[XPU] Remove padding_offsets from get_padding_offset.cu (#2911)

This commit is contained in:
周周周
2025-07-18 14:16:44 +08:00
committed by GitHub
parent 0eb5dc18d3
commit 1339e56282
5 changed files with 24 additions and 24 deletions

View File

@@ -34,7 +34,7 @@ __global__ void RemovePadding(int64_t *output_data,
}
}
__global__ void GetPaddingOffsetKernel(int *padding_offset,
__global__ void GetPaddingOffsetKernel(int *batch_id_per_token,
int *cum_offsets_out,
int *cu_seqlens_q,
int *cu_seqlens_k,
@@ -46,7 +46,7 @@ __global__ void GetPaddingOffsetKernel(int *padding_offset,
const int ti = threadIdx.x;
int cum_offset = bi == 0 ? 0 : cum_offsets[bi - 1];
for (int i = ti; i < seq_lens[bi]; i += blockDim.x) {
padding_offset[bi * max_seq_len - cum_offset + i] = bi;
batch_id_per_token[bi * max_seq_len - cum_offset + i] = bi;
}
if (ti == 0) {
cum_offsets_out[bi] = cum_offset;
@@ -75,7 +75,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
const int token_num_data = cpu_token_num.data<int64_t>()[0];
auto x_remove_padding = paddle::empty(
{token_num_data}, paddle::DataType::INT64, input_ids.place());
auto padding_offset = paddle::empty(
auto batch_id_per_token = paddle::empty(
{token_num_data}, paddle::DataType::INT32, input_ids.place());
auto cu_seqlens_q =
paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
@@ -87,7 +87,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
int blockSize = min((token_num_data + WARP_SIZE - 1) / WARP_SIZE * WARP_SIZE, 128);
#endif
GetPaddingOffsetKernel<<<bsz, 128, 0, cu_stream>>>(
padding_offset.data<int>(),
batch_id_per_token.data<int>(),
cum_offsets_out.data<int>(),
cu_seqlens_q.data<int>(),
cu_seqlens_k.data<int>(),
@@ -102,7 +102,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
seq_length);
return {x_remove_padding,
cum_offsets_out,
padding_offset,
batch_id_per_token,
cu_seqlens_q,
cu_seqlens_k}; // , enc_token_num, dec_token_num};
}
@@ -133,7 +133,7 @@ PD_BUILD_STATIC_OP(get_padding_offset)
.Inputs({"input_ids", "token_num", "cum_offsets", "seq_len"})
.Outputs({"x_remove_padding",
"cum_offsets_out",
"padding_offset",
"batch_id_per_token",
"cu_seqlens_q",
"cu_seqlens_k"})
.SetKernelFn(PD_KERNEL(GetPaddingOffset))

View File

@@ -41,7 +41,7 @@ __global__ void SpeculateRemovePadding(int64_t* output_data,
}
}
__global__ void SpeculateGetPaddingOffsetKernel(int* padding_offset,
__global__ void SpeculateGetPaddingOffsetKernel(int* batch_id_per_token,
int* cum_offsets_out,
int* cu_seqlens_q,
int* cu_seqlens_k,
@@ -53,7 +53,7 @@ __global__ void SpeculateGetPaddingOffsetKernel(int* padding_offset,
const int ti = threadIdx.x;
int cum_offset = bi == 0 ? 0 : cum_offsets[bi - 1];
for (int i = ti; i < seq_lens[bi]; i += blockDim.x) {
padding_offset[bi * max_seq_len - cum_offset + i] = bi;
batch_id_per_token[bi * max_seq_len - cum_offset + i] = bi;
}
if (ti == 0) {
cum_offsets_out[bi] = cum_offset;
@@ -81,7 +81,7 @@ std::vector<paddle::Tensor> SpeculateGetPaddingOffset(
const int token_num_data = cpu_token_num.data<int64_t>()[0];
auto x_remove_padding = paddle::full(
{token_num_data}, 0, paddle::DataType::INT64, input_ids.place());
auto padding_offset = paddle::full(
auto batch_id_per_token = paddle::full(
{token_num_data}, 0, paddle::DataType::INT32, input_ids.place());
auto cu_seqlens_q =
paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
@@ -89,7 +89,7 @@ std::vector<paddle::Tensor> SpeculateGetPaddingOffset(
paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
int blockSize = min((token_num_data + 32 - 1) / 32 * 32, 128);
SpeculateGetPaddingOffsetKernel<<<bsz, 128, 0, cu_stream>>>(
padding_offset.data<int>(),
batch_id_per_token.data<int>(),
cum_offsets_out.data<int>(),
cu_seqlens_q.data<int>(),
cu_seqlens_k.data<int>(),
@@ -107,7 +107,7 @@ std::vector<paddle::Tensor> SpeculateGetPaddingOffset(
max_draft_tokens);
return {x_remove_padding,
cum_offsets_out,
padding_offset,
batch_id_per_token,
cu_seqlens_q,
cu_seqlens_k}; // , enc_token_num, dec_token_num};
}
@@ -147,7 +147,7 @@ PD_BUILD_STATIC_OP(speculate_get_padding_offset)
"seq_lens_encoder"})
.Outputs({"x_remove_padding",
"cum_offsets_out",
"padding_offset",
"batch_id_per_token",
"cu_seqlens_q",
"cu_seqlens_k"})
.SetKernelFn(PD_KERNEL(SpeculateGetPaddingOffset))

View File

@@ -34,7 +34,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
const int token_num_data = cpu_token_num.data<int64_t>()[0];
auto x_remove_padding = paddle::full(
{token_num_data}, 0, paddle::DataType::INT64, input_ids.place());
auto padding_offset = paddle::full(
auto batch_id_per_token = paddle::full(
{token_num_data}, 0, paddle::DataType::INT32, input_ids.place());
auto cu_seqlens_q =
paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
@@ -42,7 +42,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
int r = baidu::xpu::api::plugin::get_padding_offset(
xpu_ctx->x_context(),
padding_offset.data<int>(),
batch_id_per_token.data<int>(),
cum_offsets_out.data<int>(),
cu_seqlens_q.data<int>(),
cu_seqlens_k.data<int>(),
@@ -55,7 +55,7 @@ std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
PD_CHECK(r == 0, "baidu::xpu::api::plugin::get_padding_offset failed.");
return {x_remove_padding,
cum_offsets_out,
padding_offset,
batch_id_per_token,
cu_seqlens_q,
cu_seqlens_k};
}
@@ -86,7 +86,7 @@ PD_BUILD_OP(get_padding_offset)
.Inputs({"input_ids", "cum_offsets", "token_num", "seq_len"})
.Outputs({"x_remove_padding",
"cum_offsets_out",
"padding_offset",
"batch_id_per_token",
"cu_seqlens_q",
"cu_seqlens_k"})
.SetKernelFn(PD_KERNEL(GetPaddingOffset))

View File

@@ -5,7 +5,7 @@
namespace xpu3 {
namespace plugin {
__global__ void get_padding_offset(int *padding_offset,
__global__ void get_padding_offset(int *batch_id_per_token,
int *cum_offsets_out,
int *cu_seqlens_q,
int *cu_seqlens_k,
@@ -20,7 +20,7 @@ __global__ void get_padding_offset(int *padding_offset,
int tid = clusterid * ncores + cid;
int buf_len = 32;
__simd__ int padding_offset_lm[buf_len];
__simd__ int batch_id_per_token_lm[buf_len];
__simd__ int cum_offsets_lm[16];
int seq_len_lm;
for (int i = clusterid; i < bs; i += nclusters) {
@@ -32,11 +32,11 @@ __global__ void get_padding_offset(int *padding_offset,
for (int j = cid * buf_len; j < seq_len_lm; j += ncores * buf_len) {
int cur_len = min(seq_len_lm - j, buf_len);
for (int k = 0; k < cur_len; k++) {
padding_offset_lm[k] = cum_offsets_lm[0];
batch_id_per_token_lm[k] = i;
}
mfence_lm();
LM2GM(padding_offset_lm,
padding_offset + i * max_seq_len - cum_offsets_lm[0] + j,
LM2GM(batch_id_per_token_lm,
batch_id_per_token + i * max_seq_len - cum_offsets_lm[0] + j,
cur_len * sizeof(int));
}
if (cid == 0) {