Stability-AI/generative-models · warning

Attention mode ' ' is not available. Falling back to native…

Error message

Attention mode '{attn_mode}' is not available. Falling back to native attention. This is not a problem in Pytorch >= 2.0. FYI, you are running with PyTorch version {torch.__version__}.

What it means

CrossAttention/MemoryEfficientAttention __init__ asserts attn_mode is a known mode, then warns and coerces the mode to 'softmax' if a non-default mode (e.g. 'xformers') was requested while xformers is not installed. The model still constructs, just with slower native attention.

Solutions

1. Install xformers so the requested attention mode actually becomes available
2. Change attn_mode to 'softmax' explicitly in the config to silence the fallback warning
3. Verify XFORMERS_IS_AVAILABLE is True after importing sgm.modules.attention before relying on xformers speedups

Example fix

// before
params:
  attn_mode: "xformers"   # xformers not installed -> silent fallback
// after
pip install xformers
# or
params:
  attn_mode: "softmax"

import sgm.modules.attention as A
if cfg_attn_mode != "softmax" and not A.XFORMERS_IS_AVAILABLE:
    print(f"{cfg_attn_mode} unavailable, will fall back to softmax")

def attn_mode_usable(mode: str) -> bool:
    import sgm.modules.attention as A
    return mode == "softmax" or A.XFORMERS_IS_AVAILABLE

try:
    attn = CrossAttention(..., attn_mode=cfg_attn_mode)
finally:
    if attn.attn_mode != cfg_attn_mode:
        logger.warning("attention mode fell back to %s", attn.attn_mode)

When it happens

Trigger: Config `attn_mode: 'xformers'` (or 'torch-sdp'/'vanilla' variants requiring backends) in a CrossAttention with XFORMERS_IS_AVAILABLE False — i.e. xformers import failed at module load.

Common situations: Reusing SD configs that specify xformers attention on machines without xformers; CI/CPU environments where xformers wheels are unavailable.

Related errors

• We do not support vanilla attention anymore, as it is too…
• Checkpoint path is deprecated, use `checkpoint_egnine`…
• Could not find SGM configs in
• Did not find parameters for pattern
• Expected key `target` to instantiate.

AI-assisted analysis of Stability-AI/generative-models@e8cd657656 (2026-08-29). Data as JSON: /api/errors/0c6585d01c6e61f2. Report an issue: GitHub.

Appendix: source

Thrown at sgm/modules/attention.py:478

    }

    def __init__(
        self,
        dim,
        n_heads,
        d_head,
        dropout=0.0,
        context_dim=None,
        gated_ff=True,
        checkpoint=True,
        disable_self_attn=False,
        attn_mode="softmax",
        sdp_backend=None,
    ):
        super().__init__()
        assert attn_mode in self.ATTENTION_MODES
        if attn_mode != "softmax" and not XFORMERS_IS_AVAILABLE:
            logpy.warn(
                f"Attention mode '{attn_mode}' is not available. Falling "
                f"back to native attention. This is not a problem in "
                f"Pytorch >= 2.0. FYI, you are running with PyTorch "
                f"version {torch.__version__}."
            )
            attn_mode = "softmax"
        elif attn_mode == "softmax" and not SDP_IS_AVAILABLE:
            logpy.warn(
                "We do not support vanilla attention anymore, as it is too "
                "expensive. Sorry."
            )
            if not XFORMERS_IS_AVAILABLE:
                assert (
                    False
                ), "Please install xformers via e.g. 'pip install xformers==0.0.16'"
            else:
                logpy.info("Falling back to xformers efficient attention.")
                attn_mode = "softmax-xformers"

View on GitHub (pinned to e8cd657656)