[Perf] Wan2.2 I2V optimization: convert datatype from FP32 to BF16 in vae (#2391)

Signed-off-by: KexiongYu <yukexiong1@huawei.com>
Signed-off-by: Canlin Guo <961750412@qq.com>
Co-authored-by: Canlin Guo <961750412@qq.com>

tests/diffusion/distributed/test_autoencoder_kl_wan.py

@@ -0,0 +1,43 @@
+import pytest
+import torch
+
+from vllm_omni.diffusion.distributed.autoencoders import autoencoder_kl_wan as wan_vae_module
+from vllm_omni.diffusion.distributed.autoencoders.autoencoder_kl_wan import OmniAutoencoderKLWan
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
+
+
+class _DummyOmniAutoencoderKLWan(OmniAutoencoderKLWan):
+    def __init__(self, *, dtype: torch.dtype):
+        torch.nn.Module.__init__(self)
+        self.register_parameter("dummy_weight", torch.nn.Parameter(torch.ones(1, dtype=dtype)))
+
+
+def test_wan_vae_execution_context_handles_fp32():
+    model = _DummyOmniAutoencoderKLWan(dtype=torch.float32)
+    with model._execution_context():
+        output = model.dummy_weight + 1
+    assert output.dtype == torch.float32
+
+
+def test_wan_vae_execution_context_handles_bf16():
+    model = _DummyOmniAutoencoderKLWan(dtype=torch.bfloat16)
+    with model._execution_context():
+        output = model.dummy_weight + 1
+    assert output.dtype == torch.bfloat16
+
+
+def test_wan_vae_execution_context_uses_platform_autocast(mocker):
+    sentinel = object()
+    platform = mocker.Mock()
+    platform.create_autocast_context.return_value = sentinel
+    mocker.patch.object(wan_vae_module, "current_omni_platform", platform)
+
+    model = _DummyOmniAutoencoderKLWan(dtype=torch.bfloat16)
+
+    assert model._execution_context() is sentinel
+    platform.create_autocast_context.assert_called_once_with(
+        device_type=model.dummy_weight.device.type,
+        dtype=torch.bfloat16,
+        enabled=True,
+    )