[AMD] Add AMD FP8 MLA attention test for Wan2.2-T2V-A14B (#23955)

test/registered/amd/test_wan22_fp8_mla.py

@@ -0,0 +1,136 @@
+"""AMD test for Wan2.2-T2V-A14B with FP8 MLA attention (1-GPU and 8-GPU)."""
+
+from __future__ import annotations
+
+import logging
+
+import pytest
+
+pytest.importorskip("sgl_kernel", reason="sgl_kernel is required for FP8 MLA tests")
+
+from sglang.multimodal_gen.test.server.test_server_common import (  # noqa: F401
+    DiffusionServerBase,
+    diffusion_server,
+)
+from sglang.multimodal_gen.test.server.test_server_utils import (
+    ServerContext,
+    get_generate_fn,
+)
+from sglang.multimodal_gen.test.server.testcase_configs import (
+    DiffusionServerArgs,
+    DiffusionTestCase,
+    T2V_sampling_params,
+)
+from sglang.test.ci.ci_register import register_amd_ci
+
+logger = logging.getLogger(__name__)
+
+register_amd_ci(est_time=3600, suite="nightly-amd-fp8-mla-diffusion", nightly=True)
+
+MODEL = "Wan-AI/Wan2.2-T2V-A14B-Diffusers"
+FP8_ENV = {"SGLANG_AITER_FP8_ATTN": "1"}
+
+FP8_MLA_CASES = [
+    DiffusionTestCase(
+        "wan2_2_t2v_a14b_fp8_mla_1gpu",
+        DiffusionServerArgs(
+            model_path=MODEL,
+            modality="video",
+            num_gpus=1,
+            extras=["--enable-torch-compile false"],
+            env_vars=FP8_ENV,
+        ),
+        T2V_sampling_params,
+        run_perf_check=False,
+        run_consistency_check=False,
+        run_models_api_check=False,
+        run_t2v_input_reference_check=False,
+    ),
+    DiffusionTestCase(
+        "wan2_2_t2v_a14b_fp8_mla_1gpu_compile",
+        DiffusionServerArgs(
+            model_path=MODEL,
+            modality="video",
+            num_gpus=1,
+            extras=["--enable-torch-compile true"],
+            env_vars=FP8_ENV,
+        ),
+        T2V_sampling_params,
+        run_perf_check=False,
+        run_consistency_check=False,
+        run_models_api_check=False,
+        run_t2v_input_reference_check=False,
+    ),
+    DiffusionTestCase(
+        "wan2_2_t2v_a14b_fp8_mla_8gpu",
+        DiffusionServerArgs(
+            model_path=MODEL,
+            modality="video",
+            num_gpus=8,
+            ulysses_degree=4,
+            cfg_parallel=True,
+            extras=["--enable-torch-compile false"],
+            env_vars=FP8_ENV,
+        ),
+        T2V_sampling_params,
+        run_perf_check=False,
+        run_consistency_check=False,
+        run_models_api_check=False,
+        run_t2v_input_reference_check=False,
+    ),
+    DiffusionTestCase(
+        "wan2_2_t2v_a14b_fp8_mla_8gpu_compile",
+        DiffusionServerArgs(
+            model_path=MODEL,
+            modality="video",
+            num_gpus=8,
+            ulysses_degree=4,
+            cfg_parallel=True,
+            extras=["--enable-torch-compile true"],
+            env_vars=FP8_ENV,
+        ),
+        T2V_sampling_params,
+        run_perf_check=False,
+        run_consistency_check=False,
+        run_models_api_check=False,
+        run_t2v_input_reference_check=False,
+    ),
+]
+
+
+class TestWan22FP8MLA(DiffusionServerBase):
+    """AMD test for FP8 MLA attention on Wan2.2-T2V-A14B."""
+
+    @classmethod
+    def teardown_class(cls):
+        try:
+            super().teardown_class()
+        except AttributeError:
+            pass
+
+    @pytest.fixture(params=FP8_MLA_CASES, ids=lambda c: c.id)
+    def case(self, request) -> DiffusionTestCase:
+        return request.param
+
+    def test_diffusion_generation(
+        self,
+        case: DiffusionTestCase,
+        diffusion_server: ServerContext,
+    ):
+        generate_fn = get_generate_fn(
+            model_path=case.server_args.model_path,
+            modality=case.server_args.modality,
+            sampling_params=case.sampling_params,
+        )
+
+        perf_record, content = self.run_and_collect(
+            diffusion_server, case.id, generate_fn
+        )
+
+        assert len(content) > 0, "FP8 MLA generation produced empty output"
+
+
+if __name__ == "__main__":
+    import sys
+
+    sys.exit(pytest.main([__file__, "-v"]))