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[SYCL] Update SYCL-Rope op and Refactor (#8157)

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* align with rope.cu and move sycl-op to a single file
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zhentaoyu 2024-07-01 19:39:06 +08:00 committed by GitHub
parent d0a7145ba9
commit 197fe6c1d7
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4 changed files with 300 additions and 303 deletions
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305
ggml/src/ggml-sycl.cpp
View File

@ -978,114 +978,6 @@ static void cpy_f32_q(const char * cx, char * cdst, const int ne,
cpy_blck(cx + x_offset, cdst + dst_offset);
}
static float rope_yarn_ramp(const float low, const float high, const int i0) {
const float y = (i0 / 2 - low) / sycl::max(0.001f, high - low);
return 1.0f - sycl::min(1.0f, sycl::max(0.0f, y));
}
struct rope_corr_dims {
float v[4];
};
// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
static void rope_yarn(
float theta_extrap, float freq_scale, rope_corr_dims corr_dims, int64_t i0, float ext_factor, float mscale,
float * cos_theta, float * sin_theta
) {
// Get n-d rotational scaling corrected for extrapolation
float theta_interp = freq_scale * theta_extrap;
float theta = theta_interp;
if (ext_factor != 0.0f) {
float ramp_mix = rope_yarn_ramp(corr_dims.v[0], corr_dims.v[1], i0) * ext_factor;
theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
// Get n-d magnitude scaling corrected for interpolation
mscale *= 1.0f + 0.1f * sycl::log(1.0f / freq_scale);
}
*cos_theta = sycl::cos(theta) * mscale;
*sin_theta = sycl::sin(theta) * mscale;
}
// rope == RoPE == rotary positional embedding
template<typename T, bool has_pos>
static void rope(
const T * x, T * dst, int ncols, const int32_t * pos, float freq_scale, int p_delta_rows, float freq_base,
float ext_factor, float attn_factor, rope_corr_dims corr_dims
,
const sycl::nd_item<3> &item_ct1) {
const int col = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
item_ct1.get_local_id(1));
if (col >= ncols) {
return;
}
const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
item_ct1.get_local_id(2);
const int i = row*ncols + col;
const int i2 = row/p_delta_rows;
const int p = has_pos ? pos[i2] : 0;
const float theta_base = p * dpct::pow(freq_base, -float(col) / ncols);
float cos_theta, sin_theta;
rope_yarn(theta_base, freq_scale, corr_dims, col, ext_factor, attn_factor, &cos_theta, &sin_theta);
const float x0 = x[i + 0];
const float x1 = x[i + 1];
dst[i + 0] = x0*cos_theta - x1*sin_theta;
dst[i + 1] = x0*sin_theta + x1*cos_theta;
}
template<typename T, bool has_pos, bool has_freq_facs>
static void rope_neox(
const T * x, T * dst, int ncols, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, float inv_ndims,
const float * freq_factors, const sycl::nd_item<3> &item_ct1) {
const int col = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
item_ct1.get_local_id(1));
if (col >= ncols) {
return;
}
const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
item_ct1.get_local_id(2);
const int ib = col / n_dims;
const int ic = col % n_dims;
if (ib > 0) {
const int i = row*ncols + ib*n_dims + ic;
dst[i + 0] = x[i + 0];
dst[i + 1] = x[i + 1];
return;
}
const int i = row*ncols + ib*n_dims + ic/2;
const int i2 = row/p_delta_rows;
float cur_rot = inv_ndims * ic - ib;
const int p = has_pos ? pos[i2] : 0;
const float freq_factor = has_freq_facs ? freq_factors[ic/2] : 1.0f;
const float theta_base =
p * freq_scale * dpct::pow(theta_scale, col / 2.0f)/freq_factor;
float cos_theta, sin_theta;
rope_yarn(theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta);
const float x0 = x[i + 0];
const float x1 = x[i + n_dims/2];
dst[i + 0] = x0*cos_theta - x1*sin_theta;
dst[i + n_dims/2] = x0*sin_theta + x1*cos_theta;
}
static void k_sum_rows_f32(const float * x, float * dst, const int ncols,
const sycl::nd_item<3> &item_ct1) {
const int row = item_ct1.get_group(1);
@ -2241,110 +2133,6 @@ static void clamp_f32_sycl(const float *x, float *dst, const float min,
});
}
template <typename T>
static void rope_sycl(const T *x, T *dst, int ncols, int nrows,
const int32_t *pos, float freq_scale, int p_delta_rows,
float freq_base, float ext_factor, float attn_factor,
rope_corr_dims corr_dims, queue_ptr stream) {
GGML_ASSERT(ncols % 2 == 0);
const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
const int num_blocks_x = (ncols + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
const sycl::range<3> block_nums(1, num_blocks_x, nrows);
if (pos == nullptr) {
/*
DPCT1049:40: The work-group size passed to the SYCL kernel may exceed
the limit. To get the device limit, query
info::device::max_work_group_size. Adjust the work-group size if needed.
*/
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope<T, false>(x, dst, ncols, pos, freq_scale, p_delta_rows,
freq_base, ext_factor, attn_factor, corr_dims,
item_ct1);
});
} else {
/*
DPCT1049:41: The work-group size passed to the SYCL kernel may exceed
the limit. To get the device limit, query
info::device::max_work_group_size. Adjust the work-group size if needed.
*/
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope<T, true>(x, dst, ncols, pos, freq_scale, p_delta_rows,
freq_base, ext_factor, attn_factor, corr_dims,
item_ct1);
});
}
}
template <typename T>
static void rope_neox_sycl(const T *x, T *dst, int ncols, int n_dims, int nrows,
const int32_t *pos, float freq_scale,
int p_delta_rows, float freq_base, float ext_factor,
float attn_factor, rope_corr_dims corr_dims,
const float * freq_factors, queue_ptr stream) {
GGML_ASSERT(ncols % 2 == 0);
const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
const int num_blocks_x = (ncols + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
const sycl::range<3> block_nums(1, num_blocks_x, nrows);
const float theta_scale = powf(freq_base, -2.0f/n_dims);
const float inv_ndims = -1.0f / n_dims;
if (pos == nullptr) {
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
if (freq_factors == nullptr) {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, false, false>(x, dst, ncols, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, inv_ndims, freq_factors,
item_ct1);
});
} else {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, false, true>(x, dst, ncols, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, inv_ndims, freq_factors,
item_ct1);
});
}
} else {
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
if (freq_factors == nullptr) {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, true, false>(x, dst, ncols, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, inv_ndims, freq_factors, item_ct1);
});
} else {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, true, true>(x, dst, ncols, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, inv_ndims, freq_factors, item_ct1);
});
}
}
}
static void sum_rows_f32_sycl(const float *x, float *dst, const int ncols,
const int nrows, queue_ptr stream) {
const sycl::range<3> block_dims(1, 1, WARP_SIZE);
@ -3461,97 +3249,6 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
inline void ggml_sycl_op_rope(ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1,
ggml_tensor *dst, const float *src0_dd,
const float *src1_dd, float *dst_dd,
const queue_ptr &main_stream) {
const ggml_tensor * src2 = dst->src[2];
GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
GGML_ASSERT( dst->type == GGML_TYPE_F32 || dst->type == GGML_TYPE_F16);
GGML_ASSERT(src0->type == dst->type);
const int64_t ne00 = src0->ne[0];
const int64_t ne01 = src0->ne[1];
const int64_t ne2 = dst->ne[2];
const int64_t nrows = ggml_nrows(src0);
//const int n_past = ((int32_t *) dst->op_params)[0];
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
//const int n_ctx = ((int32_t *) dst->op_params)[3];
const int n_ctx_orig = ((int32_t *) dst->op_params)[4];
// RoPE alteration for extended context
float freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow;
memcpy(&freq_base, (int32_t *) dst->op_params + 5, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->op_params + 6, sizeof(float));
memcpy(&ext_factor, (int32_t *) dst->op_params + 7, sizeof(float));
memcpy(&attn_factor, (int32_t *) dst->op_params + 8, sizeof(float));
memcpy(&beta_fast, (int32_t *) dst->op_params + 9, sizeof(float));
memcpy(&beta_slow, (int32_t *) dst->op_params + 10, sizeof(float));
const float * freq_factors = nullptr;
const int32_t * pos = nullptr;
if ((mode & 1) == 0) {
GGML_ASSERT(src1->type == GGML_TYPE_I32);
GGML_ASSERT(src1->ne[0] == ne2);
pos = (const int32_t *) src1_dd;
}
const bool is_neox = mode & 2;
#pragma message("TODO: update rope NORM mode to match NEOX mode")
#pragma message(" https://github.com/ggerganov/llama.cpp/pull/7634")
if (is_neox) {
pos = (const int32_t *) src1_dd;
if (src2 != nullptr) {
freq_factors = (const float *) src2->data;
}
} else {
GGML_ASSERT(src2 == nullptr && "TODO: freq_factors not implemented for !is_neox");
}
rope_corr_dims corr_dims;
ggml_rope_yarn_corr_dims(n_dims, n_ctx_orig, freq_base, beta_fast, beta_slow, corr_dims.v);
// compute
if (is_neox) {
if (src0->type == GGML_TYPE_F32) {
rope_neox_sycl(
(const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, freq_factors, main_stream
);
} else if (src0->type == GGML_TYPE_F16) {
rope_neox_sycl((const sycl::half *)src0_dd, (sycl::half *)dst_dd,
ne00, n_dims, nrows, pos, freq_scale, ne01,
freq_base, ext_factor, attn_factor, corr_dims,
freq_factors, main_stream);
} else {
GGML_ASSERT(false);
}
} else {
if (src0->type == GGML_TYPE_F32) {
rope_sycl(
(const float *)src0_dd, (float *)dst_dd, ne00, nrows, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, main_stream
);
} else if (src0->type == GGML_TYPE_F16) {
rope_sycl((const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00,
nrows, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, main_stream);
} else {
GGML_ASSERT(false);
}
}
(void) src1;
(void) dst;
(void) src1_dd;
}
static void ggml_sycl_op_pool2d(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
const ggml_tensor *src1, ggml_tensor *dst,
const float *src0_dd, const float *src1_dd,
@ -6241,7 +5938,9 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
case GGML_OP_CONT:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_SOFT_MAX:
return true;
case GGML_OP_ROPE:
return ggml_is_contiguous(op->src[0]);
case GGML_OP_IM2COL:
case GGML_OP_POOL_2D:
case GGML_OP_SUM_ROWS:

1
ggml/src/ggml-sycl/backend.hpp
View File

@ -19,5 +19,6 @@
#include "dmmv.hpp"
#include "mmq.hpp"
#include "mmvq.hpp"
#include "rope.hpp"
#endif // GGML_SYCL_BACKEND_HPP

275
ggml/src/ggml-sycl/rope.cpp Normal file
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@ -0,0 +1,275 @@
#include "rope.hpp"
struct rope_corr_dims {
float v[2];
};
static float rope_yarn_ramp(const float low, const float high, const int i0) {
const float y = (i0 / 2 - low) / sycl::max(0.001f, high - low);
return 1.0f - sycl::min(1.0f, sycl::max(0.0f, y));
}
// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
static void rope_yarn(
float theta_extrap, float freq_scale, rope_corr_dims corr_dims, int64_t i0, float ext_factor, float mscale,
float * cos_theta, float * sin_theta) {
// Get n-d rotational scaling corrected for extrapolation
float theta_interp = freq_scale * theta_extrap;
float theta = theta_interp;
if (ext_factor != 0.0f) {
float ramp_mix = rope_yarn_ramp(corr_dims.v[0], corr_dims.v[1], i0) * ext_factor;
theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
// Get n-d magnitude scaling corrected for interpolation
mscale *= 1.0f + 0.1f * sycl::log(1.0f / freq_scale);
}
*cos_theta = sycl::cos(theta) * mscale;
*sin_theta = sycl::sin(theta) * mscale;
}
template<typename T, bool has_ff>
static void rope_norm(
const T * x, T * dst, int ne0, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, const float * freq_factors,
const sycl::nd_item<3> &item_ct1) {
const int i0 = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
item_ct1.get_local_id(1));
if (i0 >= ne0) {
return;
}
const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
item_ct1.get_local_id(2);
if (i0 >= n_dims) {
const int i = row*ne0 + i0;
dst[i + 0] = x[i + 0];
dst[i + 1] = x[i + 1];
return;
}
const int i = row*ne0 + i0;
const int i2 = row/p_delta_rows;
const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
float cos_theta;
float sin_theta;
rope_yarn(theta_base/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta);
const float x0 = x[i + 0];
const float x1 = x[i + 1];
dst[i + 0] = x0*cos_theta - x1*sin_theta;
dst[i + 1] = x0*sin_theta + x1*cos_theta;
}
template<typename T, bool has_ff>
static void rope_neox(
const T * x, T * dst, int ne0, int n_dims, const int32_t * pos, float freq_scale, int p_delta_rows,
float ext_factor, float attn_factor, rope_corr_dims corr_dims, float theta_scale, const float * freq_factors,
const sycl::nd_item<3> &item_ct1) {
const int i0 = 2 * (item_ct1.get_local_range(1) * item_ct1.get_group(1) +
item_ct1.get_local_id(1));
if (i0 >= ne0) {
return;
}
const int row = item_ct1.get_local_range(2) * item_ct1.get_group(2) +
item_ct1.get_local_id(2);
if (i0 >= n_dims) {
const int i = row*ne0 + i0;
dst[i + 0] = x[i + 0];
dst[i + 1] = x[i + 1];
return;
}
const int i = row*ne0 + i0/2;
const int i2 = row/p_delta_rows;
const float theta_base = pos[i2]*powf(theta_scale, i0/2.0f);
const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
float cos_theta;
float sin_theta;
rope_yarn(theta_base/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta);
const float x0 = x[i + 0];
const float x1 = x[i + n_dims/2];
dst[i + 0] = x0*cos_theta - x1*sin_theta;
dst[i + n_dims/2] = x0*sin_theta + x1*cos_theta;
}
template <typename T>
static void rope_norm_sycl(
const T *x, T *dst, int ne0, int n_dims, int nr, const int32_t *pos, float freq_scale, int p_delta_rows,
float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, queue_ptr stream) {
GGML_ASSERT(ne0 % 2 == 0);
const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
const int num_blocks_x = (ne0 + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
const sycl::range<3> block_nums(1, num_blocks_x, nr);
const float theta_scale = powf(freq_base, -2.0f/n_dims);
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
if (freq_factors == nullptr) {
/*
DPCT1049:40: The work-group size passed to the SYCL kernel may exceed
the limit. To get the device limit, query
info::device::max_work_group_size. Adjust the work-group size if needed.
*/
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_norm<T, false>(x, dst, ne0, n_dims, pos, freq_scale, p_delta_rows,
ext_factor, attn_factor, corr_dims, theta_scale, freq_factors,
item_ct1);
});
} else {
/*
DPCT1049:41: The work-group size passed to the SYCL kernel may exceed
the limit. To get the device limit, query
info::device::max_work_group_size. Adjust the work-group size if needed.
*/
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_norm<T, true>(x, dst, ne0, n_dims, pos, freq_scale, p_delta_rows,
ext_factor, attn_factor, corr_dims, theta_scale, freq_factors,
item_ct1);
});
}
}
template <typename T>
static void rope_neox_sycl(
const T *x, T *dst, int ne0, int n_dims, int nr, const int32_t *pos, float freq_scale, int p_delta_rows,
float freq_base, float ext_factor, float attn_factor, rope_corr_dims corr_dims, const float * freq_factors, queue_ptr stream) {
GGML_ASSERT(ne0 % 2 == 0);
const sycl::range<3> block_dims(1, SYCL_ROPE_BLOCK_SIZE, 1);
const int num_blocks_x = (ne0 + 2*SYCL_ROPE_BLOCK_SIZE - 1) / (2*SYCL_ROPE_BLOCK_SIZE);
const sycl::range<3> block_nums(1, num_blocks_x, nr);
const float theta_scale = powf(freq_base, -2.0f/n_dims);
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
if (freq_factors == nullptr) {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, false>(x, dst, ne0, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, freq_factors,
item_ct1);
});
} else {
stream->parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
rope_neox<T, true>(x, dst, ne0, n_dims, pos, freq_scale,
p_delta_rows, ext_factor, attn_factor,
corr_dims, theta_scale, freq_factors,
item_ct1);
});
}
}
void ggml_sycl_op_rope(
ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst,
const float *src0_dd, const float *src1_dd, float *dst_dd, const queue_ptr &main_stream) {
const ggml_tensor * src2 = dst->src[2];
GGML_ASSERT(src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16);
GGML_ASSERT( dst->type == GGML_TYPE_F32 || dst->type == GGML_TYPE_F16);
GGML_ASSERT(src0->type == dst->type);
const int64_t ne00 = src0->ne[0];
const int64_t ne01 = src0->ne[1];
const int64_t nr = ggml_nrows(src0);
//const int n_past = ((int32_t *) dst->op_params)[0];
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
//const int n_ctx = ((int32_t *) dst->op_params)[3];
const int n_ctx_orig = ((int32_t *) dst->op_params)[4];
// RoPE alteration for extended context
float freq_base;
float freq_scale;
float ext_factor;
float attn_factor;
float beta_fast;
float beta_slow;
memcpy(&freq_base, (int32_t *) dst->op_params + 5, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->op_params + 6, sizeof(float));
memcpy(&ext_factor, (int32_t *) dst->op_params + 7, sizeof(float));
memcpy(&attn_factor, (int32_t *) dst->op_params + 8, sizeof(float));
memcpy(&beta_fast, (int32_t *) dst->op_params + 9, sizeof(float));
memcpy(&beta_slow, (int32_t *) dst->op_params + 10, sizeof(float));
const bool is_neox = mode & 2;
const int32_t * pos = (const int32_t *) src1_dd;
const float * freq_factors = nullptr;
if (src2 != nullptr) {
freq_factors = (const float *) src2->data;
}
rope_corr_dims corr_dims;
ggml_rope_yarn_corr_dims(n_dims, n_ctx_orig, freq_base, beta_fast, beta_slow, corr_dims.v);
// compute
if (is_neox) {
if (src0->type == GGML_TYPE_F32) {
rope_neox_sycl(
(const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, freq_factors, main_stream
);
} else if (src0->type == GGML_TYPE_F16) {
rope_neox_sycl(
(const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, freq_factors, main_stream
);
} else {
GGML_ASSERT(false);
}
} else {
if (src0->type == GGML_TYPE_F32) {
rope_norm_sycl(
(const float *)src0_dd, (float *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, freq_factors, main_stream
);
} else if (src0->type == GGML_TYPE_F16) {
rope_norm_sycl(
(const sycl::half *)src0_dd, (sycl::half *)dst_dd, ne00, n_dims, nr, pos, freq_scale, ne01, freq_base, ext_factor,
attn_factor, corr_dims, freq_factors, main_stream
);
} else {
GGML_ASSERT(false);
}
}
(void) src1;
(void) dst;
(void) src1_dd;
}

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ggml/src/ggml-sycl/rope.hpp Normal file
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//
// MIT license
// Copyright (C) 2024 Intel Corporation
// SPDX-License-Identifier: MIT
//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
#ifndef GGML_SYCL_ROPE_HPP
#define GGML_SYCL_ROPE_HPP
#include "common.hpp"
void ggml_sycl_op_rope(
ggml_backend_sycl_context & ctx, const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst,
const float *src0_dd, const float *src1_dd, float *dst_dd, const queue_ptr &main_stream);
#endif // GGML_SYCL_ROPE_HPP