mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-12-20 21:23:06 +00:00
f96e1c5b78
* sync : ggml (backend v2, k-quants, CUDA opts, Metal opts, etc.) * metal : allow env metal variable to override resource path (#1415) * Allow env variable to override resource path * Update ggml-metal.m --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * sync : restore common / main from `master` * sync : restore whisper from `master` * talk-llama : update to latest llama.cpp * ruby : fix build * ggml : fix 32-bit ARM build * ggml : fix MIN / MAX macro collisions + update ios bindings * ggml : fix ifdefs and MIN / MAX again * exampels : fix Obj-C and Swift examples * ggml : fix 32-bit ARM compatibility * ggml : one more attempt to fix 32-bit ARM compat * whisper : fix support for larger graphs --------- Co-authored-by: Chris Raethke <codesoda@users.noreply.github.com>
2824 lines
101 KiB
Metal
2824 lines
101 KiB
Metal
#include <metal_stdlib>
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using namespace metal;
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#define MAX(x, y) ((x) > (y) ? (x) : (y))
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#define QK4_0 32
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#define QR4_0 2
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typedef struct {
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half d; // delta
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uint8_t qs[QK4_0 / 2]; // nibbles / quants
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} block_q4_0;
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#define QK4_1 32
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typedef struct {
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half d; // delta
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half m; // min
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uint8_t qs[QK4_1 / 2]; // nibbles / quants
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} block_q4_1;
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#define QK5_0 32
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typedef struct {
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half d; // delta
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uint8_t qh[4]; // 5-th bit of quants
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uint8_t qs[QK5_0 / 2]; // nibbles / quants
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} block_q5_0;
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#define QK5_1 32
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typedef struct {
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half d; // delta
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half m; // min
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uint8_t qh[4]; // 5-th bit of quants
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uint8_t qs[QK5_1 / 2]; // nibbles / quants
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} block_q5_1;
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#define QK8_0 32
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typedef struct {
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half d; // delta
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int8_t qs[QK8_0]; // quants
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} block_q8_0;
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// general-purpose kernel for addition of two tensors
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// pros: works for non-contiguous tensors, supports broadcast across dims 1, 2 and 3
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// cons: not very efficient
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kernel void kernel_add(
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device const char * src0,
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device const char * src1,
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device char * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int64_t & ne02,
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constant int64_t & ne03,
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constant int64_t & nb00,
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constant int64_t & nb01,
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constant int64_t & nb02,
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constant int64_t & nb03,
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constant int64_t & ne10,
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constant int64_t & ne11,
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constant int64_t & ne12,
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constant int64_t & ne13,
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constant int64_t & nb10,
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constant int64_t & nb11,
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constant int64_t & nb12,
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constant int64_t & nb13,
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constant int64_t & ne0,
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constant int64_t & ne1,
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constant int64_t & ne2,
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constant int64_t & ne3,
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constant int64_t & nb0,
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constant int64_t & nb1,
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constant int64_t & nb2,
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constant int64_t & nb3,
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uint3 tgpig[[threadgroup_position_in_grid]],
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uint3 tpitg[[thread_position_in_threadgroup]],
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uint3 ntg[[threads_per_threadgroup]]) {
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const int64_t i03 = tgpig.z;
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const int64_t i02 = tgpig.y;
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const int64_t i01 = tgpig.x;
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const int64_t i13 = i03 % ne13;
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const int64_t i12 = i02 % ne12;
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const int64_t i11 = i01 % ne11;
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device const char * src0_ptr = src0 + i03*nb03 + i02*nb02 + i01*nb01 + tpitg.x*nb00;
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device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11 + tpitg.x*nb10;
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device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1 + tpitg.x*nb0;
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for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
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((device float *)dst_ptr)[0] = ((device float *)src0_ptr)[0] + ((device float *)src1_ptr)[0];
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src0_ptr += ntg.x*nb00;
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src1_ptr += ntg.x*nb10;
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dst_ptr += ntg.x*nb0;
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}
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}
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// assumption: src1 is a row
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// broadcast src1 into src0
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kernel void kernel_add_row(
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device const float4 * src0,
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device const float4 * src1,
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device float4 * dst,
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constant int64_t & nb [[buffer(27)]],
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] + src1[tpig % nb];
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}
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kernel void kernel_mul(
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device const float4 * src0,
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device const float4 * src1,
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device float4 * dst,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] * src1[tpig];
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}
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// assumption: src1 is a row
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// broadcast src1 into src0
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kernel void kernel_mul_row(
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device const float4 * src0,
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device const float4 * src1,
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device float4 * dst,
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constant int64_t & nb,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] * src1[tpig % nb];
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}
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kernel void kernel_scale(
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device const float * src0,
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device float * dst,
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constant float & scale,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] * scale;
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}
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kernel void kernel_scale_4(
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device const float4 * src0,
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device float4 * dst,
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constant float & scale,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] * scale;
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}
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kernel void kernel_silu(
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device const float4 * src0,
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device float4 * dst,
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uint tpig[[thread_position_in_grid]]) {
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device const float4 & x = src0[tpig];
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dst[tpig] = x / (1.0f + exp(-x));
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}
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kernel void kernel_relu(
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device const float * src0,
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device float * dst,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = max(0.0f, src0[tpig]);
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}
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kernel void kernel_sqr(
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device const float * src0,
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device float * dst,
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uint tpig[[thread_position_in_grid]]) {
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dst[tpig] = src0[tpig] * src0[tpig];
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}
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constant float GELU_COEF_A = 0.044715f;
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constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
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kernel void kernel_gelu(
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device const float4 * src0,
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device float4 * dst,
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uint tpig[[thread_position_in_grid]]) {
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device const float4 & x = src0[tpig];
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// BEWARE !!!
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// Simply using "tanh" instead of "precise::tanh" will sometimes results in NaNs!
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// This was observed with Falcon 7B and 40B models
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//
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dst[tpig] = 0.5f*x*(1.0f + precise::tanh(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
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}
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kernel void kernel_soft_max(
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device const float * src0,
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device float * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int64_t & ne02,
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threadgroup float * buf [[threadgroup(0)]],
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uint tgpig[[threadgroup_position_in_grid]],
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uint tpitg[[thread_position_in_threadgroup]],
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uint sgitg[[simdgroup_index_in_threadgroup]],
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uint tiisg[[thread_index_in_simdgroup]],
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uint ntg[[threads_per_threadgroup]]) {
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const int64_t i03 = (tgpig) / (ne02*ne01);
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const int64_t i02 = (tgpig - i03*ne02*ne01) / ne01;
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const int64_t i01 = (tgpig - i03*ne02*ne01 - i02*ne01);
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device const float * psrc0 = src0 + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
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device float * pdst = dst + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
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// parallel max
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float lmax = tpitg < ne00 ? psrc0[tpitg] : -INFINITY;
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for (int i00 = tpitg + ntg; i00 < ne00; i00 += ntg) {
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lmax = MAX(lmax, psrc0[i00]);
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}
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float max = simd_max(lmax);
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if (tiisg == 0) {
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buf[sgitg] = max;
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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// broadcast, simd group number is ntg / 32
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for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
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if (tpitg < i) {
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buf[tpitg] = MAX(buf[tpitg], buf[tpitg + i]);
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}
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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max = buf[0];
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// parallel sum
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float lsum = 0.0f;
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for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
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const float exp_psrc0 = exp(psrc0[i00] - max);
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lsum += exp_psrc0;
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// Remember the result of exp here. exp is expensive, so we really do not
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// wish to compute it twice.
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pdst[i00] = exp_psrc0;
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}
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float sum = simd_sum(lsum);
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if (tiisg == 0) {
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buf[sgitg] = sum;
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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// broadcast, simd group number is ntg / 32
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for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
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if (tpitg < i) {
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buf[tpitg] += buf[tpitg + i];
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}
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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sum = buf[0];
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for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
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pdst[i00] /= sum;
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}
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}
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kernel void kernel_soft_max_4(
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device const float * src0,
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device float * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int64_t & ne02,
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threadgroup float * buf [[threadgroup(0)]],
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uint tgpig[[threadgroup_position_in_grid]],
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uint tpitg[[thread_position_in_threadgroup]],
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uint sgitg[[simdgroup_index_in_threadgroup]],
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uint tiisg[[thread_index_in_simdgroup]],
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uint ntg[[threads_per_threadgroup]]) {
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const int64_t i03 = (tgpig) / (ne02*ne01);
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const int64_t i02 = (tgpig - i03*ne02*ne01) / ne01;
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const int64_t i01 = (tgpig - i03*ne02*ne01 - i02*ne01);
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device const float4 * psrc4 = (device const float4 *)(src0 + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00);
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device float4 * pdst4 = (device float4 *)(dst + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00);
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// parallel max
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float4 lmax4 = tpitg < ne00/4 ? psrc4[tpitg] : -INFINITY;
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for (int i00 = tpitg + ntg; i00 < ne00/4; i00 += ntg) {
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lmax4 = fmax(lmax4, psrc4[i00]);
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}
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const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));
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float max = simd_max(lmax);
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if (tiisg == 0) {
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buf[sgitg] = max;
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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// broadcast, simd group number is ntg / 32
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for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
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if (tpitg < i) {
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buf[tpitg] = MAX(buf[tpitg], buf[tpitg + i]);
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}
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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max = buf[0];
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// parallel sum
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float4 lsum4 = 0.0f;
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for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
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const float4 exp_psrc4 = exp(psrc4[i00] - max);
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lsum4 += exp_psrc4;
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pdst4[i00] = exp_psrc4;
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}
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const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];
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float sum = simd_sum(lsum);
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if (tiisg == 0) {
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buf[sgitg] = sum;
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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// broadcast, simd group number is ntg / 32
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for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
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if (tpitg < i) {
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buf[tpitg] += buf[tpitg + i];
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}
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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sum = buf[0];
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for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
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pdst4[i00] /= sum;
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}
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}
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kernel void kernel_diag_mask_inf(
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device const float * src0,
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device float * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int & n_past,
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uint3 tpig[[thread_position_in_grid]]) {
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const int64_t i02 = tpig[2];
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const int64_t i01 = tpig[1];
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const int64_t i00 = tpig[0];
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if (i00 > n_past + i01) {
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dst[i02*ne01*ne00 + i01*ne00 + i00] = -INFINITY;
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} else {
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dst[i02*ne01*ne00 + i01*ne00 + i00] = src0[i02*ne01*ne00 + i01*ne00 + i00];
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}
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}
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kernel void kernel_diag_mask_inf_8(
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device const float4 * src0,
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device float4 * dst,
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constant int64_t & ne00,
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constant int64_t & ne01,
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constant int & n_past,
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uint3 tpig[[thread_position_in_grid]]) {
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const int64_t i = 2*tpig[0];
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dst[i+0] = src0[i+0];
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dst[i+1] = src0[i+1];
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int64_t i4 = 4*i;
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const int64_t i02 = i4/(ne00*ne01); i4 -= i02*ne00*ne01;
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const int64_t i01 = i4/(ne00); i4 -= i01*ne00;
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const int64_t i00 = i4;
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for (int k = 3; k >= 0; --k) {
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if (i00 + 4 + k <= n_past + i01) {
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break;
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}
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dst[i+1][k] = -INFINITY;
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if (i00 + k > n_past + i01) {
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dst[i][k] = -INFINITY;
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}
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}
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}
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kernel void kernel_norm(
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device const void * src0,
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device float * dst,
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constant int64_t & ne00,
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constant uint64_t & nb01,
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constant float & eps,
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threadgroup float * sum [[threadgroup(0)]],
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uint tgpig[[threadgroup_position_in_grid]],
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uint tpitg[[thread_position_in_threadgroup]],
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uint ntg[[threads_per_threadgroup]]) {
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device const float * x = (device const float *) ((device const char *) src0 + tgpig*nb01);
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// MEAN
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// parallel sum
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sum[tpitg] = 0.0f;
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for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
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sum[tpitg] += x[i00];
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}
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// reduce
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threadgroup_barrier(mem_flags::mem_threadgroup);
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for (uint i = ntg/2; i > 0; i /= 2) {
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if (tpitg < i) {
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sum[tpitg] += sum[tpitg + i];
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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}
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const float mean = sum[0] / ne00;
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// recenter and VARIANCE
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threadgroup_barrier(mem_flags::mem_threadgroup);
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device float * y = dst + tgpig*ne00;
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sum[tpitg] = 0.0f;
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for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
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y[i00] = x[i00] - mean;
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sum[tpitg] += y[i00] * y[i00];
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}
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// reduce
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threadgroup_barrier(mem_flags::mem_threadgroup);
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for (uint i = ntg/2; i > 0; i /= 2) {
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if (tpitg < i) {
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sum[tpitg] += sum[tpitg + i];
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}
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threadgroup_barrier(mem_flags::mem_threadgroup);
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}
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const float variance = sum[0] / ne00;
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const float scale = 1.0f/sqrt(variance + eps);
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for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
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y[i00] = y[i00] * scale;
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}
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}
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kernel void kernel_rms_norm(
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device const void * src0,
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device float * dst,
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constant int64_t & ne00,
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constant uint64_t & nb01,
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constant float & eps,
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threadgroup float * sum [[threadgroup(0)]],
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uint tgpig[[threadgroup_position_in_grid]],
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uint tpitg[[thread_position_in_threadgroup]],
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uint sgitg[[simdgroup_index_in_threadgroup]],
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uint tiisg[[thread_index_in_simdgroup]],
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uint ntg[[threads_per_threadgroup]]) {
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device const float4 * x = (device const float4 *) ((device const char *) src0 + tgpig*nb01);
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device const float * x_scalar = (device const float *) x;
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float4 sumf = 0;
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float all_sum = 0;
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// parallel sum
|
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for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
|
|
sumf += x[i00] * x[i00];
|
|
}
|
|
all_sum = sumf[0] + sumf[1] + sumf[2] + sumf[3];
|
|
all_sum = simd_sum(all_sum);
|
|
if (tiisg == 0) {
|
|
sum[sgitg] = all_sum;
|
|
}
|
|
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
|
|
// broadcast, simd group number is ntg / 32
|
|
for (uint i = ntg / 32 / 2; i > 0; i /= 2) {
|
|
if (tpitg < i) {
|
|
sum[tpitg] += sum[tpitg + i];
|
|
}
|
|
}
|
|
if (tpitg == 0) {
|
|
for (int i = 4 * (ne00 / 4); i < ne00; i++) {
|
|
sum[0] += x_scalar[i];
|
|
}
|
|
sum[0] /= ne00;
|
|
}
|
|
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
|
|
const float mean = sum[0];
|
|
const float scale = 1.0f/sqrt(mean + eps);
|
|
|
|
device float4 * y = (device float4 *) (dst + tgpig*ne00);
|
|
device float * y_scalar = (device float *) y;
|
|
for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
|
|
y[i00] = x[i00] * scale;
|
|
}
|
|
if (tpitg == 0) {
|
|
for (int i00 = 4 * (ne00 / 4); i00 < ne00; i00++) {
|
|
y_scalar[i00] = x_scalar[i00] * scale;
|
|
}
|
|
}
|
|
}
|
|
|
|
// function for calculate inner product between half a q4_0 block and 16 floats (yl), sumy is SUM(yl[i])
|
|
// il indicates where the q4 quants begin (0 or QK4_0/4)
|
|
// we assume that the yl's have been multiplied with the appropriate scale factor
|
|
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
|
|
inline float block_q_n_dot_y(device const block_q4_0 * qb_curr, float sumy, thread float * yl, int il) {
|
|
float d = qb_curr->d;
|
|
|
|
float2 acc = 0.f;
|
|
|
|
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 1 + il/2);
|
|
|
|
for (int i = 0; i < 8; i+=2) {
|
|
acc[0] += yl[i + 0] * (qs[i / 2] & 0x000F)
|
|
+ yl[i + 1] * (qs[i / 2] & 0x0F00);
|
|
acc[1] += yl[i + 8] * (qs[i / 2] & 0x00F0)
|
|
+ yl[i + 9] * (qs[i / 2] & 0xF000);
|
|
}
|
|
return d * (sumy * -8.f + acc[0] + acc[1]);
|
|
}
|
|
|
|
// function for calculate inner product between half a q4_1 block and 16 floats (yl), sumy is SUM(yl[i])
|
|
// il indicates where the q4 quants begin (0 or QK4_0/4)
|
|
// we assume that the yl's have been multiplied with the appropriate scale factor
|
|
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
|
|
inline float block_q_n_dot_y(device const block_q4_1 * qb_curr, float sumy, thread float * yl, int il) {
|
|
float d = qb_curr->d;
|
|
float m = qb_curr->m;
|
|
|
|
float2 acc = 0.f;
|
|
|
|
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 2 + il/2);
|
|
|
|
for (int i = 0; i < 8; i+=2) {
|
|
acc[0] += yl[i + 0] * (qs[i / 2] & 0x000F)
|
|
+ yl[i + 1] * (qs[i / 2] & 0x0F00);
|
|
acc[1] += yl[i + 8] * (qs[i / 2] & 0x00F0)
|
|
+ yl[i + 9] * (qs[i / 2] & 0xF000);
|
|
}
|
|
return d * (acc[0] + acc[1]) + sumy * m;
|
|
}
|
|
|
|
// function for calculate inner product between half a q5_0 block and 16 floats (yl), sumy is SUM(yl[i])
|
|
// il indicates where the q5 quants begin (0 or QK5_0/4)
|
|
// we assume that the yl's have been multiplied with the appropriate scale factor
|
|
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
|
|
inline float block_q_n_dot_y(device const block_q5_0 * qb_curr, float sumy, thread float * yl, int il) {
|
|
float d = qb_curr->d;
|
|
|
|
float2 acc = 0.f;
|
|
|
|
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 3 + il/2);
|
|
const uint32_t qh = *((device const uint32_t *)qb_curr->qh);
|
|
|
|
for (int i = 0; i < 8; i+=2) {
|
|
acc[0] += yl[i + 0] * ((qs[i / 2] & 0x000F) | ((qh >> (i+0+il ) << 4 ) & 0x00010))
|
|
+ yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000));
|
|
acc[1] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100))
|
|
+ yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000));
|
|
}
|
|
return d * (sumy * -16.f + acc[0] + acc[1]);
|
|
}
|
|
|
|
// function for calculate inner product between half a q5_1 block and 16 floats (yl), sumy is SUM(yl[i])
|
|
// il indicates where the q5 quants begin (0 or QK5_1/4)
|
|
// we assume that the yl's have been multiplied with the appropriate scale factor
|
|
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
|
|
inline float block_q_n_dot_y(device const block_q5_1 * qb_curr, float sumy, thread float * yl, int il) {
|
|
float d = qb_curr->d;
|
|
float m = qb_curr->m;
|
|
|
|
float2 acc = 0.f;
|
|
|
|
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 4 + il/2);
|
|
const uint32_t qh = *((device const uint32_t *)qb_curr->qh);
|
|
|
|
for (int i = 0; i < 8; i+=2) {
|
|
acc[0] += yl[i + 0] * ((qs[i / 2] & 0x000F) | ((qh >> (i+0+il ) << 4 ) & 0x00010))
|
|
+ yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000));
|
|
acc[1] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100))
|
|
+ yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000));
|
|
}
|
|
return d * (acc[0] + acc[1]) + sumy * m;
|
|
}
|
|
|
|
// putting them in the kernel cause a significant performance penalty
|
|
#define N_DST 4 // each SIMD group works on 4 rows
|
|
#define N_SIMDGROUP 2 // number of SIMD groups in a thread group
|
|
#define N_SIMDWIDTH 32 // assuming SIMD group size is 32
|
|
//Note: This is a template, but strictly speaking it only applies to
|
|
// quantizations where the block size is 32. It also does not
|
|
// giard against the number of rows not being divisible by
|
|
// N_DST, so this is another explicit assumption of the implementation.
|
|
template<typename block_q_type, int nr, int nsg, int nw>
|
|
void mul_vec_q_n_f32(device const void * src0, device const float * src1, device float * dst,
|
|
int64_t ne00, int64_t ne01, int64_t ne02, int64_t ne10, int64_t ne12, int64_t ne0, int64_t ne1, uint gqa,
|
|
uint3 tgpig, uint tiisg, uint sgitg) {
|
|
const int nb = ne00/QK4_0;
|
|
|
|
const int r0 = tgpig.x;
|
|
const int r1 = tgpig.y;
|
|
const int im = tgpig.z;
|
|
|
|
const int first_row = (r0 * nsg + sgitg) * nr;
|
|
|
|
const uint offset0 = first_row * nb + im/gqa*(nb*ne0);
|
|
|
|
device const block_q_type * x = (device const block_q_type *) src0 + offset0;
|
|
device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1;
|
|
|
|
float yl[16]; // src1 vector cache
|
|
float sumf[nr] = {0.f};
|
|
|
|
const int ix = (tiisg/2);
|
|
const int il = (tiisg%2)*8;
|
|
|
|
device const float * yb = y + ix * QK4_0 + il;
|
|
|
|
// each thread in a SIMD group deals with half a block.
|
|
for (int ib = ix; ib < nb; ib += nw/2) {
|
|
float sumy = 0;
|
|
for (int i = 0; i < 8; i += 2) {
|
|
sumy += yb[i] + yb[i+1];
|
|
yl[i+0] = yb[i+ 0];
|
|
yl[i+1] = yb[i+ 1]/256.f;
|
|
|
|
sumy += yb[i+16] + yb[i+17];
|
|
yl[i+8] = yb[i+16]/16.f;
|
|
yl[i+9] = yb[i+17]/4096.f;
|
|
}
|
|
|
|
for (int row = 0; row < nr; row++) {
|
|
sumf[row] += block_q_n_dot_y(x+ib+row*nb, sumy, yl, il);
|
|
}
|
|
|
|
yb += QK4_0 * 16;
|
|
}
|
|
|
|
for (int row = 0; row < nr; ++row) {
|
|
const float tot = simd_sum(sumf[row]);
|
|
if (tiisg == 0 && first_row + row < ne01) {
|
|
dst[im*ne0*ne1 + r1*ne0 + first_row + row] = tot;
|
|
}
|
|
}
|
|
}
|
|
|
|
kernel void kernel_mul_mv_q4_0_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
mul_vec_q_n_f32<block_q4_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH>(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg);
|
|
}
|
|
|
|
kernel void kernel_mul_mv_q4_1_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
mul_vec_q_n_f32<block_q4_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH>(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg);
|
|
}
|
|
|
|
kernel void kernel_mul_mv_q5_0_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
mul_vec_q_n_f32<block_q5_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH>(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg);
|
|
}
|
|
|
|
kernel void kernel_mul_mv_q5_1_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
mul_vec_q_n_f32<block_q5_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH>(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg);
|
|
}
|
|
|
|
|
|
#define NB_Q8_0 8
|
|
|
|
kernel void kernel_mul_mv_q8_0_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
const int nr = N_DST;
|
|
const int nsg = N_SIMDGROUP;
|
|
const int nw = N_SIMDWIDTH;
|
|
|
|
const int nb = ne00/QK8_0;
|
|
const int r0 = tgpig.x;
|
|
const int r1 = tgpig.y;
|
|
const int im = tgpig.z;
|
|
const int first_row = (r0 * nsg + sgitg) * nr;
|
|
const uint offset0 = first_row * nb + im/gqa*(nb*ne0);
|
|
device const block_q8_0 * x = (device const block_q8_0 *) src0 + offset0;
|
|
device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1;
|
|
|
|
float yl[NB_Q8_0];
|
|
float sumf[nr]={0.f};
|
|
|
|
const int ix = tiisg/4;
|
|
const int il = tiisg%4;
|
|
|
|
device const float * yb = y + ix * QK8_0 + NB_Q8_0*il;
|
|
|
|
// each thread in a SIMD group deals with NB_Q8_0 quants at a time
|
|
for (int ib = ix; ib < nb; ib += nw/4) {
|
|
for (int i = 0; i < NB_Q8_0; ++i) {
|
|
yl[i] = yb[i];
|
|
}
|
|
|
|
for (int row = 0; row < nr; row++) {
|
|
device const int8_t * qs = x[ib+row*nb].qs + NB_Q8_0*il;
|
|
float sumq = 0.f;
|
|
for (int iq = 0; iq < NB_Q8_0; ++iq) {
|
|
sumq += qs[iq] * yl[iq];
|
|
}
|
|
sumf[row] += sumq*x[ib+row*nb].d;
|
|
}
|
|
|
|
yb += NB_Q8_0 * nw;
|
|
}
|
|
|
|
for (int row = 0; row < nr; ++row) {
|
|
const float tot = simd_sum(sumf[row]);
|
|
if (tiisg == 0 && first_row + row < ne01) {
|
|
dst[r1*ne0 + im*ne0*ne1 + first_row + row] = tot;
|
|
}
|
|
}
|
|
}
|
|
|
|
#define N_F32_F32 4
|
|
|
|
kernel void kernel_mul_mv_f32_f32(
|
|
device const char * src0,
|
|
device const char * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant int64_t & ne10,
|
|
constant int64_t & ne11,
|
|
constant int64_t & ne12,
|
|
constant uint64_t & nb10,
|
|
constant uint64_t & nb11,
|
|
constant uint64_t & nb12,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]]) {
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t rb = tgpig.y*N_F32_F32;
|
|
const int64_t im = tgpig.z;
|
|
|
|
device const float * x = (device const float *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02);
|
|
|
|
if (ne00 < 128) {
|
|
for (int row = 0; row < N_F32_F32; ++row) {
|
|
int r1 = rb + row;
|
|
if (r1 >= ne11) {
|
|
break;
|
|
}
|
|
|
|
device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
|
|
|
|
float sumf = 0;
|
|
for (int i = tiisg; i < ne00; i += 32) {
|
|
sumf += (float) x[i] * (float) y[i];
|
|
}
|
|
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
} else {
|
|
device const float4 * x4 = (device const float4 *)x;
|
|
for (int row = 0; row < N_F32_F32; ++row) {
|
|
int r1 = rb + row;
|
|
if (r1 >= ne11) {
|
|
break;
|
|
}
|
|
|
|
device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
|
|
device const float4 * y4 = (device const float4 *) y;
|
|
|
|
float sumf = 0;
|
|
for (int i = tiisg; i < ne00/4; i += 32) {
|
|
for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
|
|
}
|
|
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
kernel void kernel_mul_mv_f16_f32_1row(
|
|
device const char * src0,
|
|
device const char * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant int64_t & ne10,
|
|
constant int64_t & ne11,
|
|
constant int64_t & ne12,
|
|
constant uint64_t & nb10,
|
|
constant uint64_t & nb11,
|
|
constant uint64_t & nb12,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]]) {
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t r1 = tgpig.y;
|
|
const int64_t im = tgpig.z;
|
|
|
|
device const half * x = (device const half *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02);
|
|
device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
|
|
|
|
float sumf = 0;
|
|
if (ne00 < 128) {
|
|
for (int i = tiisg; i < ne00; i += 32) {
|
|
sumf += (float) x[i] * (float) y[i];
|
|
}
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
} else {
|
|
device const half4 * x4 = (device const half4 *) x;
|
|
device const float4 * y4 = (device const float4 *) y;
|
|
for (int i = tiisg; i < ne00/4; i += 32) {
|
|
for (int k = 0; k < 4; ++k) sumf += (float)x4[i][k] * y4[i][k];
|
|
}
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
#define N_F16_F32 4
|
|
|
|
kernel void kernel_mul_mv_f16_f32(
|
|
device const char * src0,
|
|
device const char * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant int64_t & ne10,
|
|
constant int64_t & ne11,
|
|
constant int64_t & ne12,
|
|
constant uint64_t & nb10,
|
|
constant uint64_t & nb11,
|
|
constant uint64_t & nb12,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]]) {
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t rb = tgpig.y*N_F16_F32;
|
|
const int64_t im = tgpig.z;
|
|
|
|
device const half * x = (device const half *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02);
|
|
|
|
if (ne00 < 128) {
|
|
for (int row = 0; row < N_F16_F32; ++row) {
|
|
int r1 = rb + row;
|
|
if (r1 >= ne11) {
|
|
break;
|
|
}
|
|
|
|
device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
|
|
|
|
float sumf = 0;
|
|
for (int i = tiisg; i < ne00; i += 32) {
|
|
sumf += (float) x[i] * (float) y[i];
|
|
}
|
|
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
} else {
|
|
device const half4 * x4 = (device const half4 *)x;
|
|
for (int row = 0; row < N_F16_F32; ++row) {
|
|
int r1 = rb + row;
|
|
if (r1 >= ne11) {
|
|
break;
|
|
}
|
|
|
|
device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12);
|
|
device const float4 * y4 = (device const float4 *) y;
|
|
|
|
float sumf = 0;
|
|
for (int i = tiisg; i < ne00/4; i += 32) {
|
|
for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
|
|
}
|
|
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i];
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Assumes row size (ne00) is a multiple of 4
|
|
kernel void kernel_mul_mv_f16_f32_l4(
|
|
device const char * src0,
|
|
device const char * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant int64_t & ne10,
|
|
constant int64_t & ne11,
|
|
constant int64_t & ne12,
|
|
constant uint64_t & nb10,
|
|
constant uint64_t & nb11,
|
|
constant uint64_t & nb12,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]]) {
|
|
|
|
const int nrows = ne11;
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t im = tgpig.z;
|
|
|
|
device const half4 * x4 = (device const half4 *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02);
|
|
|
|
for (int r1 = 0; r1 < nrows; ++r1) {
|
|
device const float4 * y4 = (device const float4 *) (src1 + r1*nb11 + im*nb12);
|
|
|
|
float sumf = 0;
|
|
for (int i = tiisg; i < ne00/4; i += 32) {
|
|
for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k];
|
|
}
|
|
|
|
float all_sum = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
|
|
kernel void kernel_alibi_f32(
|
|
device const float * src0,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
constant float & m0,
|
|
constant float & m1,
|
|
constant int & n_heads_log2_floor,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint3 tpitg[[thread_position_in_threadgroup]],
|
|
uint3 ntg[[threads_per_threadgroup]]) {
|
|
const int64_t i03 = tgpig[2];
|
|
const int64_t i02 = tgpig[1];
|
|
const int64_t i01 = tgpig[0];
|
|
|
|
const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
|
|
|
|
const int64_t i3 = n / (ne2*ne1*ne0);
|
|
const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
|
|
const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
|
|
const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
|
|
|
|
device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
float m_k;
|
|
if (i2 < n_heads_log2_floor) {
|
|
m_k = pow(m0, i2 + 1);
|
|
} else {
|
|
m_k = pow(m1, 2 * (i2 - n_heads_log2_floor) + 1);
|
|
}
|
|
for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
|
|
device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
|
|
dst_data[i00] = src[0] + m_k * (i00 - ne00 + 1);
|
|
}
|
|
}
|
|
|
|
static float rope_yarn_ramp(const float low, const float high, const int i0) {
|
|
const float y = (i0 / 2 - low) / max(0.001f, high - low);
|
|
return 1.0f - min(1.0f, 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, float corr_dims[2], int64_t i0, float ext_factor, float mscale,
|
|
thread float * cos_theta, thread 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[0], corr_dims[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 * log(1.0f / freq_scale);
|
|
}
|
|
*cos_theta = cos(theta) * mscale;
|
|
*sin_theta = sin(theta) * mscale;
|
|
}
|
|
|
|
// Apparently solving `n_rot = 2pi * x * base^((2 * max_pos_emb) / n_dims)` for x, we get
|
|
// `corr_fac(n_rot) = n_dims * log(max_pos_emb / (n_rot * 2pi)) / (2 * log(base))`
|
|
static float rope_yarn_corr_factor(int n_dims, int n_orig_ctx, float n_rot, float base) {
|
|
return n_dims * log(n_orig_ctx / (n_rot * 2 * M_PI_F)) / (2 * log(base));
|
|
}
|
|
|
|
static void rope_yarn_corr_dims(
|
|
int n_dims, int n_orig_ctx, float freq_base, float beta_fast, float beta_slow, float dims[2]
|
|
) {
|
|
// start and end correction dims
|
|
dims[0] = max(0.0f, floor(rope_yarn_corr_factor(n_dims, n_orig_ctx, beta_fast, freq_base)));
|
|
dims[1] = min(n_dims - 1.0f, ceil(rope_yarn_corr_factor(n_dims, n_orig_ctx, beta_slow, freq_base)));
|
|
}
|
|
|
|
typedef void (rope_t)(
|
|
device const void * src0,
|
|
device const int32_t * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
constant int & n_past,
|
|
constant int & n_dims,
|
|
constant int & mode,
|
|
constant int & n_orig_ctx,
|
|
constant float & freq_base,
|
|
constant float & freq_scale,
|
|
constant float & ext_factor,
|
|
constant float & attn_factor,
|
|
constant float & beta_fast,
|
|
constant float & beta_slow,
|
|
uint tiitg[[thread_index_in_threadgroup]],
|
|
uint3 tptg[[threads_per_threadgroup]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]]);
|
|
|
|
template<typename T>
|
|
kernel void kernel_rope(
|
|
device const void * src0,
|
|
device const int32_t * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
constant int & n_past,
|
|
constant int & n_dims,
|
|
constant int & mode,
|
|
constant int & n_orig_ctx,
|
|
constant float & freq_base,
|
|
constant float & freq_scale,
|
|
constant float & ext_factor,
|
|
constant float & attn_factor,
|
|
constant float & beta_fast,
|
|
constant float & beta_slow,
|
|
uint tiitg[[thread_index_in_threadgroup]],
|
|
uint3 tptg[[threads_per_threadgroup]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]]) {
|
|
const int64_t i3 = tgpig[2];
|
|
const int64_t i2 = tgpig[1];
|
|
const int64_t i1 = tgpig[0];
|
|
|
|
const bool is_neox = mode & 2;
|
|
|
|
float corr_dims[2];
|
|
rope_yarn_corr_dims(n_dims, n_orig_ctx, freq_base, beta_fast, beta_slow, corr_dims);
|
|
|
|
device const int32_t * pos = src1;
|
|
|
|
const int64_t p = pos[i2];
|
|
|
|
const float theta_0 = (float)p;
|
|
const float inv_ndims = -1.f/n_dims;
|
|
|
|
if (!is_neox) {
|
|
for (int64_t i0 = 2*tiitg; i0 < ne0; i0 += 2*tptg.x) {
|
|
|
|
const float theta = theta_0 * pow(freq_base, inv_ndims*i0);
|
|
float cos_theta, sin_theta;
|
|
rope_yarn(theta, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta);
|
|
|
|
device const T * const src = (device T *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
|
|
device T * dst_data = (device T *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
|
|
const T x0 = src[0];
|
|
const T x1 = src[1];
|
|
|
|
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
|
dst_data[1] = x0*sin_theta + x1*cos_theta;
|
|
}
|
|
} else {
|
|
for (int64_t ib = 0; ib < ne0/n_dims; ++ib) {
|
|
for (int64_t ic = 2*tiitg; ic < n_dims; ic += 2*tptg.x) {
|
|
|
|
// simplified from `(ib * n_dims + ic) * inv_ndims`
|
|
const float cur_rot = inv_ndims*ic - ib;
|
|
|
|
const float theta = theta_0 * pow(freq_base, cur_rot);
|
|
float cos_theta, sin_theta;
|
|
rope_yarn(theta, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta);
|
|
|
|
const int64_t i0 = ib*n_dims + ic/2;
|
|
|
|
device const T * const src = (device T *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
|
|
device T * dst_data = (device T *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
|
|
const float x0 = src[0];
|
|
const float x1 = src[n_dims/2];
|
|
|
|
dst_data[0] = x0*cos_theta - x1*sin_theta;
|
|
dst_data[n_dims/2] = x0*sin_theta + x1*cos_theta;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template [[host_name("kernel_rope_f32")]] kernel rope_t kernel_rope<float>;
|
|
template [[host_name("kernel_rope_f16")]] kernel rope_t kernel_rope<half>;
|
|
|
|
kernel void kernel_cpy_f16_f16(
|
|
device const half * src0,
|
|
device half * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint3 tpitg[[thread_position_in_threadgroup]],
|
|
uint3 ntg[[threads_per_threadgroup]]) {
|
|
const int64_t i03 = tgpig[2];
|
|
const int64_t i02 = tgpig[1];
|
|
const int64_t i01 = tgpig[0];
|
|
|
|
const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
|
|
|
|
const int64_t i3 = n / (ne2*ne1*ne0);
|
|
const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
|
|
const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
|
|
const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
|
|
|
|
device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
|
|
for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
|
|
device const half * src = (device half *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
|
|
dst_data[i00] = src[0];
|
|
}
|
|
}
|
|
|
|
kernel void kernel_cpy_f32_f16(
|
|
device const float * src0,
|
|
device half * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint3 tpitg[[thread_position_in_threadgroup]],
|
|
uint3 ntg[[threads_per_threadgroup]]) {
|
|
const int64_t i03 = tgpig[2];
|
|
const int64_t i02 = tgpig[1];
|
|
const int64_t i01 = tgpig[0];
|
|
|
|
const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
|
|
|
|
const int64_t i3 = n / (ne2*ne1*ne0);
|
|
const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
|
|
const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
|
|
const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
|
|
|
|
device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
|
|
for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
|
|
device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
|
|
|
|
dst_data[i00] = src[0];
|
|
}
|
|
}
|
|
|
|
kernel void kernel_cpy_f32_f32(
|
|
device const float * src0,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint3 tpitg[[thread_position_in_threadgroup]],
|
|
uint3 ntg[[threads_per_threadgroup]]) {
|
|
const int64_t i03 = tgpig[2];
|
|
const int64_t i02 = tgpig[1];
|
|
const int64_t i01 = tgpig[0];
|
|
|
|
const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00;
|
|
|
|
const int64_t i3 = n / (ne2*ne1*ne0);
|
|
const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0);
|
|
const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0;
|
|
const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0);
|
|
|
|
device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
|
|
|
|
for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) {
|
|
device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
|
|
|
|
dst_data[i00] = src[0];
|
|
}
|
|
}
|
|
|
|
kernel void kernel_concat(
|
|
device const char * src0,
|
|
device const char * src1,
|
|
device char * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01,
|
|
constant int64_t & ne02,
|
|
constant int64_t & ne03,
|
|
constant uint64_t & nb00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb02,
|
|
constant uint64_t & nb03,
|
|
constant int64_t & ne10,
|
|
constant int64_t & ne11,
|
|
constant int64_t & ne12,
|
|
constant int64_t & ne13,
|
|
constant uint64_t & nb10,
|
|
constant uint64_t & nb11,
|
|
constant uint64_t & nb12,
|
|
constant uint64_t & nb13,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant int64_t & ne2,
|
|
constant int64_t & ne3,
|
|
constant uint64_t & nb0,
|
|
constant uint64_t & nb1,
|
|
constant uint64_t & nb2,
|
|
constant uint64_t & nb3,
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint3 tpitg[[thread_position_in_threadgroup]],
|
|
uint3 ntg[[threads_per_threadgroup]]) {
|
|
|
|
const int64_t i03 = tgpig.z;
|
|
const int64_t i02 = tgpig.y;
|
|
const int64_t i01 = tgpig.x;
|
|
|
|
const int64_t i13 = i03 % ne13;
|
|
const int64_t i12 = i02 % ne12;
|
|
const int64_t i11 = i01 % ne11;
|
|
|
|
device const char * src0_ptr = src0 + i03 * nb03 + i02 * nb02 + i01 * nb01 + tpitg.x*nb00;
|
|
device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11 + tpitg.x*nb10;
|
|
device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1 + tpitg.x*nb0;
|
|
|
|
for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
|
|
if (i02 < ne02) {
|
|
((device float *)dst_ptr)[0] = ((device float *)src0_ptr)[0];
|
|
src0_ptr += ntg.x*nb00;
|
|
} else {
|
|
((device float *)dst_ptr)[0] = ((device float *)src1_ptr)[0];
|
|
src1_ptr += ntg.x*nb10;
|
|
}
|
|
dst_ptr += ntg.x*nb0;
|
|
}
|
|
}
|
|
|
|
//============================================ k-quants ======================================================
|
|
|
|
#ifndef QK_K
|
|
#define QK_K 256
|
|
#else
|
|
static_assert(QK_K == 256 || QK_K == 64, "QK_K must be 256 or 64");
|
|
#endif
|
|
|
|
#if QK_K == 256
|
|
#define K_SCALE_SIZE 12
|
|
#else
|
|
#define K_SCALE_SIZE 4
|
|
#endif
|
|
|
|
typedef struct {
|
|
uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
|
|
uint8_t qs[QK_K/4]; // quants
|
|
half d; // super-block scale for quantized scales
|
|
half dmin; // super-block scale for quantized mins
|
|
} block_q2_K;
|
|
// 84 bytes / block
|
|
|
|
typedef struct {
|
|
uint8_t hmask[QK_K/8]; // quants - high bit
|
|
uint8_t qs[QK_K/4]; // quants - low 2 bits
|
|
#if QK_K == 64
|
|
uint8_t scales[2];
|
|
#else
|
|
uint8_t scales[K_SCALE_SIZE]; // scales, quantized with 6 bits
|
|
#endif
|
|
half d; // super-block scale
|
|
} block_q3_K;
|
|
|
|
#if QK_K == 64
|
|
typedef struct {
|
|
half d[2]; // super-block scales/mins
|
|
uint8_t scales[2];
|
|
uint8_t qs[QK_K/2]; // 4-bit quants
|
|
} block_q4_K;
|
|
#else
|
|
typedef struct {
|
|
half d; // super-block scale for quantized scales
|
|
half dmin; // super-block scale for quantized mins
|
|
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
|
|
uint8_t qs[QK_K/2]; // 4--bit quants
|
|
} block_q4_K;
|
|
#endif
|
|
|
|
#if QK_K == 64
|
|
typedef struct {
|
|
half d; // super-block scales/mins
|
|
int8_t scales[QK_K/16]; // 8-bit block scales
|
|
uint8_t qh[QK_K/8]; // quants, high bit
|
|
uint8_t qs[QK_K/2]; // quants, low 4 bits
|
|
} block_q5_K;
|
|
#else
|
|
typedef struct {
|
|
half d; // super-block scale for quantized scales
|
|
half dmin; // super-block scale for quantized mins
|
|
uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits
|
|
uint8_t qh[QK_K/8]; // quants, high bit
|
|
uint8_t qs[QK_K/2]; // quants, low 4 bits
|
|
} block_q5_K;
|
|
// 176 bytes / block
|
|
#endif
|
|
|
|
typedef struct {
|
|
uint8_t ql[QK_K/2]; // quants, lower 4 bits
|
|
uint8_t qh[QK_K/4]; // quants, upper 2 bits
|
|
int8_t scales[QK_K/16]; // scales, quantized with 8 bits
|
|
half d; // super-block scale
|
|
} block_q6_K;
|
|
// 210 bytes / block
|
|
|
|
static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) {
|
|
uchar4 r;
|
|
if (j < 4) {
|
|
r[0] = q[j+0] & 63;
|
|
r[2] = q[j+1] & 63;
|
|
r[1] = q[j+4] & 63;
|
|
r[3] = q[j+5] & 63;
|
|
} else {
|
|
r[0] = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4);
|
|
r[2] = (q[j+5] & 0xF) | ((q[j-3] >> 6) << 4);
|
|
r[1] = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4);
|
|
r[3] = (q[j+5] >> 4) | ((q[j+1] >> 6) << 4);
|
|
}
|
|
return r;
|
|
}
|
|
|
|
//====================================== dot products =========================
|
|
|
|
kernel void kernel_mul_mv_q2_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const int nb = ne00/QK_K;
|
|
const int r0 = tgpig.x;
|
|
const int r1 = tgpig.y;
|
|
const int r2 = tgpig.z;
|
|
|
|
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
|
|
const int ib_row = first_row * nb;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q2_K * x = (device const block_q2_K *) src0 + ib_row + offset0;
|
|
device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
float yl[32];
|
|
float sumf[N_DST]={0.f}, all_sum;
|
|
|
|
const int step = sizeof(block_q2_K) * nb;
|
|
|
|
#if QK_K == 256
|
|
const int ix = tiisg/8; // 0...3
|
|
const int it = tiisg%8; // 0...7
|
|
const int im = it/4; // 0 or 1
|
|
const int ir = it%4; // 0...3
|
|
const int is = (8*ir)/16;// 0 or 1
|
|
|
|
device const float * y4 = y + ix * QK_K + 128 * im + 8 * ir;
|
|
|
|
for (int ib = ix; ib < nb; ib += 4) {
|
|
|
|
float4 sumy = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; ++i) {
|
|
yl[i+ 0] = y4[i+ 0]; sumy[0] += yl[i+ 0];
|
|
yl[i+ 8] = y4[i+32]; sumy[1] += yl[i+ 8];
|
|
yl[i+16] = y4[i+64]; sumy[2] += yl[i+16];
|
|
yl[i+24] = y4[i+96]; sumy[3] += yl[i+24];
|
|
}
|
|
|
|
device const uint8_t * sc = (device const uint8_t *)x[ib].scales + 8*im + is;
|
|
device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 16 * im + 4 * ir;
|
|
device const half * dh = &x[ib].d;
|
|
|
|
for (int row = 0; row < N_DST; row++) {
|
|
|
|
float4 acc1 = {0.f, 0.f, 0.f, 0.f};
|
|
float4 acc2 = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; i += 2) {
|
|
acc1[0] += yl[i+ 0] * (qs[i/2] & 0x0003);
|
|
acc2[0] += yl[i+ 1] * (qs[i/2] & 0x0300);
|
|
acc1[1] += yl[i+ 8] * (qs[i/2] & 0x000c);
|
|
acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
|
|
acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
|
|
acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
|
|
acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
|
|
acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
|
|
}
|
|
float dall = dh[0];
|
|
float dmin = dh[1] * 1.f/16.f;
|
|
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
|
|
(acc1[1] + 1.f/256.f * acc2[1]) * (sc[2] & 0xF) * 1.f/ 4.f +
|
|
(acc1[2] + 1.f/256.f * acc2[2]) * (sc[4] & 0xF) * 1.f/16.f +
|
|
(acc1[3] + 1.f/256.f * acc2[3]) * (sc[6] & 0xF) * 1.f/64.f) -
|
|
dmin * (sumy[0] * (sc[0] & 0xF0) + sumy[1] * (sc[2] & 0xF0) + sumy[2] * (sc[4] & 0xF0) + sumy[3] * (sc[6] & 0xF0));
|
|
|
|
qs += step/2;
|
|
sc += step;
|
|
dh += step/2;
|
|
}
|
|
|
|
y4 += 4 * QK_K;
|
|
}
|
|
#else
|
|
const int ix = tiisg/2; // 0...15
|
|
const int it = tiisg%2; // 0...1
|
|
|
|
device const float * y4 = y + ix * QK_K + 8 * it;
|
|
|
|
for (int ib = ix; ib < nb; ib += 16) {
|
|
|
|
float4 sumy = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; ++i) {
|
|
yl[i+ 0] = y4[i+ 0]; sumy[0] += yl[i+ 0];
|
|
yl[i+ 8] = y4[i+16]; sumy[1] += yl[i+ 8];
|
|
yl[i+16] = y4[i+32]; sumy[2] += yl[i+16];
|
|
yl[i+24] = y4[i+48]; sumy[3] += yl[i+24];
|
|
}
|
|
|
|
device const uint8_t * sc = (device const uint8_t *)x[ib].scales;
|
|
device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it;
|
|
device const half * dh = &x[ib].d;
|
|
|
|
for (int row = 0; row < N_DST; row++) {
|
|
|
|
float4 acc1 = {0.f, 0.f, 0.f, 0.f};
|
|
float4 acc2 = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; i += 2) {
|
|
acc1[0] += yl[i+ 0] * (qs[i/2] & 0x0003);
|
|
acc2[0] += yl[i+ 1] * (qs[i/2] & 0x0300);
|
|
acc1[1] += yl[i+ 8] * (qs[i/2] & 0x000c);
|
|
acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
|
|
acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
|
|
acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
|
|
acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
|
|
acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
|
|
}
|
|
|
|
float dall = dh[0];
|
|
float dmin = dh[1];
|
|
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
|
|
(acc1[1] + 1.f/256.f * acc2[1]) * (sc[1] & 0xF) * 1.f/ 4.f +
|
|
(acc1[2] + 1.f/256.f * acc2[2]) * (sc[2] & 0xF) * 1.f/16.f +
|
|
(acc1[3] + 1.f/256.f * acc2[3]) * (sc[3] & 0xF) * 1.f/64.f) -
|
|
dmin * (sumy[0] * (sc[0] >> 4) + sumy[1] * (sc[1] >> 4) + sumy[2] * (sc[2] >> 4) + sumy[3] * (sc[3] >> 4));
|
|
|
|
qs += step/2;
|
|
sc += step;
|
|
dh += step/2;
|
|
}
|
|
|
|
y4 += 16 * QK_K;
|
|
}
|
|
#endif
|
|
|
|
for (int row = 0; row < N_DST; ++row) {
|
|
all_sum = simd_sum(sumf[row]);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
|
|
#if QK_K == 256
|
|
kernel void kernel_mul_mv_q3_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const int nb = ne00/QK_K;
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t r1 = tgpig.y;
|
|
const int64_t r2 = tgpig.z;
|
|
|
|
const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q3_K * x = (device const block_q3_K *) src0 + first_row*nb + offset0;
|
|
device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
|
|
float yl[32];
|
|
|
|
//const uint16_t kmask1 = 0x3030;
|
|
//const uint16_t kmask2 = 0x0f0f;
|
|
|
|
const int tid = tiisg/4;
|
|
const int ix = tiisg%4;
|
|
const int ip = tid/4; // 0 or 1
|
|
const int il = 2*((tid%4)/2); // 0 or 2
|
|
const int ir = tid%2;
|
|
const int n = 8;
|
|
const int l0 = n*ir;
|
|
|
|
// One would think that the Metal compiler would figure out that ip and il can only have
|
|
// 4 possible states, and optimize accordingly. Well, no. It needs help, and we do it
|
|
// with these two tales.
|
|
//
|
|
// Possible masks for the high bit
|
|
const ushort4 mm[4] = {{0x0001, 0x0100, 0x0002, 0x0200}, // ip = 0, il = 0
|
|
{0x0004, 0x0400, 0x0008, 0x0800}, // ip = 0, il = 2
|
|
{0x0010, 0x1000, 0x0020, 0x2000}, // ip = 1, il = 0
|
|
{0x0040, 0x4000, 0x0080, 0x8000}}; // ip = 1, il = 2
|
|
|
|
// Possible masks for the low 2 bits
|
|
const int4 qm[2] = {{0x0003, 0x0300, 0x000c, 0x0c00}, {0x0030, 0x3000, 0x00c0, 0xc000}};
|
|
|
|
const ushort4 hm = mm[2*ip + il/2];
|
|
|
|
const int shift = 2*il;
|
|
const float v1 = il == 0 ? 4.f : 64.f;
|
|
const float v2 = 4.f * v1;
|
|
|
|
const uint16_t s_shift1 = 4*ip;
|
|
const uint16_t s_shift2 = s_shift1 + il;
|
|
|
|
const int q_offset = 32*ip + l0;
|
|
const int y_offset = 128*ip + 32*il + l0;
|
|
|
|
const int step = sizeof(block_q3_K) * nb / 2;
|
|
|
|
device const float * y1 = yy + ix*QK_K + y_offset;
|
|
|
|
uint32_t scales32, aux32;
|
|
thread uint16_t * scales16 = (thread uint16_t *)&scales32;
|
|
thread const int8_t * scales = (thread const int8_t *)&scales32;
|
|
|
|
float sumf1[2] = {0.f};
|
|
float sumf2[2] = {0.f};
|
|
for (int i = ix; i < nb; i += 4) {
|
|
|
|
for (int l = 0; l < 8; ++l) {
|
|
yl[l+ 0] = y1[l+ 0];
|
|
yl[l+ 8] = y1[l+16];
|
|
yl[l+16] = y1[l+32];
|
|
yl[l+24] = y1[l+48];
|
|
}
|
|
|
|
device const uint16_t * q = (device const uint16_t *)(x[i].qs + q_offset);
|
|
device const uint16_t * h = (device const uint16_t *)(x[i].hmask + l0);
|
|
device const uint16_t * a = (device const uint16_t *)(x[i].scales);
|
|
device const half * dh = &x[i].d;
|
|
|
|
for (int row = 0; row < 2; ++row) {
|
|
|
|
const float d_all = (float)dh[0];
|
|
|
|
scales16[0] = a[4];
|
|
scales16[1] = a[5];
|
|
aux32 = ((scales32 >> s_shift2) << 4) & 0x30303030;
|
|
scales16[0] = a[il+0];
|
|
scales16[1] = a[il+1];
|
|
scales32 = ((scales32 >> s_shift1) & 0x0f0f0f0f) | aux32;
|
|
|
|
float s1 = 0, s2 = 0, s3 = 0, s4 = 0, s5 = 0, s6 = 0;
|
|
for (int l = 0; l < n; l += 2) {
|
|
const int32_t qs = q[l/2];
|
|
s1 += yl[l+0] * (qs & qm[il/2][0]);
|
|
s2 += yl[l+1] * (qs & qm[il/2][1]);
|
|
s3 += ((h[l/2] & hm[0]) ? 0.f : yl[l+0]) + ((h[l/2] & hm[1]) ? 0.f : yl[l+1]);
|
|
s4 += yl[l+16] * (qs & qm[il/2][2]);
|
|
s5 += yl[l+17] * (qs & qm[il/2][3]);
|
|
s6 += ((h[l/2] & hm[2]) ? 0.f : yl[l+16]) + ((h[l/2] & hm[3]) ? 0.f : yl[l+17]);
|
|
}
|
|
float d1 = d_all * (s1 + 1.f/256.f * s2 - s3*v1);
|
|
float d2 = d_all * (s4 + 1.f/256.f * s5 - s6*v2);
|
|
sumf1[row] += d1 * (scales[0] - 32);
|
|
sumf2[row] += d2 * (scales[2] - 32);
|
|
|
|
s1 = s2 = s3 = s4 = s5 = s6 = 0;
|
|
for (int l = 0; l < n; l += 2) {
|
|
const int32_t qs = q[l/2+8];
|
|
s1 += yl[l+8] * (qs & qm[il/2][0]);
|
|
s2 += yl[l+9] * (qs & qm[il/2][1]);
|
|
s3 += ((h[l/2+8] & hm[0]) ? 0.f : yl[l+8]) + ((h[l/2+8] & hm[1]) ? 0.f : yl[l+9]);
|
|
s4 += yl[l+24] * (qs & qm[il/2][2]);
|
|
s5 += yl[l+25] * (qs & qm[il/2][3]);
|
|
s6 += ((h[l/2+8] & hm[2]) ? 0.f : yl[l+24]) + ((h[l/2+8] & hm[3]) ? 0.f : yl[l+25]);
|
|
}
|
|
d1 = d_all * (s1 + 1.f/256.f * s2 - s3*v1);
|
|
d2 = d_all * (s4 + 1.f/256.f * s5 - s6*v2);
|
|
sumf1[row] += d1 * (scales[1] - 32);
|
|
sumf2[row] += d2 * (scales[3] - 32);
|
|
|
|
q += step;
|
|
h += step;
|
|
a += step;
|
|
dh += step;
|
|
|
|
}
|
|
|
|
y1 += 4 * QK_K;
|
|
|
|
}
|
|
|
|
for (int row = 0; row < 2; ++row) {
|
|
const float sumf = (sumf1[row] + 0.25f * sumf2[row]) / (1 << shift);
|
|
sumf1[row] = simd_sum(sumf);
|
|
}
|
|
if (tiisg == 0) {
|
|
for (int row = 0; row < 2; ++row) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = sumf1[row];
|
|
}
|
|
}
|
|
}
|
|
#else
|
|
kernel void kernel_mul_mv_q3_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const int nb = ne00/QK_K;
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t r1 = tgpig.y;
|
|
const int64_t r2 = tgpig.z;
|
|
|
|
const int row = 2 * r0 + sgitg;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q3_K * x = (device const block_q3_K *) src0 + row*nb + offset0;
|
|
device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
const int ix = tiisg/4;
|
|
const int il = 4 * (tiisg%4);// 0, 4, 8, 12
|
|
const int im = il/8; // 0, 0, 1, 1
|
|
const int in = il%8; // 0, 4, 0, 4
|
|
|
|
float2 sum = {0.f, 0.f};
|
|
|
|
for (int i = ix; i < nb; i += 8) {
|
|
|
|
const float d_all = (float)(x[i].d);
|
|
|
|
device const uint16_t * q = (device const uint16_t *)(x[i].qs + il);
|
|
device const uint16_t * h = (device const uint16_t *)(x[i].hmask + in);
|
|
device const uint16_t * s = (device const uint16_t *)(x[i].scales);
|
|
device const float * y = yy + i * QK_K + il;
|
|
|
|
const float d1 = d_all * ((int32_t)(s[0] & 0x000F) - 8);
|
|
const float d2 = d_all * ((int32_t)(s[0] & 0x00F0) - 128) * 1.f/64.f;
|
|
const float d3 = d_all * ((int32_t)(s[0] & 0x0F00) - 2048) * 1.f/4096.f;
|
|
const float d4 = d_all * ((int32_t)(s[0] & 0xF000) - 32768) * 1.f/262144.f;
|
|
|
|
for (int l = 0; l < 4; l += 2) {
|
|
const uint16_t hm = h[l/2] >> im;
|
|
sum[0] += y[l+ 0] * d1 * ((int32_t)(q[l/2] & 0x0003) - ((hm & 0x0001) ? 0 : 4))
|
|
+ y[l+16] * d2 * ((int32_t)(q[l/2] & 0x000c) - ((hm & 0x0004) ? 0 : 16))
|
|
+ y[l+32] * d3 * ((int32_t)(q[l/2] & 0x0030) - ((hm & 0x0010) ? 0 : 64))
|
|
+ y[l+48] * d4 * ((int32_t)(q[l/2] & 0x00c0) - ((hm & 0x0040) ? 0 : 256));
|
|
sum[1] += y[l+ 1] * d1 * ((int32_t)(q[l/2] & 0x0300) - ((hm & 0x0100) ? 0 : 1024))
|
|
+ y[l+17] * d2 * ((int32_t)(q[l/2] & 0x0c00) - ((hm & 0x0400) ? 0 : 4096))
|
|
+ y[l+33] * d3 * ((int32_t)(q[l/2] & 0x3000) - ((hm & 0x1000) ? 0 : 16384))
|
|
+ y[l+49] * d4 * ((int32_t)(q[l/2] & 0xc000) - ((hm & 0x4000) ? 0 : 65536));
|
|
}
|
|
|
|
}
|
|
const float sumf = sum[0] + sum[1] * 1.f/256.f;
|
|
|
|
const float tot = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + row] = tot;
|
|
}
|
|
|
|
}
|
|
#endif
|
|
|
|
#if QK_K == 256
|
|
kernel void kernel_mul_mv_q4_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01 [[buffer(4)]],
|
|
constant int64_t & ne02 [[buffer(5)]],
|
|
constant int64_t & ne10 [[buffer(9)]],
|
|
constant int64_t & ne12 [[buffer(11)]],
|
|
constant int64_t & ne0 [[buffer(15)]],
|
|
constant int64_t & ne1 [[buffer(16)]],
|
|
constant uint & gqa [[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const uint16_t kmask1 = 0x3f3f;
|
|
const uint16_t kmask2 = 0x0f0f;
|
|
const uint16_t kmask3 = 0xc0c0;
|
|
|
|
const int ix = tiisg/8; // 0...3
|
|
const int it = tiisg%8; // 0...7
|
|
const int im = it/4; // 0 or 1
|
|
const int ir = it%4; // 0...3
|
|
|
|
const int nb = ne00/QK_K;
|
|
const int r0 = tgpig.x;
|
|
const int r1 = tgpig.y;
|
|
const int r2 = tgpig.z;
|
|
//const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
|
|
const int first_row = r0 * N_DST;
|
|
const int ib_row = first_row * nb;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q4_K * x = (device const block_q4_K *) src0 + ib_row + offset0;
|
|
device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
float yl[16];
|
|
float yh[16];
|
|
float sumf[N_DST]={0.f}, all_sum;
|
|
|
|
const int step = sizeof(block_q4_K) * nb / 2;
|
|
|
|
device const float * y4 = y + ix * QK_K + 64 * im + 8 * ir;
|
|
|
|
uint16_t sc16[4];
|
|
thread const uint8_t * sc8 = (thread const uint8_t *)sc16;
|
|
|
|
for (int ib = ix; ib < nb; ib += 4) {
|
|
|
|
float4 sumy = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; ++i) {
|
|
yl[i+0] = y4[i+ 0]; sumy[0] += yl[i+0];
|
|
yl[i+8] = y4[i+ 32]; sumy[1] += yl[i+8];
|
|
yh[i+0] = y4[i+128]; sumy[2] += yh[i+0];
|
|
yh[i+8] = y4[i+160]; sumy[3] += yh[i+8];
|
|
}
|
|
|
|
device const uint16_t * sc = (device const uint16_t *)x[ib].scales + im;
|
|
device const uint16_t * q1 = (device const uint16_t *)x[ib].qs + 16 * im + 4 * ir;
|
|
device const half * dh = &x[ib].d;
|
|
|
|
for (int row = 0; row < N_DST; row++) {
|
|
|
|
sc16[0] = sc[0] & kmask1;
|
|
sc16[1] = sc[2] & kmask1;
|
|
sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
|
|
sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);
|
|
|
|
device const uint16_t * q2 = q1 + 32;
|
|
|
|
float4 acc1 = {0.f, 0.f, 0.f, 0.f};
|
|
float4 acc2 = {0.f, 0.f, 0.f, 0.f};
|
|
for (int i = 0; i < 8; i += 2) {
|
|
acc1[0] += yl[i+0] * (q1[i/2] & 0x000F);
|
|
acc1[1] += yl[i+1] * (q1[i/2] & 0x0F00);
|
|
acc1[2] += yl[i+8] * (q1[i/2] & 0x00F0);
|
|
acc1[3] += yl[i+9] * (q1[i/2] & 0xF000);
|
|
acc2[0] += yh[i+0] * (q2[i/2] & 0x000F);
|
|
acc2[1] += yh[i+1] * (q2[i/2] & 0x0F00);
|
|
acc2[2] += yh[i+8] * (q2[i/2] & 0x00F0);
|
|
acc2[3] += yh[i+9] * (q2[i/2] & 0xF000);
|
|
}
|
|
|
|
float dall = dh[0];
|
|
float dmin = dh[1];
|
|
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc8[0] +
|
|
(acc1[2] + 1.f/256.f * acc1[3]) * sc8[1] * 1.f/16.f +
|
|
(acc2[0] + 1.f/256.f * acc2[1]) * sc8[4] +
|
|
(acc2[2] + 1.f/256.f * acc2[3]) * sc8[5] * 1.f/16.f) -
|
|
dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]);
|
|
|
|
q1 += step;
|
|
sc += step;
|
|
dh += step;
|
|
}
|
|
|
|
y4 += 4 * QK_K;
|
|
}
|
|
|
|
for (int row = 0; row < N_DST; ++row) {
|
|
all_sum = simd_sum(sumf[row]);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
#else
|
|
kernel void kernel_mul_mv_q4_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const int ix = tiisg/4; // 0...7
|
|
const int it = tiisg%4; // 0...3
|
|
|
|
const int nb = ne00/QK_K;
|
|
const int r0 = tgpig.x;
|
|
const int r1 = tgpig.y;
|
|
const int r2 = tgpig.z;
|
|
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
|
|
const int ib_row = first_row * nb;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q4_K * x = (device const block_q4_K *) src0 + ib_row + offset0;
|
|
device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
float yl[8];
|
|
float yh[8];
|
|
float sumf[N_DST]={0.f}, all_sum;
|
|
|
|
const int step = sizeof(block_q4_K) * nb / 2;
|
|
|
|
device const float * y4 = y + ix * QK_K + 8 * it;
|
|
|
|
uint16_t sc16[4];
|
|
|
|
for (int ib = ix; ib < nb; ib += 8) {
|
|
|
|
float2 sumy = {0.f, 0.f};
|
|
for (int i = 0; i < 8; ++i) {
|
|
yl[i] = y4[i+ 0]; sumy[0] += yl[i];
|
|
yh[i] = y4[i+32]; sumy[1] += yh[i];
|
|
}
|
|
|
|
device const uint16_t * sc = (device const uint16_t *)x[ib].scales;
|
|
device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it;
|
|
device const half * dh = x[ib].d;
|
|
|
|
for (int row = 0; row < N_DST; row++) {
|
|
|
|
sc16[0] = sc[0] & 0x000f;
|
|
sc16[1] = sc[0] & 0x0f00;
|
|
sc16[2] = sc[0] & 0x00f0;
|
|
sc16[3] = sc[0] & 0xf000;
|
|
|
|
float2 acc1 = {0.f, 0.f};
|
|
float2 acc2 = {0.f, 0.f};
|
|
for (int i = 0; i < 8; i += 2) {
|
|
acc1[0] += yl[i+0] * (qs[i/2] & 0x000F);
|
|
acc1[1] += yl[i+1] * (qs[i/2] & 0x0F00);
|
|
acc2[0] += yh[i+0] * (qs[i/2] & 0x00F0);
|
|
acc2[1] += yh[i+1] * (qs[i/2] & 0xF000);
|
|
}
|
|
|
|
float dall = dh[0];
|
|
float dmin = dh[1];
|
|
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc16[0] +
|
|
(acc2[0] + 1.f/256.f * acc2[1]) * sc16[1] * 1.f/4096.f) -
|
|
dmin * 1.f/16.f * (sumy[0] * sc16[2] + sumy[1] * sc16[3] * 1.f/256.f);
|
|
|
|
qs += step;
|
|
sc += step;
|
|
dh += step;
|
|
}
|
|
|
|
y4 += 8 * QK_K;
|
|
}
|
|
|
|
for (int row = 0; row < N_DST; ++row) {
|
|
all_sum = simd_sum(sumf[row]);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0+ r2*ne0*ne1 + first_row + row] = all_sum;
|
|
}
|
|
}
|
|
}
|
|
#endif
|
|
|
|
kernel void kernel_mul_mv_q5_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const int nb = ne00/QK_K;
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t r1 = tgpig.y;
|
|
const int r2 = tgpig.z;
|
|
|
|
const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q5_K * x = (device const block_q5_K *) src0 + first_row*nb + offset0;
|
|
device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
|
|
float sumf[2]={0.f};
|
|
|
|
const int step = sizeof(block_q5_K) * nb;
|
|
|
|
#if QK_K == 256
|
|
#
|
|
float yl[16], yh[16];
|
|
|
|
const uint16_t kmask1 = 0x3f3f;
|
|
const uint16_t kmask2 = 0x0f0f;
|
|
const uint16_t kmask3 = 0xc0c0;
|
|
|
|
const int tid = tiisg/4;
|
|
const int ix = tiisg%4;
|
|
const int im = tid/4;
|
|
const int ir = tid%4;
|
|
const int n = 8;
|
|
|
|
const int l0 = n*ir;
|
|
const int q_offset = 32*im + l0;
|
|
const int y_offset = 64*im + l0;
|
|
|
|
const uint8_t hm1 = 1u << (2*im);
|
|
const uint8_t hm2 = hm1 << 1;
|
|
const uint8_t hm3 = hm1 << 4;
|
|
const uint8_t hm4 = hm2 << 4;
|
|
|
|
uint16_t sc16[4];
|
|
thread const uint8_t * sc8 = (thread const uint8_t *)sc16;
|
|
|
|
device const float * y1 = yy + ix*QK_K + y_offset;
|
|
|
|
for (int i = ix; i < nb; i += 4) {
|
|
|
|
device const uint8_t * q1 = x[i].qs + q_offset;
|
|
device const uint8_t * qh = x[i].qh + l0;
|
|
device const half * dh = &x[i].d;
|
|
device const uint16_t * a = (device const uint16_t *)x[i].scales + im;
|
|
|
|
device const float * y2 = y1 + 128;
|
|
float4 sumy = {0.f, 0.f, 0.f, 0.f};
|
|
for (int l = 0; l < 8; ++l) {
|
|
yl[l+0] = y1[l+ 0]; sumy[0] += yl[l+0];
|
|
yl[l+8] = y1[l+32]; sumy[1] += yl[l+8];
|
|
yh[l+0] = y2[l+ 0]; sumy[2] += yh[l+0];
|
|
yh[l+8] = y2[l+32]; sumy[3] += yh[l+8];
|
|
}
|
|
|
|
for (int row = 0; row < 2; ++row) {
|
|
|
|
device const uint8_t * q2 = q1 + 64;
|
|
|
|
sc16[0] = a[0] & kmask1;
|
|
sc16[1] = a[2] & kmask1;
|
|
sc16[2] = ((a[4] >> 0) & kmask2) | ((a[0] & kmask3) >> 2);
|
|
sc16[3] = ((a[4] >> 4) & kmask2) | ((a[2] & kmask3) >> 2);
|
|
|
|
float4 acc1 = {0.f};
|
|
float4 acc2 = {0.f};
|
|
for (int l = 0; l < n; ++l) {
|
|
uint8_t h = qh[l];
|
|
acc1[0] += yl[l+0] * (q1[l] & 0x0F);
|
|
acc1[1] += yl[l+8] * (q1[l] & 0xF0);
|
|
acc1[2] += yh[l+0] * (q2[l] & 0x0F);
|
|
acc1[3] += yh[l+8] * (q2[l] & 0xF0);
|
|
acc2[0] += h & hm1 ? yl[l+0] : 0.f;
|
|
acc2[1] += h & hm2 ? yl[l+8] : 0.f;
|
|
acc2[2] += h & hm3 ? yh[l+0] : 0.f;
|
|
acc2[3] += h & hm4 ? yh[l+8] : 0.f;
|
|
}
|
|
const float dall = dh[0];
|
|
const float dmin = dh[1];
|
|
sumf[row] += dall * (sc8[0] * (acc1[0] + 16.f*acc2[0]) +
|
|
sc8[1] * (acc1[1]/16.f + 16.f*acc2[1]) +
|
|
sc8[4] * (acc1[2] + 16.f*acc2[2]) +
|
|
sc8[5] * (acc1[3]/16.f + 16.f*acc2[3])) -
|
|
dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]);
|
|
|
|
q1 += step;
|
|
qh += step;
|
|
dh += step/2;
|
|
a += step/2;
|
|
|
|
}
|
|
|
|
y1 += 4 * QK_K;
|
|
|
|
}
|
|
#else
|
|
float yl[8], yh[8];
|
|
|
|
const int il = 4 * (tiisg/8); // 0, 4, 8, 12
|
|
const int ix = tiisg%8;
|
|
const int im = il/8; // 0, 0, 1, 1
|
|
const int in = il%8; // 0, 4, 0, 4
|
|
|
|
device const float * y = yy + ix*QK_K + il;
|
|
|
|
for (int i = ix; i < nb; i += 8) {
|
|
|
|
for (int l = 0; l < 4; ++l) {
|
|
yl[l+0] = y[l+ 0];
|
|
yl[l+4] = y[l+16];
|
|
yh[l+0] = y[l+32];
|
|
yh[l+4] = y[l+48];
|
|
}
|
|
|
|
device const half * dh = &x[i].d;
|
|
device const uint8_t * q = x[i].qs + il;
|
|
device const uint8_t * h = x[i].qh + in;
|
|
device const int8_t * s = x[i].scales;
|
|
|
|
for (int row = 0; row < 2; ++row) {
|
|
|
|
const float d = dh[0];
|
|
|
|
float2 acc = {0.f, 0.f};
|
|
for (int l = 0; l < 4; ++l) {
|
|
const uint8_t hl = h[l] >> im;
|
|
acc[0] += yl[l+0] * s[0] * ((int16_t)(q[l+ 0] & 0x0F) - (hl & 0x01 ? 0 : 16))
|
|
+ yl[l+4] * s[1] * ((int16_t)(q[l+16] & 0x0F) - (hl & 0x04 ? 0 : 16));
|
|
acc[1] += yh[l+0] * s[2] * ((int16_t)(q[l+ 0] & 0xF0) - (hl & 0x10 ? 0 : 256))
|
|
+ yh[l+4] * s[3] * ((int16_t)(q[l+16] & 0xF0) - (hl & 0x40 ? 0 : 256));
|
|
}
|
|
sumf[row] += d * (acc[0] + 1.f/16.f * acc[1]);
|
|
|
|
q += step;
|
|
h += step;
|
|
s += step;
|
|
dh += step/2;
|
|
|
|
}
|
|
|
|
y += 8 * QK_K;
|
|
}
|
|
#endif
|
|
|
|
for (int row = 0; row < 2; ++row) {
|
|
const float tot = simd_sum(sumf[row]);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = tot;
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
kernel void kernel_mul_mv_q6_K_f32(
|
|
device const void * src0,
|
|
device const float * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne01[[buffer(4)]],
|
|
constant int64_t & ne02[[buffer(5)]],
|
|
constant int64_t & ne10[[buffer(9)]],
|
|
constant int64_t & ne12[[buffer(11)]],
|
|
constant int64_t & ne0[[buffer(15)]],
|
|
constant int64_t & ne1[[buffer(16)]],
|
|
constant uint & gqa[[buffer(17)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiisg[[thread_index_in_simdgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
const uint8_t kmask1 = 0x03;
|
|
const uint8_t kmask2 = 0x0C;
|
|
const uint8_t kmask3 = 0x30;
|
|
const uint8_t kmask4 = 0xC0;
|
|
|
|
const int nb = ne00/QK_K;
|
|
|
|
const int64_t r0 = tgpig.x;
|
|
const int64_t r1 = tgpig.y;
|
|
const int r2 = tgpig.z;
|
|
|
|
const int row = 2 * r0 + sgitg;
|
|
const uint offset0 = r2/gqa*(nb*ne0);
|
|
device const block_q6_K * x = (device const block_q6_K *) src0 + row * nb + offset0;
|
|
device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1;
|
|
|
|
float sumf = 0;
|
|
|
|
#if QK_K == 256
|
|
const int tid = tiisg/2;
|
|
const int ix = tiisg%2;
|
|
const int ip = tid/8; // 0 or 1
|
|
const int il = tid%8;
|
|
const int n = 4;
|
|
const int l0 = n*il;
|
|
const int is = 8*ip + l0/16;
|
|
|
|
const int y_offset = 128*ip + l0;
|
|
const int q_offset_l = 64*ip + l0;
|
|
const int q_offset_h = 32*ip + l0;
|
|
|
|
for (int i = ix; i < nb; i += 2) {
|
|
|
|
device const uint8_t * q1 = x[i].ql + q_offset_l;
|
|
device const uint8_t * q2 = q1 + 32;
|
|
device const uint8_t * qh = x[i].qh + q_offset_h;
|
|
device const int8_t * sc = x[i].scales + is;
|
|
|
|
device const float * y = yy + i * QK_K + y_offset;
|
|
|
|
const float dall = x[i].d;
|
|
|
|
float4 sums = {0.f, 0.f, 0.f, 0.f};
|
|
for (int l = 0; l < n; ++l) {
|
|
sums[0] += y[l+ 0] * ((int8_t)((q1[l] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
|
|
sums[1] += y[l+32] * ((int8_t)((q2[l] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
|
|
sums[2] += y[l+64] * ((int8_t)((q1[l] >> 4) | ((qh[l] & kmask3) << 0)) - 32);
|
|
sums[3] += y[l+96] * ((int8_t)((q2[l] >> 4) | ((qh[l] & kmask4) >> 2)) - 32);
|
|
}
|
|
|
|
sumf += dall * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]);
|
|
|
|
}
|
|
|
|
#else
|
|
const int ix = tiisg/4;
|
|
const int il = 4*(tiisg%4);
|
|
|
|
for (int i = ix; i < nb; i += 8) {
|
|
device const float * y = yy + i * QK_K + il;
|
|
device const uint8_t * ql = x[i].ql + il;
|
|
device const uint8_t * qh = x[i].qh + il;
|
|
device const int8_t * s = x[i].scales;
|
|
|
|
const float d = x[i].d;
|
|
|
|
float4 sums = {0.f, 0.f, 0.f, 0.f};
|
|
for (int l = 0; l < 4; ++l) {
|
|
sums[0] += y[l+ 0] * ((int8_t)((ql[l+ 0] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
|
|
sums[1] += y[l+16] * ((int8_t)((ql[l+16] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
|
|
sums[2] += y[l+32] * ((int8_t)((ql[l+ 0] >> 4) | ((qh[l] & kmask3) >> 0)) - 32);
|
|
sums[3] += y[l+48] * ((int8_t)((ql[l+16] >> 4) | ((qh[l] & kmask4) >> 2)) - 32);
|
|
}
|
|
sumf += d * (sums[0] * s[0] + sums[1] * s[1] + sums[2] * s[2] + sums[3] * s[3]);
|
|
}
|
|
|
|
#endif
|
|
|
|
const float tot = simd_sum(sumf);
|
|
if (tiisg == 0) {
|
|
dst[r1*ne0 + r2*ne0*ne1 + row] = tot;
|
|
}
|
|
}
|
|
|
|
//============================= templates and their specializations =============================
|
|
|
|
// NOTE: this is not dequantizing - we are simply fitting the template
|
|
template <typename type4x4>
|
|
void dequantize_f32(device const float4x4 * src, short il, thread type4x4 & reg) {
|
|
float4x4 temp = *(((device float4x4 *)src));
|
|
for (int i = 0; i < 16; i++){
|
|
reg[i/4][i%4] = temp[i/4][i%4];
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_f16(device const half4x4 * src, short il, thread type4x4 & reg) {
|
|
half4x4 temp = *(((device half4x4 *)src));
|
|
for (int i = 0; i < 16; i++){
|
|
reg[i/4][i%4] = temp[i/4][i%4];
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q4_0(device const block_q4_0 *xb, short il, thread type4x4 & reg) {
|
|
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
|
|
const float d1 = il ? (xb->d / 16.h) : xb->d;
|
|
const float d2 = d1 / 256.f;
|
|
const float md = -8.h * xb->d;
|
|
const ushort mask0 = il ? 0x00F0 : 0x000F;
|
|
const ushort mask1 = mask0 << 8;
|
|
|
|
for (int i=0;i<8;i++) {
|
|
reg[i/2][2*(i%2)+0] = d1 * (qs[i] & mask0) + md;
|
|
reg[i/2][2*(i%2)+1] = d2 * (qs[i] & mask1) + md;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q4_1(device const block_q4_1 *xb, short il, thread type4x4 & reg) {
|
|
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
|
|
const float d1 = il ? (xb->d / 16.h) : xb->d;
|
|
const float d2 = d1 / 256.f;
|
|
const float m = xb->m;
|
|
const ushort mask0 = il ? 0x00F0 : 0x000F;
|
|
const ushort mask1 = mask0 << 8;
|
|
|
|
for (int i=0;i<8;i++) {
|
|
reg[i/2][2*(i%2)+0] = ((qs[i] & mask0) * d1) + m;
|
|
reg[i/2][2*(i%2)+1] = ((qs[i] & mask1) * d2) + m;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q5_0(device const block_q5_0 *xb, short il, thread type4x4 & reg) {
|
|
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
|
|
const float d = xb->d;
|
|
const float md = -16.h * xb->d;
|
|
const ushort mask = il ? 0x00F0 : 0x000F;
|
|
|
|
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
|
|
|
const int x_mv = il ? 4 : 0;
|
|
|
|
const int gh_mv = il ? 12 : 0;
|
|
const int gh_bk = il ? 0 : 4;
|
|
|
|
for (int i = 0; i < 8; i++) {
|
|
// extract the 5-th bits for x0 and x1
|
|
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
|
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
|
|
|
// combine the 4-bits from qs with the 5th bit
|
|
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
|
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
|
|
|
reg[i/2][2*(i%2)+0] = d * x0 + md;
|
|
reg[i/2][2*(i%2)+1] = d * x1 + md;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q5_1(device const block_q5_1 *xb, short il, thread type4x4 & reg) {
|
|
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
|
|
const float d = xb->d;
|
|
const float m = xb->m;
|
|
const ushort mask = il ? 0x00F0 : 0x000F;
|
|
|
|
const uint32_t qh = *((device const uint32_t *)xb->qh);
|
|
|
|
const int x_mv = il ? 4 : 0;
|
|
|
|
const int gh_mv = il ? 12 : 0;
|
|
const int gh_bk = il ? 0 : 4;
|
|
|
|
for (int i = 0; i < 8; i++) {
|
|
// extract the 5-th bits for x0 and x1
|
|
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
|
|
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
|
|
|
|
// combine the 4-bits from qs with the 5th bit
|
|
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
|
|
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
|
|
|
|
reg[i/2][2*(i%2)+0] = d * x0 + m;
|
|
reg[i/2][2*(i%2)+1] = d * x1 + m;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q8_0(device const block_q8_0 *xb, short il, thread type4x4 & reg) {
|
|
device const int8_t * qs = ((device const int8_t *)xb->qs);
|
|
const half d = xb->d;
|
|
|
|
for (int i=0;i<16;i++) {
|
|
reg[i/4][i%4] = (qs[i + 16*il] * d);
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
|
|
const half d = xb->d;
|
|
const half min = xb->dmin;
|
|
device const uint8_t * q = (device const uint8_t *)xb->qs;
|
|
half dl, ml;
|
|
uint8_t sc = xb->scales[il];
|
|
|
|
#if QK_K == 256
|
|
q = q + 32*(il/8) + 16*(il&1);
|
|
il = (il/2)%4;
|
|
#endif
|
|
half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
|
|
uchar mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
|
dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg) {
|
|
const half d_all = xb->d;
|
|
device const uint8_t * q = (device const uint8_t *)xb->qs;
|
|
device const uint8_t * h = (device const uint8_t *)xb->hmask;
|
|
device const int8_t * scales = (device const int8_t *)xb->scales;
|
|
|
|
#if QK_K == 256
|
|
q = q + 32 * (il/8) + 16 * (il&1);
|
|
h = h + 16 * (il&1);
|
|
uint8_t m = 1 << (il/2);
|
|
uint16_t kmask1 = (il/4)>1 ? ((il/4)>2 ? 192 : 48) : \
|
|
((il/4)>0 ? 12 : 3);
|
|
uint16_t kmask2 = il/8 ? 0xF0 : 0x0F;
|
|
uint16_t scale_2 = scales[il%8], scale_1 = scales[8 + il%4];
|
|
int16_t dl_int = (il/4)&1 ? (scale_2&kmask2) | ((scale_1&kmask1) << 2)
|
|
: (scale_2&kmask2) | ((scale_1&kmask1) << 4);
|
|
half dl = il<8 ? d_all * (dl_int - 32.h) : d_all * (dl_int / 16.h - 32.h);
|
|
const half ml = 4.h * dl;
|
|
|
|
il = (il/2) & 3;
|
|
const half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
|
|
const uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
|
dl *= coef;
|
|
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = dl * (q[i] & mask) - (h[i] & m ? 0 : ml);
|
|
}
|
|
#else
|
|
float kcoef = il&1 ? 1.f/16.f : 1.f;
|
|
uint16_t kmask = il&1 ? 0xF0 : 0x0F;
|
|
float dl = d_all * ((scales[il/2] & kmask) * kcoef - 8);
|
|
float coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
|
|
uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
|
uint8_t m = 1<<(il*2);
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = coef * dl * ((q[i] & mask) - ((h[i%8] & (m * (1 + i/8))) ? 0 : 4.f/coef));
|
|
}
|
|
#endif
|
|
}
|
|
|
|
static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
|
|
return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
|
|
: uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)), uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 & reg) {
|
|
device const uchar * q = xb->qs;
|
|
|
|
#if QK_K == 256
|
|
short is = (il/4) * 2;
|
|
q = q + (il/4) * 32 + 16 * (il&1);
|
|
il = il & 3;
|
|
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
|
|
const half d = il < 2 ? xb->d : xb->d / 16.h;
|
|
const half min = xb->dmin;
|
|
const half dl = d * sc[0];
|
|
const half ml = min * sc[1];
|
|
#else
|
|
q = q + 16 * (il&1);
|
|
device const uint8_t * s = xb->scales;
|
|
device const half2 * dh = (device const half2 *)xb->d;
|
|
const float2 d = (float2)dh[0];
|
|
const float dl = il<2 ? d[0] * (s[0]&0xF) : d[0] * (s[1]&0xF)/16.h;
|
|
const float ml = il<2 ? d[1] * (s[0]>>4) : d[1] * (s[1]>>4);
|
|
#endif
|
|
const ushort mask = il<2 ? 0x0F : 0xF0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
|
|
}
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg) {
|
|
device const uint8_t * q = xb->qs;
|
|
device const uint8_t * qh = xb->qh;
|
|
|
|
#if QK_K == 256
|
|
short is = (il/4) * 2;
|
|
q = q + 32 * (il/4) + 16 * (il&1);
|
|
qh = qh + 16 * (il&1);
|
|
uint8_t ul = 1 << (il/2);
|
|
il = il & 3;
|
|
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
|
|
const half d = il < 2 ? xb->d : xb->d / 16.h;
|
|
const half min = xb->dmin;
|
|
const half dl = d * sc[0];
|
|
const half ml = min * sc[1];
|
|
|
|
const ushort mask = il<2 ? 0x0F : 0xF0;
|
|
const half qh_val = il<2 ? 16.h : 256.h;
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml;
|
|
}
|
|
#else
|
|
q = q + 16 * (il&1);
|
|
device const int8_t * s = xb->scales;
|
|
const float dl = xb->d * s[il];
|
|
uint8_t m = 1<<(il*2);
|
|
const float coef = il<2 ? 1.f : 1.f/16.f;
|
|
const ushort mask = il<2 ? 0x0F : 0xF0;
|
|
for (int i = 0; i < 16; ++i) {
|
|
reg[i/4][i%4] = coef * dl * ((q[i] & mask) - (qh[i%8] & (m*(1+i/8)) ? 0.f : 16.f/coef));
|
|
}
|
|
#endif
|
|
}
|
|
|
|
template <typename type4x4>
|
|
void dequantize_q6_K(device const block_q6_K *xb, short il, thread type4x4 & reg) {
|
|
const half d_all = xb->d;
|
|
device const uint8_t * ql = (device const uint8_t *)xb->ql;
|
|
device const uint8_t * qh = (device const uint8_t *)xb->qh;
|
|
device const int8_t * scales = (device const int8_t *)xb->scales;
|
|
|
|
#if QK_K == 256
|
|
ql = ql + 64*(il/8) + 32*((il/2)&1) + 16*(il&1);
|
|
qh = qh + 32*(il/8) + 16*(il&1);
|
|
half sc = scales[(il%2) + 2 * ((il/2))];
|
|
il = (il/2) & 3;
|
|
#else
|
|
ql = ql + 16 * (il&1);
|
|
half sc = scales[il];
|
|
#endif
|
|
const uint16_t kmask1 = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
|
|
const uint16_t kmask2 = il>1 ? 0xF0 : 0x0F;
|
|
const half coef = il>1 ? 1.f/16.h : 1.h;
|
|
const half ml = d_all * sc * 32.h;
|
|
const half dl = d_all * sc * coef;
|
|
for (int i = 0; i < 16; ++i) {
|
|
const half q = il&1 ? ((ql[i] & kmask2) | ((qh[i] & kmask1) << 2))
|
|
: ((ql[i] & kmask2) | ((qh[i] & kmask1) << 4));
|
|
reg[i/4][i%4] = dl * q - ml;
|
|
}
|
|
}
|
|
|
|
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread float4x4 &)>
|
|
kernel void kernel_get_rows(
|
|
device const void * src0,
|
|
device const int * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant uint64_t & nb01,
|
|
constant uint64_t & nb1,
|
|
uint tgpig[[threadgroup_position_in_grid]],
|
|
uint tiitg[[thread_index_in_threadgroup]],
|
|
uint tptg[[threads_per_threadgroup]]) {
|
|
const int i = tgpig;
|
|
const int r = ((device int32_t *) src1)[i];
|
|
|
|
for (int ind = tiitg; ind < ne00/16; ind += tptg) {
|
|
float4x4 temp;
|
|
dequantize_func(
|
|
((device const block_q *) ((device char *) src0 + r*nb01)) + ind/nl, ind%nl, temp);
|
|
*(((device float4x4 *) ((device char *) dst + i*nb1)) + ind) = temp;
|
|
}
|
|
}
|
|
|
|
#define BLOCK_SIZE_M 64 // 8 simdgroup matrices from matrix A
|
|
#define BLOCK_SIZE_N 32 // 4 simdgroup matrices from matrix B
|
|
#define BLOCK_SIZE_K 32
|
|
#define THREAD_MAT_M 4 // each thread take 4 simdgroup matrices from matrix A
|
|
#define THREAD_MAT_N 2 // each thread take 2 simdgroup matrices from matrix B
|
|
#define THREAD_PER_BLOCK 128
|
|
#define THREAD_PER_ROW 2 // 2 thread for each row in matrix A to load numbers
|
|
#define THREAD_PER_COL 4 // 4 thread for each row in matrix B to load numbers
|
|
#define SG_MAT_SIZE 64 // simdgroup matrix is of shape 8x8
|
|
#define SG_MAT_ROW 8
|
|
|
|
// each block_q contains 16*nl weights
|
|
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread half4x4 &)>
|
|
kernel void kernel_mul_mm(device const uchar * src0,
|
|
device const uchar * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
|
|
constant int64_t & ne02,
|
|
constant int64_t & nb01,
|
|
constant int64_t & nb02,
|
|
constant int64_t & ne12,
|
|
constant int64_t & nb10,
|
|
constant int64_t & nb11,
|
|
constant int64_t & nb12,
|
|
constant int64_t & ne0,
|
|
constant int64_t & ne1,
|
|
constant uint & gqa,
|
|
threadgroup uchar * shared_memory [[threadgroup(0)]],
|
|
uint3 tgpig[[threadgroup_position_in_grid]],
|
|
uint tiitg[[thread_index_in_threadgroup]],
|
|
uint sgitg[[simdgroup_index_in_threadgroup]]) {
|
|
|
|
threadgroup half * sa = (threadgroup half *)(shared_memory);
|
|
threadgroup float * sb = (threadgroup float *)(shared_memory + 4096);
|
|
|
|
const uint r0 = tgpig.y;
|
|
const uint r1 = tgpig.x;
|
|
const uint im = tgpig.z;
|
|
|
|
// if this block is of 64x32 shape or smaller
|
|
short n_rows = (ne0 - r0 * BLOCK_SIZE_M < BLOCK_SIZE_M) ? (ne0 - r0 * BLOCK_SIZE_M) : BLOCK_SIZE_M;
|
|
short n_cols = (ne1 - r1 * BLOCK_SIZE_N < BLOCK_SIZE_N) ? (ne1 - r1 * BLOCK_SIZE_N) : BLOCK_SIZE_N;
|
|
|
|
// a thread shouldn't load data outside of the matrix
|
|
short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1;
|
|
short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1;
|
|
|
|
simdgroup_half8x8 ma[4];
|
|
simdgroup_float8x8 mb[2];
|
|
simdgroup_float8x8 c_res[8];
|
|
for (int i = 0; i < 8; i++){
|
|
c_res[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
|
|
}
|
|
|
|
short il = (tiitg % THREAD_PER_ROW);
|
|
|
|
uint offset0 = im/gqa*nb02;
|
|
ushort offset1 = il/nl;
|
|
|
|
device const block_q * x = (device const block_q *)(src0 + (r0 * BLOCK_SIZE_M + thread_row) * nb01 + offset0) + offset1;
|
|
device const float * y = (device const float *)(src1
|
|
+ nb12 * im
|
|
+ nb11 * (r1 * BLOCK_SIZE_N + thread_col)
|
|
+ nb10 * (BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL)));
|
|
|
|
for (int loop_k = 0; loop_k < ne00; loop_k += BLOCK_SIZE_K) {
|
|
// load data and store to threadgroup memory
|
|
half4x4 temp_a;
|
|
dequantize_func(x, il, temp_a);
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
|
|
#pragma unroll(16)
|
|
for (int i = 0; i < 16; i++) {
|
|
*(sa + SG_MAT_SIZE * ((tiitg / THREAD_PER_ROW / 8) \
|
|
+ (tiitg % THREAD_PER_ROW) * 16 + (i / 8) * 8) \
|
|
+ (tiitg / THREAD_PER_ROW) % 8 + (i & 7) * 8) = temp_a[i/4][i%4];
|
|
}
|
|
|
|
*(threadgroup float2x4 *)(sb + (tiitg % THREAD_PER_COL) * 8 * 32 + 8 * (tiitg / THREAD_PER_COL)) = *((device float2x4 *)y);
|
|
|
|
il = (il + 2 < nl) ? il + 2 : il % 2;
|
|
x = (il < 2) ? x + (2+nl-1)/nl : x;
|
|
y += BLOCK_SIZE_K;
|
|
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
|
|
// load matrices from threadgroup memory and conduct outer products
|
|
threadgroup half * lsma = (sa + THREAD_MAT_M * SG_MAT_SIZE * (sgitg % 2));
|
|
threadgroup float * lsmb = (sb + THREAD_MAT_N * SG_MAT_SIZE * (sgitg / 2));
|
|
|
|
#pragma unroll(4)
|
|
for (int ik = 0; ik < BLOCK_SIZE_K / 8; ik++) {
|
|
#pragma unroll(4)
|
|
for (int i = 0; i < 4; i++) {
|
|
simdgroup_load(ma[i],lsma + SG_MAT_SIZE * i);
|
|
}
|
|
simdgroup_barrier(mem_flags::mem_none);
|
|
#pragma unroll(2)
|
|
for (int i = 0; i < 2; i++) {
|
|
simdgroup_load(mb[i],lsmb + SG_MAT_SIZE * i);
|
|
}
|
|
|
|
lsma += BLOCK_SIZE_M / SG_MAT_ROW * SG_MAT_SIZE;
|
|
lsmb += BLOCK_SIZE_N / SG_MAT_ROW * SG_MAT_SIZE;
|
|
|
|
#pragma unroll(8)
|
|
for (int i = 0; i < 8; i++){
|
|
simdgroup_multiply_accumulate(c_res[i], mb[i/4], ma[i%4], c_res[i]);
|
|
}
|
|
}
|
|
}
|
|
|
|
if ((r0 + 1) * BLOCK_SIZE_M <= ne0 && (r1 + 1) * BLOCK_SIZE_N <= ne1) {
|
|
device float * C = dst + (BLOCK_SIZE_M * r0 + 32 * (sgitg & 1)) \
|
|
+ (BLOCK_SIZE_N * r1 + 16 * (sgitg >> 1)) * ne0 + im*ne1*ne0;
|
|
for (int i = 0; i < 8; i++) {
|
|
simdgroup_store(c_res[i], C + 8 * (i%4) + 8 * ne0 * (i/4), ne0);
|
|
}
|
|
} else {
|
|
// block is smaller than 64x32, we should avoid writing data outside of the matrix
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
threadgroup float * temp_str = ((threadgroup float *)shared_memory) \
|
|
+ 32 * (sgitg&1) + (16 * (sgitg>>1)) * BLOCK_SIZE_M;
|
|
for (int i = 0; i < 8; i++) {
|
|
simdgroup_store(c_res[i], temp_str + 8 * (i%4) + 8 * BLOCK_SIZE_M * (i/4), BLOCK_SIZE_M);
|
|
}
|
|
|
|
threadgroup_barrier(mem_flags::mem_threadgroup);
|
|
|
|
device float * C = dst + (BLOCK_SIZE_M * r0) + (BLOCK_SIZE_N * r1) * ne0 + im*ne1*ne0;
|
|
if (sgitg == 0) {
|
|
for (int i = 0; i < n_rows; i++) {
|
|
for (int j = tiitg; j < n_cols; j += BLOCK_SIZE_N) {
|
|
*(C + i + j * ne0) = *(temp_str + i + j * BLOCK_SIZE_M);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
#if QK_K == 256
|
|
#define QK_NL 16
|
|
#else
|
|
#define QK_NL 4
|
|
#endif
|
|
|
|
typedef void (get_rows_t)(device const void *, device const int *, device float *, constant int64_t &, \
|
|
constant uint64_t &, constant uint64_t &, uint, uint, uint);
|
|
|
|
template [[host_name("kernel_get_rows_f32")]] kernel get_rows_t kernel_get_rows<float4x4, 1, dequantize_f32>;
|
|
template [[host_name("kernel_get_rows_f16")]] kernel get_rows_t kernel_get_rows<half4x4, 1, dequantize_f16>;
|
|
template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_t kernel_get_rows<block_q4_0, 2, dequantize_q4_0>;
|
|
template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_t kernel_get_rows<block_q4_1, 2, dequantize_q4_1>;
|
|
template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_t kernel_get_rows<block_q5_0, 2, dequantize_q5_0>;
|
|
template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_t kernel_get_rows<block_q5_1, 2, dequantize_q5_1>;
|
|
template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_t kernel_get_rows<block_q8_0, 2, dequantize_q8_0>;
|
|
template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_t kernel_get_rows<block_q2_K, QK_NL, dequantize_q2_K>;
|
|
template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_t kernel_get_rows<block_q3_K, QK_NL, dequantize_q3_K>;
|
|
template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_t kernel_get_rows<block_q4_K, QK_NL, dequantize_q4_K>;
|
|
template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_t kernel_get_rows<block_q5_K, QK_NL, dequantize_q5_K>;
|
|
template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_t kernel_get_rows<block_q6_K, QK_NL, dequantize_q6_K>;
|
|
|
|
typedef void (mat_mm_t)(
|
|
device const uchar * src0,
|
|
device const uchar * src1,
|
|
device float * dst,
|
|
constant int64_t & ne00,
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constant int64_t & ne02,
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constant int64_t & nb01,
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constant int64_t & nb02,
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constant int64_t & ne12,
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constant int64_t & nb10,
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constant int64_t & nb11,
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constant int64_t & nb12,
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constant int64_t & ne0,
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constant int64_t & ne1,
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constant uint & gqa,
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threadgroup uchar *, uint3, uint, uint);
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template [[host_name("kernel_mul_mm_f32_f32")]] kernel mat_mm_t kernel_mul_mm<float4x4, 1, dequantize_f32>;
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template [[host_name("kernel_mul_mm_f16_f32")]] kernel mat_mm_t kernel_mul_mm<half4x4, 1, dequantize_f16>;
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template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mat_mm_t kernel_mul_mm<block_q4_0, 2, dequantize_q4_0>;
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template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mat_mm_t kernel_mul_mm<block_q4_1, 2, dequantize_q4_1>;
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template [[host_name("kernel_mul_mm_q5_0_f32")]] kernel mat_mm_t kernel_mul_mm<block_q5_0, 2, dequantize_q5_0>;
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template [[host_name("kernel_mul_mm_q5_1_f32")]] kernel mat_mm_t kernel_mul_mm<block_q5_1, 2, dequantize_q5_1>;
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template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mat_mm_t kernel_mul_mm<block_q8_0, 2, dequantize_q8_0>;
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template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mat_mm_t kernel_mul_mm<block_q2_K, QK_NL, dequantize_q2_K>;
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template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mat_mm_t kernel_mul_mm<block_q3_K, QK_NL, dequantize_q3_K>;
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template [[host_name("kernel_mul_mm_q4_K_f32")]] kernel mat_mm_t kernel_mul_mm<block_q4_K, QK_NL, dequantize_q4_K>;
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template [[host_name("kernel_mul_mm_q5_K_f32")]] kernel mat_mm_t kernel_mul_mm<block_q5_K, QK_NL, dequantize_q5_K>;
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template [[host_name("kernel_mul_mm_q6_K_f32")]] kernel mat_mm_t kernel_mul_mm<block_q6_K, QK_NL, dequantize_q6_K>;
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