[Hardware][Ascend] Integrate MindIE dense and sparse quantized attention for Wan2.2 T2V (#7561)

Signed-off-by: zqxu <xuzhenqiang3@huawei.com>
Co-authored-by: zqxu <xuzhenqiang3@huawei.com>

tests/diffusion/models/wan2_2/test_wan22_mindie_metadata.py

@@ -0,0 +1,40 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+"""Wan integration contracts required by quantized dense/sparse attention."""
+
+from unittest.mock import Mock
+
+import pytest
+import torch
+
+from vllm_omni.diffusion.models.wan2_2.wan2_2_transformer import WanTransformerBlock
+
+pytestmark = [pytest.mark.core_model, pytest.mark.diffusion, pytest.mark.cpu]
+
+
+def test_block_publishes_unpadded_grid_without_partial_packed_metadata():
+    block = object.__new__(WanTransformerBlock)
+    torch.nn.Module.__init__(block)
+    block.scale_shift_table = torch.zeros(1, 6, 4)
+    block.norm1 = lambda x, *a: x
+    block.norm2 = lambda x: x
+    block.norm3 = lambda x, *a: x
+    block.attn1 = Mock(side_effect=lambda x, *a: torch.zeros_like(x))
+    block.attn2 = Mock(side_effect=lambda x, *a: torch.zeros_like(x))
+    block.ffn = lambda x: torch.zeros_like(x)
+    # Local SP tokens include alignment padding; grid describes the full valid video.
+    x = torch.zeros(1, 1152, 4)
+    block(
+        x,
+        x,
+        torch.zeros(1, 6, 4),
+        None,
+        hidden_states_mask=torch.ones(1, 1152, dtype=torch.bool),
+        vsa_dit_seq_shape=(5, 16, 27),
+    )
+    metadata = block.attn1.call_args.args[2]
+    assert metadata.video_layout.latent_grid == (5, 16, 27)
+    assert metadata.video_layout.used_len == 2160
+    assert metadata.video_layout.prefix_len == 0
+    assert "max_seqlen_q" not in metadata.extra  # CUDA must not infer incomplete packed varlen.
+    assert block.attn2.call_args.args[2] is None