[Kernel][Hardware][Amd]Custom paged attention kernel for rocm (#8310)

csrc/rocm/torch_bindings.cpp

@@ -0,0 +1,33 @@
+#include "core/registration.h"
+#include "rocm/ops.h"
+
+// Note on op signatures:
+// The X_meta signatures are for the meta functions corresponding to op X.
+// They must be kept in sync with the signature for X. Generally, only
+// functions that return Tensors require a meta function.
+//
+// See the following links for detailed docs on op registration and function
+// schemas.
+// https://docs.google.com/document/d/1_W62p8WJOQQUzPsJYa7s701JXt0qf2OfLub2sbkHOaU/edit#heading=h.ptttacy8y1u9
+// https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/native/README.md#annotations
+
+TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, rocm_ops) {
+  // vLLM custom ops for rocm
+
+  // Custom attention op
+  // Compute the attention between an input query and the cached
+  // keys/values using PagedAttention.
+  rocm_ops.def(
+      "paged_attention(Tensor! out, Tensor exp_sums,"
+      "                Tensor max_logits, Tensor tmp_out,"
+      "                Tensor query, Tensor key_cache,"
+      "                Tensor value_cache, int num_kv_heads,"
+      "                float scale, Tensor block_tables,"
+      "                Tensor context_lens, int block_size,"
+      "                int max_context_len,"
+      "                Tensor? alibi_slopes,"
+      "                str kv_cache_dtype) -> ()");
+  rocm_ops.impl("paged_attention", torch::kCUDA, &paged_attention);
+}
+
+REGISTER_EXTENSION(TORCH_EXTENSION_NAME)