[CI/Build][AMD] Fix import errors in tests/kernels/attention (#29032)

Signed-off-by: Randall Smith <ransmith@amd.com>
Co-authored-by: Randall Smith <ransmith@amd.com>

tests/kernels/attention/test_cascade_flash_attn.py

@@ -7,11 +7,19 @@ import torch
 
 from vllm.platforms import current_platform
 from vllm.v1.attention.backends.flash_attn import cascade_attention, merge_attn_states
-from vllm.vllm_flash_attn import (
-    fa_version_unsupported_reason,
-    flash_attn_varlen_func,
-    is_fa_version_supported,
-)
+
+try:
+    from vllm.vllm_flash_attn import (
+        fa_version_unsupported_reason,
+        flash_attn_varlen_func,
+        is_fa_version_supported,
+    )
+except ImportError:
+    if current_platform.is_rocm():
+        pytest.skip(
+            "vllm_flash_attn is not supported for vLLM on ROCm.",
+            allow_module_level=True,
+        )
 
 NUM_HEADS = [(4, 4), (8, 2), (16, 2)]
 HEAD_SIZES = [128, 192, 256]

tests/kernels/attention/test_flash_attn.py

@@ -6,11 +6,20 @@ import pytest
 import torch
 
 from vllm.platforms import current_platform
-from vllm.vllm_flash_attn import (
-    fa_version_unsupported_reason,
-    flash_attn_varlen_func,
-    is_fa_version_supported,
-)
+
+try:
+    from vllm.vllm_flash_attn import (
+        fa_version_unsupported_reason,
+        flash_attn_varlen_func,
+        is_fa_version_supported,
+    )
+except ImportError:
+    if current_platform.is_rocm():
+        pytest.skip(
+            "vllm_flash_attn is not supported for vLLM on ROCm.",
+            allow_module_level=True,
+        )
+
 
 NUM_HEADS = [(4, 4), (8, 2)]
 HEAD_SIZES = [40, 72, 80, 128, 256]

tests/kernels/attention/test_flashinfer.py

@@ -2,12 +2,20 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 
-import flashinfer
 import pytest
-import torch
 
 from vllm.platforms import current_platform
 
+try:
+    import flashinfer
+except ImportError:
+    if current_platform.is_rocm():
+        pytest.skip(
+            "flashinfer is not supported for vLLM on ROCm.", allow_module_level=True
+        )
+
+import torch
+
 NUM_HEADS = [(32, 8), (6, 1)]
 HEAD_SIZES = [128, 256]
 BLOCK_SIZES = [16, 32]

tests/kernels/attention/test_flashinfer_mla_decode.py

@@ -3,7 +3,6 @@
 import pytest
 import torch
 import torch.nn.functional as F
-from flashinfer.decode import trtllm_batch_decode_with_kv_cache_mla
 from torch import Tensor
 
 from vllm.platforms import current_platform
@@ -15,6 +14,8 @@ if not current_platform.has_device_capability(100):
         reason="FlashInfer MLA Requires compute capability of 10 or above.",
         allow_module_level=True,
     )
+else:
+    from flashinfer.decode import trtllm_batch_decode_with_kv_cache_mla
 
 
 def ref_mla(

tests/kernels/attention/test_flashinfer_trtllm_attention.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
-import flashinfer
 import pytest
 import torch
 
@@ -16,6 +15,8 @@ if not current_platform.is_device_capability(100):
     pytest.skip(
         "This TRTLLM kernel requires NVIDIA Blackwell.", allow_module_level=True
     )
+else:
+    import flashinfer
 
 FLOAT32_BYTES = torch.finfo(torch.float).bits // 8
 FP8_DTYPE = current_platform.fp8_dtype()

tests/kernels/moe/test_flashinfer.py

@@ -22,7 +22,14 @@ from vllm.model_executor.layers.quantization.utils.flashinfer_utils import (
 from vllm.model_executor.layers.quantization.utils.fp8_utils import input_to_float8
 from vllm.model_executor.models.llama4 import Llama4MoE
 from vllm.platforms import current_platform
-from vllm.utils.flashinfer import has_flashinfer_cutlass_fused_moe
+
+try:
+    from vllm.utils.flashinfer import has_flashinfer_cutlass_fused_moe
+except ImportError:
+    if current_platform.is_rocm():
+        pytest.skip(
+            "flashinfer not supported for vLLM on ROCm", allow_module_level=True
+        )
 
 if not has_flashinfer_cutlass_fused_moe() or not current_platform.has_device_capability(
     90