Clean up allocators (#9134)

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

sgl-kernel/csrc/common_extension_rocm.cc

@@ -0,0 +1,119 @@
+/* Copyright 2025 SGLang Team. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <ATen/core/dispatch/Dispatcher.h>
+#include <torch/library.h>
+
+#include "sgl_kernel_ops.h"
+
+TORCH_LIBRARY_EXPAND(sgl_kernel, m) {
+  /*
+   * From csrc/activation
+   */
+  m.def("silu_and_mul(Tensor! out, Tensor input) -> ()");
+  m.impl("silu_and_mul", torch::kCUDA, &silu_and_mul);
+
+  m.def("gelu_tanh_and_mul(Tensor! out, Tensor input) -> ()");
+  m.impl("gelu_tanh_and_mul", torch::kCUDA, &gelu_tanh_and_mul);
+
+  m.def("gelu_and_mul(Tensor! out, Tensor input) -> ()");
+  m.impl("gelu_and_mul", torch::kCUDA, &gelu_and_mul);
+
+  m.def("gelu_quick(Tensor! out, Tensor input) -> ()");
+  m.impl("gelu_quick", torch::kCUDA, &gelu_quick);
+  /*
+   * From csrc/allreduce
+   */
+  m.def(
+      "init_custom_ar(Tensor meta, Tensor rank_data, "
+      "str[] handles, int[] offsets, int rank, "
+      "bool full_nvlink) -> int");
+  m.impl("init_custom_ar", torch::kCUDA, &init_custom_ar);
+
+  m.def("all_reduce_reg(int fa, Tensor inp, Tensor! out) -> ()");
+  m.impl("all_reduce_reg", torch::kCUDA, &all_reduce_reg);
+
+  m.def(
+      "all_reduce_unreg(int fa, Tensor inp, Tensor reg_buffer, Tensor! out) -> "
+      "()");
+  m.impl("all_reduce_unreg", torch::kCUDA, &all_reduce_unreg);
+
+  m.def("dispose", &dispose);
+
+  m.def("meta_size", &meta_size);
+
+  m.def(
+      "register_buffer(int fa, Tensor t, str[] handles, "
+      "int[] offsets) -> ()");
+  m.impl("register_buffer", torch::kCUDA, &register_buffer);
+
+  m.def("get_graph_buffer_ipc_meta", &get_graph_buffer_ipc_meta);
+  m.def("register_graph_buffers", &register_graph_buffers);
+
+  m.def("allocate_meta_buffer", &allocate_meta_buffer);
+  m.impl("allocate_meta_buffer", torch::kCUDA, &allocate_meta_buffer);
+
+  m.def("get_meta_buffer_ipc_handle", &get_meta_buffer_ipc_handle);
+  m.impl("get_meta_buffer_ipc_handle", torch::kCPU, &get_meta_buffer_ipc_handle);
+
+  // quick allreduce
+#ifdef USE_ROCM
+  m.def(
+      "qr_all_reduce(int fa, Tensor inp, Tensor out, int quant_level, bool "
+      "cast_bf2half) -> ()");
+  m.impl("qr_all_reduce", torch::kCUDA, &qr_all_reduce);
+
+  m.def("init_custom_qr", &init_custom_qr);
+  m.def("qr_destroy", &qr_destroy);
+
+  m.def("qr_get_handle", &qr_get_handle);
+
+  m.def("qr_open_handles(int _fa, Tensor[](b!) handles) -> ()");
+  m.impl("qr_open_handles", torch::kCPU, &qr_open_handles);
+
+  // Max input size in bytes
+  m.def("qr_max_size", &qr_max_size);
+#endif
+
+  /*
+   * From csrc/moe
+   */
+  m.def(
+      "moe_align_block_size(Tensor topk_ids, int num_experts, int block_size, Tensor! sorted_token_ids, Tensor! "
+      "experts_ids, Tensor! num_tokens_post_pad, Tensor! cumsum_buffer, bool "
+      "pad_sorted_token_ids) -> ()");
+  m.impl("moe_align_block_size", torch::kCUDA, &moe_align_block_size);
+
+  m.def("topk_softmax(Tensor! topk_weights, Tensor! topk_indices, Tensor gating_output, bool renormalize) -> ()");
+  m.impl("topk_softmax", torch::kCUDA, &topk_softmax);
+
+  /*
+   * From csrc/speculative
+   */
+  m.def(
+      "verify_tree_greedy(Tensor! predicts, Tensor! accept_index, Tensor! accept_token_num, "
+      "Tensor candidates, Tensor retrive_index, Tensor retrive_next_token, Tensor retrive_next_sibling, "
+      "Tensor target_predict, int cuda_stream) -> ()");
+  m.impl("verify_tree_greedy", torch::kCUDA, &verify_tree_greedy);
+
+  m.def(
+      "build_tree_kernel_efficient(Tensor parent_list, Tensor selected_index, Tensor verified_seq_len, "
+      "Tensor! tree_mask, Tensor! positions, Tensor! retrive_index, Tensor! retrive_next_token, "
+      "Tensor! retrive_next_sibling, int topk, int depth, int draft_token_num, int tree_mask_mode) -> "
+      "()");
+  m.impl("build_tree_kernel_efficient", torch::kCUDA, &build_tree_kernel_efficient);
+}
+
+REGISTER_EXTENSION(common_ops)