From b4bd5f91ee8a04135992287637182448db0bf38d Mon Sep 17 00:00:00 2001 From: Hert4 <98259769+Hert4@users.noreply.github.com> Date: Mon, 24 Aug 2026 18:48:17 +0700 Subject: [PATCH] [diffusion] Fix test_model_fast_paths import after sana_ln_modulate rename (#36175) Co-authored-by: Alex Nails --- .../kernels/ops/diffusion/test_model_fast_paths.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/test/registered/kernels/ops/diffusion/test_model_fast_paths.py b/test/registered/kernels/ops/diffusion/test_model_fast_paths.py index 0b4702fca..79c691f61 100644 --- a/test/registered/kernels/ops/diffusion/test_model_fast_paths.py +++ b/test/registered/kernels/ops/diffusion/test_model_fast_paths.py @@ -99,7 +99,7 @@ from sglang.multimodal_gen.runtime.models.dits.sana import ( _eager_ln_modulate as _sana_eager_ln_modulate, ) from sglang.multimodal_gen.runtime.models.dits.sana import ( - _sana_ln_modulate, + sana_ln_modulate, ) from sglang.multimodal_gen.runtime.models.vaes import flux2_vae_cuda_opt as vae_opt from sglang.multimodal_gen.runtime.models.vaes.autoencoder import AutoencoderKL @@ -361,7 +361,7 @@ def test_sana_fused_ln_modulate_is_bit_exact(shape, nmod, transposed): shift, scale = emb.chunk(nmod, dim=1)[0], emb.chunk(nmod, dim=1)[-1] # default-stream eager serving must stay on the untouched eager chain n_sigs = len(sana._SANA_LN_MOD.verified_sigs) - _sana_ln_modulate(norm, x, scale, shift) + sana_ln_modulate(norm, x, scale, shift) assert len(sana._SANA_LN_MOD.verified_sigs) == n_sigs # The fusion engages on non-default streams (the BCG warmup/capture path). # x/scale/shift were filled on the default stream, so the side stream must @@ -373,9 +373,9 @@ def test_sana_fused_ln_modulate_is_bit_exact(shape, nmod, transposed): side = torch.cuda.Stream() side.wait_stream(torch.cuda.current_stream()) with torch.cuda.stream(side): - out = _sana_ln_modulate(norm, x, scale, shift) + out = sana_ln_modulate(norm, x, scale, shift) assert len(sana._SANA_LN_MOD.verified_sigs) == n_sigs + 1 # verified - out2 = _sana_ln_modulate(norm, x, scale, shift) # verified-sig lane + out2 = sana_ln_modulate(norm, x, scale, shift) # verified-sig lane torch.cuda.current_stream().wait_stream(side) torch.cuda.synchronize() assert torch.equal(out, _sana_eager_ln_modulate(norm, x, scale, shift))