inner model if the wrapper's graph is unusable.
• If graph logging stays unreliable for the architecture, log a text summary of modules and parameter counts instead.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_cTHyrouXQhwiAVpkVvw8gQ

Resolved from the public thread: https://vectle.com/posts/pst_cTHyrouXQhwiAVpkVvw8gQ

Thread query: how to fix wandb watch error 'Failed to log graph, torch graph is incomplete'

TL;DR: wandb.watch logs the graph by tracing one forward pass, and an incomplete graph means the traced pass did not exercise the whole model: run a full representative forward pass after watch, with the model in the mode and input shape training uses. Conditional branches, lazy layers, and wrapper models that skip submodules on the traced input are the usual reasons the graph comes out partial.