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c++ code format (#4527)

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zhupengyang
2025-10-22 17:59:50 +08:00
committed by GitHub
parent d7bcedf421
commit 3a6883ac1a
97 changed files with 8760 additions and 7382 deletions
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350
custom_ops/cpu_ops/rebuild_padding.cc
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@@ -19,7 +19,6 @@
#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
#endif
template <typename T>
void RebuildPaddingCPUImpl(T *output_data,
const T *input_data,
@@ -30,27 +29,27 @@ void RebuildPaddingCPUImpl(T *output_data,
int max_input_length,
int dim_embed,
const int elem_nums) {
for (int i = 0; i < elem_nums; ++i) {
const int bi = i / dim_embed;
const int bias_idx = i % dim_embed;
int seq_id = 0;
for (int i = 0; i < elem_nums; ++i) {
const int bi = i / dim_embed;
const int bias_idx = i % dim_embed;
int seq_id = 0;
if (seq_len_this_time_data[bi] == 0) {
continue;
}
if (seq_lens_decoder_data[bi] == 0 && seq_lens_encoder_data[bi] == 0) {
continue;
}
if (seq_lens_encoder_data[bi] > 0) {
seq_id = seq_lens_encoder_data[bi] - 1;
}
const int ori_token_idx = cu_seqlens_q_data[bi] + seq_id;
const int src_offset = ori_token_idx * dim_embed + bias_idx;
output_data[i] = input_data[src_offset];
if (seq_len_this_time_data[bi] == 0) {
continue;
}
if (seq_lens_decoder_data[bi] == 0 && seq_lens_encoder_data[bi] == 0) {
continue;
}
if (seq_lens_encoder_data[bi] > 0) {
seq_id = seq_lens_encoder_data[bi] - 1;
}
const int ori_token_idx = cu_seqlens_q_data[bi] + seq_id;
const int src_offset = ori_token_idx * dim_embed + bias_idx;
output_data[i] = input_data[src_offset];
}
}
template <typename T>
@@ -64,27 +63,25 @@ void RebuildAppendPaddingCPUImpl(T *output_data,
const int max_input_length,
const int dim_embed,
const int64_t output_elem_nums) {
for (int i = 0; i < output_elem_nums; ++i) {
int out_token_id = i / dim_embed;
int ori_token_id =
out_token_id + output_padding_offset_data[out_token_id];
int bi = ori_token_id / max_input_length;
if (seq_len_this_time_data[bi] == 0 ||
(seq_lens_decoder_data[bi] == 0 &&
seq_lens_encoder_data[bi] == 0)) {
continue;
}
int seq_id = 0;
if (seq_lens_encoder_data[bi] > 0) {
seq_id = seq_lens_encoder_data[bi] - 1;
}
int input_token_id = cu_seqlens_q_data[bi] + seq_id;
int bias_idx = i % dim_embed;
int src_offset = input_token_id * dim_embed + bias_idx;
output_data[i] = input_data[src_offset];
for (int i = 0; i < output_elem_nums; ++i) {
int out_token_id = i / dim_embed;
int ori_token_id = out_token_id + output_padding_offset_data[out_token_id];
int bi = ori_token_id / max_input_length;
if (seq_len_this_time_data[bi] == 0 ||
(seq_lens_decoder_data[bi] == 0 && seq_lens_encoder_data[bi] == 0)) {
continue;
}
int seq_id = 0;
if (seq_lens_encoder_data[bi] > 0) {
seq_id = seq_lens_encoder_data[bi] - 1;
}
int input_token_id = cu_seqlens_q_data[bi] + seq_id;
int bias_idx = i % dim_embed;
int src_offset = input_token_id * dim_embed + bias_idx;
output_data[i] = input_data[src_offset];
}
}
std::vector<paddle::Tensor> RebuildPaddingCPU(
@@ -95,140 +92,139 @@ std::vector<paddle::Tensor> RebuildPaddingCPU(
const paddle::Tensor &seq_lens_encoder,
const paddle::optional<paddle::Tensor> &output_padding_offset,
int max_input_length) {
auto tmp_out_cpu = tmp_out.copy_to(paddle::CPUPlace(), true);
auto cu_seqlens_q_cpu = cu_seqlens_q.copy_to(paddle::CPUPlace(), true);
auto seq_len_this_time_cpu =
seq_len_this_time.copy_to(paddle::CPUPlace(), true);
auto seq_lens_decoder_cpu =
seq_lens_decoder.copy_to(paddle::CPUPlace(), true);
auto seq_lens_encoder_cpu =
seq_lens_encoder.copy_to(paddle::CPUPlace(), true);
paddle::optional<paddle::Tensor> output_padding_offset_cpu;
if (output_padding_offset) {
output_padding_offset_cpu =
output_padding_offset->copy_to(paddle::CPUPlace(), true);
auto tmp_out_cpu = tmp_out.copy_to(paddle::CPUPlace(), true);
auto cu_seqlens_q_cpu = cu_seqlens_q.copy_to(paddle::CPUPlace(), true);
auto seq_len_this_time_cpu =
seq_len_this_time.copy_to(paddle::CPUPlace(), true);
auto seq_lens_decoder_cpu =
seq_lens_decoder.copy_to(paddle::CPUPlace(), true);
auto seq_lens_encoder_cpu =
seq_lens_encoder.copy_to(paddle::CPUPlace(), true);
paddle::optional<paddle::Tensor> output_padding_offset_cpu;
if (output_padding_offset) {
output_padding_offset_cpu =
output_padding_offset->copy_to(paddle::CPUPlace(), true);
}
int token_num = tmp_out_cpu.shape()[0];
int dim_embed = tmp_out_cpu.shape()[1];
int bsz = cu_seqlens_q_cpu.shape()[0] - 1;
paddle::Tensor out;
if (output_padding_offset_cpu) {
int need_delete_token_num = 0;
for (int i = 0; i < bsz; ++i) {
if (seq_lens_encoder_cpu.data<int>()[i] > 0) {
need_delete_token_num += seq_lens_encoder_cpu.data<int>()[i] - 1;
}
}
int output_token_num = token_num - need_delete_token_num;
out = paddle::full({output_token_num, dim_embed},
0,
tmp_out_cpu.dtype(),
paddle::CPUPlace());
} else {
out = paddle::full(
{bsz, dim_embed}, 0, tmp_out_cpu.dtype(), paddle::CPUPlace());
}
int token_num = tmp_out_cpu.shape()[0];
int dim_embed = tmp_out_cpu.shape()[1];
int bsz = cu_seqlens_q_cpu.shape()[0] - 1;
const int *cu_seqlens_q_data = cu_seqlens_q_cpu.data<int>();
const int *seq_len_this_time_data = seq_len_this_time_cpu.data<int>();
const int *seq_lens_decoder_data = seq_lens_decoder_cpu.data<int>();
const int *seq_lens_encoder_data = seq_lens_encoder_cpu.data<int>();
int elem_nums = out.numel();
paddle::Tensor out;
if (output_padding_offset_cpu) {
int need_delete_token_num = 0;
for (int i = 0; i < bsz; ++i) {
if (seq_lens_encoder_cpu.data<int>()[i] > 0) {
need_delete_token_num +=
seq_lens_encoder_cpu.data<int>()[i] - 1;
}
}
int output_token_num = token_num - need_delete_token_num;
out = paddle::full({output_token_num, dim_embed},
0,
tmp_out_cpu.dtype(),
paddle::CPUPlace());
} else {
out = paddle::full(
{bsz, dim_embed}, 0, tmp_out_cpu.dtype(), paddle::CPUPlace());
if (output_padding_offset_cpu) {
const int *output_padding_offset_data =
output_padding_offset_cpu->data<int>();
switch (tmp_out_cpu.dtype()) {
case paddle::DataType::FLOAT32:
RebuildAppendPaddingCPUImpl<float>(out.data<float>(),
tmp_out_cpu.data<float>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::FLOAT16:
RebuildAppendPaddingCPUImpl<paddle::float16>(
out.data<paddle::float16>(),
tmp_out_cpu.data<paddle::float16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::BFLOAT16:
RebuildAppendPaddingCPUImpl<paddle::bfloat16>(
out.data<paddle::bfloat16>(),
tmp_out_cpu.data<paddle::bfloat16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
default:
PD_THROW(
"Unsupported data type for rebuild_padding_cpu. "
"Only float32, float16, and bfloat16 are supported.");
}
const int *cu_seqlens_q_data = cu_seqlens_q_cpu.data<int>();
const int *seq_len_this_time_data = seq_len_this_time_cpu.data<int>();
const int *seq_lens_decoder_data = seq_lens_decoder_cpu.data<int>();
const int *seq_lens_encoder_data = seq_lens_encoder_cpu.data<int>();
int elem_nums = out.numel();
if (output_padding_offset_cpu) {
const int *output_padding_offset_data =
output_padding_offset_cpu->data<int>();
switch (tmp_out_cpu.dtype()) {
case paddle::DataType::FLOAT32:
RebuildAppendPaddingCPUImpl<float>(out.data<float>(),
tmp_out_cpu.data<float>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::FLOAT16:
RebuildAppendPaddingCPUImpl<paddle::float16>(
out.data<paddle::float16>(),
tmp_out_cpu.data<paddle::float16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::BFLOAT16:
RebuildAppendPaddingCPUImpl<paddle::bfloat16>(
out.data<paddle::bfloat16>(),
tmp_out_cpu.data<paddle::bfloat16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
output_padding_offset_data,
max_input_length,
dim_embed,
elem_nums);
break;
default:
PD_THROW(
"Unsupported data type for rebuild_padding_cpu. "
"Only float32, float16, and bfloat16 are supported.");
}
} else {
switch (tmp_out_cpu.dtype()) {
case paddle::DataType::FLOAT32:
RebuildPaddingCPUImpl<float>(out.data<float>(),
tmp_out_cpu.data<float>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::FLOAT16:
RebuildPaddingCPUImpl<paddle::float16>(
out.data<paddle::float16>(),
tmp_out_cpu.data<paddle::float16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::BFLOAT16:
RebuildPaddingCPUImpl<paddle::bfloat16>(
out.data<paddle::bfloat16>(),
tmp_out_cpu.data<paddle::bfloat16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
default:
PD_THROW(
"Unsupported data type for rebuild_padding_cpu. "
"Only float32, float16, and bfloat16 are supported.");
}
} else {
switch (tmp_out_cpu.dtype()) {
case paddle::DataType::FLOAT32:
RebuildPaddingCPUImpl<float>(out.data<float>(),
tmp_out_cpu.data<float>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::FLOAT16:
RebuildPaddingCPUImpl<paddle::float16>(
out.data<paddle::float16>(),
tmp_out_cpu.data<paddle::float16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
case paddle::DataType::BFLOAT16:
RebuildPaddingCPUImpl<paddle::bfloat16>(
out.data<paddle::bfloat16>(),
tmp_out_cpu.data<paddle::bfloat16>(),
cu_seqlens_q_data,
seq_len_this_time_data,
seq_lens_decoder_data,
seq_lens_encoder_data,
max_input_length,
dim_embed,
elem_nums);
break;
default:
PD_THROW(
"Unsupported data type for rebuild_padding_cpu. "
"Only float32, float16, and bfloat16 are supported.");
}
return {out};
}
return {out};
}
std::vector<std::vector<int64_t>> RebuildPaddingInferShape(
@@ -238,13 +234,13 @@ std::vector<std::vector<int64_t>> RebuildPaddingInferShape(
const std::vector<int64_t> &seq_lens_decoder_shape,
const std::vector<int64_t> &seq_lens_encoder_shape,
const paddle::optional<std::vector<int64_t>> &output_padding_offset_shape) {
int64_t dim_embed = tmp_out_shape[1];
if (output_padding_offset_shape) {
return {{-1, dim_embed}};
} else {
int64_t bsz = cu_seqlens_q_shape[0] - 1;
return {{bsz, dim_embed}};
}
int64_t dim_embed = tmp_out_shape[1];
if (output_padding_offset_shape) {
return {{-1, dim_embed}};
} else {
int64_t bsz = cu_seqlens_q_shape[0] - 1;
return {{bsz, dim_embed}};
}
}
std::vector<paddle::DataType> RebuildPaddingInferDtype(
@@ -254,7 +250,7 @@ std::vector<paddle::DataType> RebuildPaddingInferDtype(
const paddle::DataType &seq_lens_decoder_dtype,
const paddle::DataType &seq_lens_encoder_dtype,
const paddle::optional<paddle::DataType> &output_padding_offset_dtype) {
return {tmp_out_dtype};
return {tmp_out_dtype};
}
PD_BUILD_STATIC_OP(rebuild_padding_cpu)