feat: pybind11 bindings for xllm CUDA kernels

norm.cu compiled successfully on BI-V100 (only warning: fp8 __host__ attr).
Failed at import because no PYBIND11_MODULE — now fixed.

New bindings/ directory with 4 binding files:
  xllm_norm_bind.cpp      → rms_norm, fused_add_rms_norm
  xllm_activation_bind.cpp → silu_and_mul, gelu_and_mul, act_and_mul
  xllm_rope_bind.cpp       → rotary_embedding
  xllm_cache_bind.cpp      → reshape_paged_cache, block_copy

Build script updated: each .so = kernel .cu + binding .cpp

ex_engine/xllm_kernels/cuda/bindings/xllm_activation_bind.cpp

@@ -0,0 +1,18 @@
+// xllm_activation_bind.cpp
+#include <torch/extension.h>
+
+namespace xllm::kernel::cuda {
+void act_and_mul(torch::Tensor out, torch::Tensor input,
+                 const std::string& act_mode);
+}
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("silu_and_mul", [](torch::Tensor out, torch::Tensor input) {
+        xllm::kernel::cuda::act_and_mul(out, input, "silu");
+    }, "SiLU and Mul", py::arg("out"), py::arg("input"));
+    m.def("gelu_and_mul", [](torch::Tensor out, torch::Tensor input) {
+        xllm::kernel::cuda::act_and_mul(out, input, "gelu");
+    }, "GELU and Mul", py::arg("out"), py::arg("input"));
+    m.def("act_and_mul", &xllm::kernel::cuda::act_and_mul,
+          "Activation and Mul", py::arg("out"), py::arg("input"), py::arg("act_mode"));
+}

ex_engine/xllm_kernels/cuda/bindings/xllm_cache_bind.cpp

@@ -0,0 +1,19 @@
+// xllm_cache_bind.cpp
+#include <torch/extension.h>
+
+namespace xllm::kernel::cuda {
+void reshape_paged_cache(torch::Tensor slot_ids, torch::Tensor keys,
+                         torch::Tensor values, torch::Tensor key_cache,
+                         torch::Tensor value_cache);
+void block_copy(torch::Tensor key_cache_ptrs, torch::Tensor value_cache_ptrs,
+                torch::Tensor src_block_indices, torch::Tensor dst_block_indices,
+                torch::Tensor cum_sum, int64_t numel_per_block,
+                torch::ScalarType cache_dtype);
+}
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("reshape_paged_cache", &xllm::kernel::cuda::reshape_paged_cache,
+          "Reshape Paged KV Cache");
+    m.def("block_copy", &xllm::kernel::cuda::block_copy,
+          "Block Copy for KV Cache");
+}

ex_engine/xllm_kernels/cuda/bindings/xllm_norm_bind.cpp

@@ -0,0 +1,24 @@
+// xllm_norm_bind.cpp — pybind11 entry point for xllm norm kernels
+// Compiled together with norm.cu to produce xllm_norm.so
+//
+// Exports: rms_norm, fused_add_rms_norm
+
+#include <torch/extension.h>
+
+namespace xllm::kernel::cuda {
+void rms_norm(torch::Tensor output, torch::Tensor input,
+              torch::Tensor weight, double eps);
+void fused_add_rms_norm(torch::Tensor& input, torch::Tensor& residual,
+                        torch::Tensor& weight, double epsilon);
+}  // namespace xllm::kernel::cuda
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("rms_norm", &xllm::kernel::cuda::rms_norm,
+          "RMS Norm (xllm CUDA kernel)",
+          py::arg("output"), py::arg("input"),
+          py::arg("weight"), py::arg("eps") = 1e-6);
+    m.def("fused_add_rms_norm", &xllm::kernel::cuda::fused_add_rms_norm,
+          "Fused Add + RMS Norm (xllm CUDA kernel)",
+          py::arg("input"), py::arg("residual"),
+          py::arg("weight"), py::arg("epsilon") = 1e-6);
+}

ex_engine/xllm_kernels/cuda/bindings/xllm_rope_bind.cpp

@@ -0,0 +1,17 @@
+// xllm_rope_bind.cpp
+#include <torch/extension.h>
+#include <optional>
+
+namespace xllm::kernel::cuda {
+void rotary_embedding(torch::Tensor& positions, torch::Tensor& query,
+                      std::optional<torch::Tensor> key,
+                      torch::Tensor& cos_sin_cache, bool is_neox);
+}
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    m.def("rotary_embedding", &xllm::kernel::cuda::rotary_embedding,
+          "Rotary Position Embedding (xllm CUDA kernel)",
+          py::arg("positions"), py::arg("query"),
+          py::arg("key"), py::arg("cos_sin_cache"),
+          py::arg("is_neox") = true);
+}