update

vllm/config/attention.py

@@ -0,0 +1,69 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from typing import Any, Literal
+
+from pydantic import field_validator
+
+from vllm.config.utils import config
+from vllm.v1.attention.backends.registry import AttentionBackendEnum
+
+
+@config
+class AttentionConfig:
+    """Configuration for attention mechanisms in vLLM."""
+
+    backend: AttentionBackendEnum | None = None
+    """Attention backend to use. If None, will be selected automatically."""
+
+    flash_attn_version: Literal[2, 3] | None = None
+    """Force vllm to use a specific flash-attention version (2 or 3).
+    Only valid when using the flash-attention backend."""
+
+    use_prefill_decode_attention: bool = False
+    """Use separate prefill and decode kernels for attention instead of
+    the unified triton kernel."""
+
+    flash_attn_max_num_splits_for_cuda_graph: int = 32
+    """Flash Attention max number splits for cuda graph decode."""
+
+    use_cudnn_prefill: bool = False
+    """Whether to use cudnn prefill."""
+
+    use_trtllm_ragged_deepseek_prefill: bool = True
+    """Whether to use TRTLLM ragged deepseek prefill."""
+
+    use_trtllm_attention: bool | None = None
+    """If set to True/False, use or don't use the TRTLLM attention backend
+    in flashinfer. If None, auto-detect the attention backend in flashinfer."""
+
+    disable_flashinfer_prefill: bool = False
+    """Whether to disable flashinfer prefill."""
+
+    disable_flashinfer_q_quantization: bool = False
+    """If set, when using fp8 kv, do not quantize Q to fp8."""
+
+    use_prefill_query_quantization: bool = False
+    """If set, quantize query for attention in prefill."""
+
+    def compute_hash(self) -> str:
+        """
+        Provide a hash that uniquely identifies all the configs
+        that affect the structure of the computation
+        graph from input ids/embeddings to the final hidden states,
+        excluding anything before input ids/embeddings and after
+        the final hidden states.
+        """
+        from vllm.config.utils import get_hash_factors, hash_factors
+
+        ignored_factors: list[str] = []
+        factors = get_hash_factors(self, ignored_factors)
+        return hash_factors(factors)
+
+    @field_validator("backend", mode="before")
+    @classmethod
+    def validate_backend_before(cls, value: Any) -> Any:
+        """Enable parsing of the `backend` enum type from string."""
+        if isinstance(value, str):
+            return AttentionBackendEnum[value.upper()]
+        return value