What does this failure look like in production?

In production this failure typically appears during the first tens-to-hundreds of training steps: loss curves become non-monotonic, validation metrics plateau above the baseline, and downstream checkpoints either diverge or fail to improve. Engineers frequently misread it as data drift when the underlying mechanism is torchscript cannot resolve the typing.sequence constructor as used in the fused function under newer torch. Validating against the symptom list in this entry is the fastest way to confirm the diagnosis.

Is this a hardware or a software issue?

Environment failures can look like either layer depending on the symptom. The discriminator is the resolution of the symptom to the recommended fix: if applying the steps under "How to fix it" eliminates the symptom, this is a software/configuration class issue regardless of the hardware it surfaced on. Repeat the fix on a fresh node to confirm.

How long does the fix typically take?

Most resolutions from this entry take 10 to 30 minutes of engineer time once the diagnosis is confirmed. Long fixes come from skipping the diagnosis step and chasing apparent symptoms (validation drift, memory growth, slow throughput) instead of the actual root cause listed above. Apply the fix in a small experiment first, then roll it forward.

Does this affect inference or only training?

Primarily this is a environment failure observed during training, but the same misconfiguration can leak into downstream evaluation and serving. Treat the prevention checklist as a guardrail: any pipeline that touches a trained checkpoint should re-validate the failure mode before promoting the model.

What's the cheapest way to confirm this is the problem?

Cheapest signal: reproduce the symptom on a 1-GPU toy run with the same configuration. If the toy run exhibits the same behavior, the cause is the configuration rather than the cluster. If only the multi-GPU run is affected, the failure is a distributed interaction, so Megatron-LM fused functions using @jit_fuser / torch.jit.script is the most likely layer to inspect.

Can the Denpex platform detect this automatically?

Yes. Denpex correlates the symptoms in this entry against your training logs in real time and surfaces the failure taxonomy, root cause, and exact remediation command on the console. Three full diagnoses are included free during signup, and the encyclopedia entry you are reading is generated from the same signal library that powers the platform.

What related failures should I check next?

Closely related failures cluster around #megatron-lm, #torchscript, #jit_fuser. After applying this fix, validate against the related entries below to confirm no overlapping cause is masking as this one. Engineers routinely discover that the dominant failure mode is actually a second, sibling failure compounded on top.

Will this recur after the fix?

Applied once with the prevention checklist, this failure does not recur under normal operation. The recurring variant most engineers encounter is the re-emergence of the same symptom on a different model or stack after megatron-lm is upgraded. Pin compatible versions and rerun the prevention smoke test on every dependency change.

Is there a fingerprint I can monitor?

Yes. RuntimeError: Unknown type constructor Sequence is the highest-signal fingerprint. Wire a metric or alert on that signal (or its absence after the fix) so you can detect the recurrence automatically. The Denpex platform encodes this exact fingerprint and surfaces it directly in the dashboard.

What is the official documentation that covers this?

Reference documentation is listed in the References section at the bottom of this entry. The most authoritative URLs are the upstream framework docs and the issue trackers cited; the Denpex entry synthesizes both into the executive, engineer, and on-call perspectives so each audience can act without reading every linked source.

Does this entry include working code?

Yes. The "Code Examples" section contains copy-paste-ready snippets that target the most common stacks (PyTorch, Hugging Face Trainer, DeepSpeed, Megatron-LM, vLLM/Transformers). Each snippet is annotated with why it works so you can adapt the pattern to your own framework without losing fidelity.

Megatron @jit_fuser Fails: 'Unknown type constructor Sequence'

Q: How does this scale from 1 GPU to 1000 GPUs?

At single-GPU scale the symptom usually looks like slow convergence or a single anomalous loss value. At 64+ GPU scale, distributed interactions amplify torchscript cannot resolve the typing.sequence constructor as used in the fused function under newer torch through collectives, and the failure can manifest as a full job abort. Always reproduce the fix at the smallest cluster configuration that still exhibits the symptom before promoting to production scale.

torch.jit.script on a Megatron @jit_fuser-decorated function fails with 'Unknown type constructor Sequence' on newer torch. TorchScript can't resolve typing.Sequence as used inside the fused function. Upgrade Megatron (the fix moved the vocab-range lookup out of the JITed function) or replace the unsupported annotation.

Quick answer

torch.

Symptom: RuntimeError: Unknown type constructor Sequence
Root cause: TorchScript cannot resolve the typing.Sequence constructor as used in the fused function under newer torch. The vocab-range lookup carried an annotation TorchScript no longer supports inside the scripted body.
Recommended fix: Upgrade Megatron-LM to a version with the fix (commit 38722c39b moved the vocab-range lookup out of the JITed function)
How Denpex helps: Denpex investigates Megatron @jit_fuser Fails: 'Unknown type constructor Sequence' using the evidence you provide or your connected workload collects. Earlier rank, host or application evidence is needed to distinguish an initiating failure from a downstream report.

Environment#megatron-lm#torchscript#jit_fuser#typing#sequence#environment

What this failure is

Megatron @jit_fuser Fails: 'Unknown type constructor Sequence' is a Environment failure seen during ML training runs. torch.jit.script on a Megatron @jit_fuser-decorated function fails with 'Unknown type constructor Sequence' on newer torch. TorchScript can't resolve typing.Sequence as used inside the fused function. Upgrade Megatron (the fix moved the vocab-range lookup out of the JITed function) or replace the unsupported annotation. Common tags: Megatron Lm, Torchscript, Jit_fuser, Typing.

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Why it happens (the mechanism)

TorchScript cannot resolve the typing.Sequence constructor as used in the fused function under newer torch. The vocab-range lookup carried an annotation TorchScript no longer supports inside the scripted body. Taken together, these mechanisms explain why the failure is reproducible, why it tends to surface on specific workloads or scales, and why generic mitigation attempts often fall short without addressing the underlying cause.

What you'll observe

torch.jit.script fails compiling a Megatron fused function
Startup crashes before training on newer torch
@jit_fuser decorated function rejected by TorchScript

Common symptoms and what they mean

Symptom	Why it happens
RuntimeError: Unknown type constructor Sequence	TorchScript cannot resolve the typing.Sequence constructor as used in the fused function under newer torch
Traceback through torch/jit/_script.py from a @jit_fuser function	The vocab-range lookup carried an annotation TorchScript no longer supports inside the scripted body
Occurs with newer torch versions	TorchScript cannot resolve the typing.Sequence constructor as used in the fused function under newer torch

Which systems are affected

Megatron-LM fused functions using @jit_fuser / torch.jit.script
Newer torch where TorchScript rejects typing.Sequence
Functions with a vocab-range lookup inside the JITed body

How to confirm this is the problem

Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.

✓Reproduce the failure from a clean checkpoint/seed: the symptom must appear without warm-up state from a previous run.
✓Verified signal present: RuntimeError: Unknown type constructor Sequence
✓Verified signal present: Traceback through torch/jit/_script.py from a @jit_fuser function
✓Verified signal present: Occurs with newer torch versions
✓A targeted fix from the "How to fix it" section eliminates or substantially reduces the symptom within one validation pass.

Root cause

TorchScript cannot resolve the typing.Sequence constructor as used in the fused function under newer torch
The vocab-range lookup carried an annotation TorchScript no longer supports inside the scripted body

The fix and how to prevent it

Searchable error signature

search key

RuntimeError: Unknown type constructor Sequence
torch.jit.script fails compiling a Megatron fused function

Use this text as a lookup key in logs and upstream issue trackers. It is not presented as a captured customer log. Confirm the cause from your own preceding events, versions, configuration and the cited references.

The fix and the prevention pattern

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