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[Ops] RoPE kernel support theta input #8440

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May 23, 2024
Merged

[Ops] RoPE kernel support theta input #8440

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4a6aab9
[RoPE] feat: support theta
yinfan98 May 14, 2024
519744e
Update modeling.py
yinfan98 May 14, 2024
9784dbf
[RoPE] feat: support theta for qwen
yinfan98 May 14, 2024
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12 changes: 9 additions & 3 deletions csrc/generation/fused_get_rope.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,7 @@ __global__ __launch_bounds__(kBlockSize) void fused_get_rotary_embedding_neox(co
const int32_t prompt_num,
const float inv_head_dim,
const int32_t elem_cnt,
const float theta,
float* rope_embedding) {
/*
In Naive implementation, it will stacks [freqs, freqs]
Expand All @@ -63,7 +64,7 @@ __global__ __launch_bounds__(kBlockSize) void fused_get_rotary_embedding_neox(co
const int64_t position_offset = bsz_idx * max_position_seq_length + seq_idx + prompt_num;
const int32_t half_head_idx = (idx % half_head_dim) * PackSize;
const float exponent_factor = -static_cast<float>(half_head_idx) * inv_head_dim; // * inv_head_dim equals to / head_dim.
const float inv_freq_val = powf(10000.0f, exponent_factor);
const float inv_freq_val = powf(theta, exponent_factor);
const float freqs_val = static_cast<float>(position_ids[position_offset]) * inv_freq_val;
const float cos_embedding_val = cos(freqs_val);
const float sin_embedding_val = sin(freqs_val);
Expand Down Expand Up @@ -100,6 +101,7 @@ __global__ __launch_bounds__(kBlockSize) void fused_get_rotary_embedding(const i
const int32_t prompt_num,
const float inv_head_dim,
const int32_t elem_cnt,
const float theta,
float* rope_embedding) {
/*
In Naive implementation, it will stacks [freqs, freqs]
Expand All @@ -119,7 +121,7 @@ __global__ __launch_bounds__(kBlockSize) void fused_get_rotary_embedding(const i
const int64_t position_offset = bsz_idx * max_position_seq_length + seq_idx + prompt_num;
const int32_t half_head_idx = (idx % half_head_dim) * PackSize;
const float exponent_factor = -static_cast<float>(half_head_idx) * inv_head_dim; // * inv_head_dim equals to / head_dim.
const float inv_freq_val = powf(10000.0f, exponent_factor);
const float inv_freq_val = powf(theta, exponent_factor);
const float freqs_val = static_cast<float>(position_ids[position_offset]) * inv_freq_val;
const float cos_embedding_val = cos(freqs_val);
const float sin_embedding_val = sin(freqs_val);
Expand All @@ -145,6 +147,7 @@ std::vector<paddle::Tensor> GetRoPE(const paddle::Tensor& input_ids,
const paddle::Tensor& position_ids,
const paddle::Tensor& head_dim_shape_tensor,
int prompt_num,
float theta,
bool use_neox) {
const int64_t batch_size = input_ids.shape()[0];
const int64_t max_seq_length = input_ids.shape()[1];
Expand All @@ -170,6 +173,7 @@ std::vector<paddle::Tensor> GetRoPE(const paddle::Tensor& input_ids,
prompt_num,
inv_head_dim,
elem_cnt,
theta,
reinterpret_cast<float*>(rotary_embedding.data<float>()));
} else {
fused_get_rotary_embedding<<<grid_size, kBlockSize, 0, cu_stream>>> (
Expand All @@ -181,6 +185,7 @@ std::vector<paddle::Tensor> GetRoPE(const paddle::Tensor& input_ids,
prompt_num,
inv_head_dim,
elem_cnt,
theta,
reinterpret_cast<float*>(rotary_embedding.data<float>()));
}
return {rotary_embedding};
Expand Down Expand Up @@ -209,7 +214,8 @@ PD_BUILD_OP(fused_get_rotary_embedding)
.Inputs({"input_ids", "position_ids", "head_dim_shape_tensor"})
.Outputs({"rotary_embedding"})
.Attrs({"prompt_num: int",
"theta: float",
"use_neox: bool"})
.SetKernelFn(PD_KERNEL(GetRoPE))
.SetInferShapeFn(PD_INFER_SHAPE(GetRoPEInferShape))
.SetInferDtypeFn(PD_INFER_DTYPE(GetRoPEInferDtype));
.SetInferDtypeFn(PD_INFER_DTYPE(GetRoPEInferDtype));
3 changes: 2 additions & 1 deletion paddlenlp/experimental/transformers/llama/modeling.py
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Expand Up @@ -432,10 +432,11 @@
seq_lens = seq_len_decoder if is_decoder else seq_len_encoder

position_offset = 0
theta = 10000.0

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paddlenlp/experimental/transformers/llama/modeling.py#L435 

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if not is_decoder and pre_caches is not None:
position_offset = 128
new_rope = fused_get_rotary_embedding(
input_ids, position_ids, self.head_dim_shape_tensor, position_offset, True
input_ids, position_ids, self.head_dim_shape_tensor, position_offset, theta, True
)

with dy2st_nocheck_guard_context():
Expand Down
3 changes: 2 additions & 1 deletion paddlenlp/experimental/transformers/qwen/modeling.py
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Expand Up @@ -320,11 +320,12 @@
seq_lens = seq_len_decoder if is_decoder else seq_len_encoder

position_offset = 0
theta = 10000.0

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if not is_decoder and pre_caches is not None:
position_offset = 128

new_rope = fused_get_rotary_embedding(
input_ids, position_ids, self.head_dim_shape_tensor, position_offset, True
input_ids, position_ids, self.head_dim_shape_tensor, position_offset, theta, True
)

with dy2st_nocheck_guard_context():
Expand Down
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