[Diffusion] Add LTX-2.5 Diffusion VAE decoder support (#6189)
Signed-off-by: mglyn <1203789601@qq.com> Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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@@ -1,5 +1,5 @@
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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"""Unit tests for LTX image-to-video input and conditioning behavior."""
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@@ -258,6 +258,39 @@ class TestLTXImageToVideoConditioning:
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assert LTX2Pipeline.support_image_input is True
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def test_ltx25_i2v_encode_uses_diffusion_decoder_statistics(self, monkeypatch):
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import vllm_omni.diffusion.models.ltx2.ltx2_conditioning as ltx2_conditioning
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from vllm_omni.diffusion.models.ltx2.pipeline_ltx2 import LTX2Pipeline
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pipe = object.__new__(LTX2Pipeline)
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torch.nn.Module.__init__(pipe)
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pipe.use_diffusion_decoder = True
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pipe.vae = SimpleNamespace(
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encode=lambda image: image,
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latents_mean=torch.full((2,), 100.0),
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latents_std=torch.full((2,), 10.0),
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config=SimpleNamespace(scaling_factor=1.0),
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)
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pipe.diffusion_decoder = SimpleNamespace(
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latents_mean=torch.tensor([1.0, 3.0]),
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latents_std=torch.tensor([2.0, 4.0]),
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config=SimpleNamespace(scaling_factor=2.0),
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)
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monkeypatch.setattr(
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ltx2_conditioning,
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"retrieve_latents",
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lambda *_args, **_kwargs: torch.tensor([[[[[3.0]]], [[[7.0]]]]]),
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)
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actual = pipe._encode_i2v_image_latents(
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torch.zeros(1, 3, 1, 1),
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batch_size=1,
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generator=None,
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dtype=torch.float32,
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)
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torch.testing.assert_close(actual, torch.full((1, 2, 1, 1, 1), 2.0))
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def test_ltx23_i2v_rejects_multi_image_prompt_list(self):
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from vllm_omni.diffusion.models.ltx2.pipeline_ltx2 import LTX2Pipeline
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