sgl-project/sglang · error · ValueError

Unsupported action_mode={sp.action_mode!r}; expected one of

Error message

Unsupported action_mode={sp.action_mode!r}; expected one of {sorted(ACTION_MODES)}

What it means

_prepare_action_latents normalizes action_mode (strip+lower) and checks membership in the ACTION_MODES set, which contains 'policy', 'inverse_dynamics', and 'forward_dynamics'. Anything else, including typos or unnormalized variants that still fail, is rejected with the sorted valid list.

Source

Thrown at python/sglang/multimodal_gen/runtime/pipelines_core/stages/model_specific_stages/cosmos3.py:672

        device: torch.device,
        dtype: torch.dtype,
    ) -> None:
        """Prepare action latents and conditioning, writing them onto ``batch``.

        Action tokens run at frame rate (no temporal compression), so the chunk
        length is ``num_frames - 1`` with ``start_frame_offset=1`` so each action
        aligns with the frame it drives.

        Three modes:
        - ``forward_dynamics``: the user supplies the action; all tokens are
          clean conditioning (velocity mask 0) and the model predicts video.
        - ``policy`` / ``inverse_dynamics``: actions are denoised from noise
          (velocity mask 1); ``raw_action_dim`` is required.
        """
        sp = batch.sampling_params
        mode = str(sp.action_mode).strip().lower()
        if mode not in ACTION_MODES:
            raise ValueError(
                f"Unsupported action_mode={sp.action_mode!r}; "
                f"expected one of {sorted(ACTION_MODES)}"
            )
        action_dim = self.transformer.action_dim
        num_frames = batch.num_frames

        action_chunk_size = num_frames - 1 if num_frames > 1 else 1
        action_offset = 1 if action_chunk_size == num_frames - 1 else 0

        domain_id = self._resolve_domain_id(batch)
        batch_dim = (
            int(batch.raw_latent_shape[0])
            if getattr(batch, "raw_latent_shape", None)
            else 1
        )
        raw_action_dim = getattr(sp, "raw_action_dim", None)
        if raw_action_dim is None:
            embodiment = getattr(sp, "domain_name", None)

View on GitHub (pinned to 0132848349)

Solutions

1. Use one of the exact modes from the error message (e.g. 'policy', 'forward_dynamics', 'inverse_dynamics')
2. Check for casing/whitespace; the code lowercases and strips, so only the name itself matters
3. If action generation isn't wanted, remove action_mode entirely

Example fix

# before
sp.action_mode = 'ForwardDynamics'

# after
sp.action_mode = 'forward_dynamics'

from ... import ACTION_MODES
assert str(sp.action_mode).strip().lower() in ACTION_MODES

def is_valid_action_mode(mode: str, modes: set) -> bool:
    return mode.strip().lower() in modes

When it happens

Trigger: Passing sampling_params.action_mode not in ACTION_MODES, e.g. 'Prediction', 'fd', or 'policy_v2'.

Common situations: Guessing mode names from another library, casing/typo issues, or stale names after an API rename.

Understand the failure class

Background: Invalid enum value errors: "Unknown type", "Invalid scope", "must be one of" — when a string is not on the library's allowed list — this error's family across 23 libraries.

Related errors

• Cosmos3 action generation does not support sequence parallel
• action_mode is set but the loaded Cosmos3 checkpoint has no
• domain_id must be non-negative, got {domain_id}
• Unknown action domain name {domain_name!r}. Valid names: {so
• Cosmos3 action generation requires --domain-id or --domain-n

AI-assisted analysis of sgl-project/sglang@0132848349 (2026-08-28). Data as JSON: /api/errors/e64e4e8b031b0d89. Report an issue: GitHub.