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Add greedy verification kernel (#4383)

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This commit is contained in:
Ying Sheng
2025-03-16 00:58:26 -07:00
committed by GitHub
parent 06d12b39d3
commit 52a34d7448
11 changed files with 394 additions and 153 deletions
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229
sgl-kernel/csrc/speculative/eagle_utils.cu
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@@ -17,6 +17,8 @@
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include "pytorch_extension_utils.h"
// parent_list [bs, topk * (depth - 1) + 1)]
// selected_index [bs, draft_token_num - 1]
// verified_seq_len [bs]
@@ -72,8 +74,8 @@ __global__ void build_tree_efficient(
}
if (parent_position == draft_token_num) {
printf(
"ERROR: invalid eagle tree!!! Detected a token with no parent token selected. Check the logprob. The token "
"will be dropped.");
"WARNING: invalid eagle tree!!! Detected a token with no parent token selected. "
"Please check if the logprob has nan. The token will be ignored to keep proceeding.\n");
continue;
}
@@ -140,112 +142,141 @@ void build_tree_kernel_efficient(
int32_t(draft_token_num));
}
// parent_list [bs, topk * (depth - 1) + 1)]
// selected_index [bs, draft_token_num - 1]
// verified_seq_len [bs]
// tree_mask [draft_token*(seq_len[0]+draft_token) | draft_token*(seq_len[1]+draft_token) | ..] =
// [sum(verified_seq_len)*draft_token+bs*draft_token*draft_token] positions [bs * draft_token] retrive_index [b,
// draft_token, depth + 2]
__global__ void build_tree(
int64_t* parent_list,
int64_t* selected_index,
int32_t* verified_seq_len,
bool* tree_mask,
int64_t* positions,
int64_t* retrive_index,
int topk,
int depth,
int draft_token_num) {
int bid = blockIdx.x;
int tid = threadIdx.x;
template <typename IdType>
__global__ void VerifyTreeGreedy(
IdType* predicts,
IdType* accept_index,
IdType* accept_token_num, // mutable
IdType* candidates,
IdType* retrive_index,
IdType* retrive_next_token,
IdType* retrive_next_sibling,
IdType* target_predict,
uint32_t batch_size,
uint32_t num_speculative_tokens,
uint32_t num_draft_tokens) {
uint32_t bx = blockIdx.x;
if (tid >= draft_token_num) {
return;
}
int seq_tree_idx = draft_token_num * draft_token_num * bid;
for (int i = 0; i < bid; i++) {
seq_tree_idx += verified_seq_len[i] * draft_token_num;
}
int seq_len = verified_seq_len[bid];
int token_tree_idx = seq_tree_idx + (seq_len + draft_token_num) * tid + seq_len + 1;
for (int i = 0; i < draft_token_num - 1; i++) {
tree_mask[token_tree_idx + i] = false;
}
IdType last_accepted_retrive_idx = retrive_index[bx * num_draft_tokens];
accept_index[bx * num_speculative_tokens] = last_accepted_retrive_idx;
uint32_t num_accepted_tokens = 0;
IdType cur_index = 0;
int position = 0;
if (tid == 0) {
positions[bid * draft_token_num] = seq_len;
retrive_index[bid * draft_token_num * (depth + 2)] = bid * draft_token_num;
return;
}
for (uint32_t j = 1; j < num_speculative_tokens; ++j) {
cur_index = retrive_next_token[bx * num_draft_tokens + cur_index];
while (cur_index != -1) {
IdType draft_index = retrive_index[bx * num_draft_tokens + cur_index];
IdType draft_token_id = candidates[bx * num_draft_tokens + cur_index];
IdType target_token_id = target_predict[last_accepted_retrive_idx];
int depends_order[10];
int cur_position = tid - 1;
while (true) {
depends_order[position] = cur_position + 1;
position += 1;
tree_mask[token_tree_idx + cur_position] = true;
int parent_tb_idx = selected_index[bid * (draft_token_num - 1) + cur_position] / topk;
if (parent_tb_idx == 0) {
break;
}
int token_idx = parent_list[bid * (topk * (depth - 1) + 1) + parent_tb_idx];
for (cur_position = 0; cur_position < draft_token_num; cur_position++) {
if (selected_index[bid * (draft_token_num - 1) + cur_position] == token_idx) {
if (draft_token_id == target_token_id) {
// accept token
predicts[last_accepted_retrive_idx] = target_token_id;
++num_accepted_tokens;
accept_index[bx * num_speculative_tokens + num_accepted_tokens] = draft_index;
last_accepted_retrive_idx = draft_index;
break;
} else {
cur_index = retrive_next_sibling[bx * num_draft_tokens + cur_index];
}
}
if (cur_position == draft_token_num) {
printf(
"ERROR: invalid eagle tree!!! Detected a token with no parent token selected. Check the logprob. The token "
"will be dropped.");
break;
}
}
positions[bid * draft_token_num + tid] = position + seq_len;
int is_leaf = 0;
for (int i = 1; i < draft_token_num; i++) {
if (tree_mask[seq_tree_idx + i * (draft_token_num + seq_len) + seq_len + tid]) {
is_leaf++;
}
}
if (is_leaf == 1) {
for (int i = 0; i < position; i++) {
retrive_index[(bid * (draft_token_num) + tid) * (depth + 2) + position - i] =
depends_order[i] + bid * draft_token_num;
}
retrive_index[(bid * (draft_token_num) + tid) * (depth + 2)] = bid * draft_token_num;
if (cur_index == -1) break;
}
accept_token_num[bx] = num_accepted_tokens;
predicts[last_accepted_retrive_idx] = target_predict[last_accepted_retrive_idx];
}
void build_tree_kernel(
at::Tensor parent_list,
at::Tensor selected_index,
at::Tensor verified_seq_len,
at::Tensor tree_mask,
at::Tensor positions,
// predicts: [tot_num_draft_tokens]
// accept_index: [bs, num_spec_step]
// accept_token_num: [bs]
// candidates: [bs, num_draft_tokens]
// retrive_index: [bs, num_draft_tokens]
// retrive_next_token: [bs, num_draft_tokens]
// retrive_next_sibling: [bs, num_draft_tokens]
// target_predict: [bs, num_draft_tokens]
void verify_tree_greedy(
at::Tensor predicts,
at::Tensor accept_index,
at::Tensor accept_token_num, // mutable
at::Tensor candidates,
at::Tensor retrive_index,
int64_t topk,
int64_t depth,
int64_t draft_token_num) {
// TODO (ying) check shape
// TODO (ying) check type
int bs = parent_list.size(0);
dim3 grid(bs);
dim3 block(draft_token_num);
const cudaStream_t stream = at::cuda::getCurrentCUDAStream();
at::Tensor retrive_next_token,
at::Tensor retrive_next_sibling,
at::Tensor target_predict,
int64_t cuda_stream = 0) {
CHECK_INPUT(candidates);
CHECK_INPUT(retrive_index);
CHECK_INPUT(retrive_next_token);
CHECK_INPUT(retrive_next_sibling);
CHECK_INPUT(target_predict);
auto device = target_predict.device();
CHECK_EQ(candidates.device(), device);
CHECK_EQ(retrive_index.device(), device);
CHECK_EQ(retrive_next_token.device(), device);
CHECK_EQ(retrive_next_sibling.device(), device);
CHECK_EQ(target_predict.device(), device);
CHECK_DIM(1, predicts);
CHECK_DIM(2, accept_index);
CHECK_DIM(1, accept_token_num);
CHECK_DIM(2, candidates);
CHECK_DIM(2, retrive_index);
CHECK_DIM(2, retrive_next_token);
CHECK_DIM(2, retrive_next_sibling);
CHECK_DIM(2, target_predict);
unsigned int batch_size = candidates.size(0);
unsigned int num_spec_step = accept_index.size(1);
unsigned int num_draft_tokens = candidates.size(1);
CHECK_EQ(batch_size, accept_index.size(0));
CHECK_EQ(batch_size, accept_token_num.size(0));
CHECK_EQ(batch_size, retrive_index.size(0));
CHECK_EQ(batch_size, retrive_next_token.size(0));
CHECK_EQ(batch_size, retrive_next_sibling.size(0));
CHECK_EQ(batch_size, target_predict.size(0));
CHECK_EQ(num_draft_tokens, retrive_index.size(1));
CHECK_EQ(num_draft_tokens, retrive_next_token.size(1));
CHECK_EQ(num_draft_tokens, retrive_next_sibling.size(1));
CHECK_EQ(num_draft_tokens, target_predict.size(1));
CHECK_EQ(batch_size, accept_index.size(0));
CHECK_EQ(batch_size, accept_token_num.size(0));
if (predicts.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'predicts' to be of type int (torch.int32).");
}
if (accept_index.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'accept_index' to be of type int (torch.int32).");
}
if (accept_token_num.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'accept_token_num' to be of type int (torch.int32).");
}
if (candidates.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'candidates' to be of type int (torch.int32).");
}
if (retrive_index.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'retrive_index' to be of type int (torch.int32).");
}
if (retrive_next_token.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'retrive_next_token' to be of type int (torch.int32).");
}
if (retrive_next_sibling.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'retrive_next_sibling' to be of type int (torch.int32).");
}
if (target_predict.scalar_type() != at::kInt) {
throw std::runtime_error("Expected 'target_predict' to be of type int (torch.int32).");
}
build_tree<<<grid, block, 0, stream>>>(
static_cast<int64_t*>(parent_list.data_ptr()),
static_cast<int64_t*>(selected_index.data_ptr()),
static_cast<int32_t*>(verified_seq_len.data_ptr()),
static_cast<bool*>(tree_mask.data_ptr()),
static_cast<int64_t*>(positions.data_ptr()),
static_cast<int64_t*>(retrive_index.data_ptr()),
int32_t(topk),
int32_t(depth),
int32_t(draft_token_num));
cudaStream_t stream = reinterpret_cast<cudaStream_t>(cuda_stream);
dim3 grid(batch_size);
dim3 block(1);
VerifyTreeGreedy<int><<<grid, block, 0, stream>>>(
static_cast<int*>(predicts.data_ptr()),
static_cast<int*>(accept_index.data_ptr()),
static_cast<int*>(accept_token_num.data_ptr()),
static_cast<int*>(candidates.data_ptr()),
static_cast<int*>(retrive_index.data_ptr()),
static_cast<int*>(retrive_next_token.data_ptr()),
static_cast<int*>(retrive_next_sibling.data_ptr()),
static_cast<int*>(target_predict.data_ptr()),
batch_size,
num_spec_step,
num_draft_tokens);
}