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