ollama/llama/ggml-cuda/cpy.cu

/**
 * llama.cpp - commit 3f1ae2e32cde00c39b96be6d01c2997c29bae555 - do not edit this file
 *
 * MIT License
 *
 * Copyright (c) 2023-2024 The ggml authors
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */

#include "cpy.cuh"

typedef void (*cpy_kernel_t)(const char * cx, char * cdst);

static __device__ void cpy_1_f32_f32(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    float * dsti = (float *) cdsti;

    *dsti = *xi;
}

static __device__ void cpy_1_f32_f16(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    half * dsti = (half *) cdsti;

    *dsti = __float2half(*xi);
}

static __device__ void cpy_1_f16_f16(const char * cxi, char * cdsti) {
    const half * xi = (const half *) cxi;
    half * dsti = (half *) cdsti;

    *dsti = *xi;
}

static __device__ void cpy_1_f16_f32(const char * cxi, char * cdsti) {
    const half * xi = (const half *) cxi;
    float * dsti = (float *) cdsti;

    *dsti = *xi;
}

template <cpy_kernel_t cpy_1>
static __global__ void cpy_f32_f16(const char * cx, char * cdst, const int ne,
                                   const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
                                   const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
                                   const int nb12, const int nb13) {
    const int64_t i = blockDim.x*blockIdx.x + threadIdx.x;

    if (i >= ne) {
        return;
    }

    // determine indices i03/i13, i02/i12, i01/i11, i00/i10 as a function of index i of flattened tensor
    // then combine those indices with the corresponding byte offsets to get the total offsets
    const int64_t i03 = i/(ne00 * ne01 * ne02);
    const int64_t i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
    const int64_t i01 = (i - i03*ne00*ne01*ne02  -  i02*ne01*ne00) / ne00;
    const int64_t i00 = i - i03*ne00*ne01*ne02 - i02*ne01*ne00 - i01*ne00;
    const int64_t x_offset = i00*nb00 + i01*nb01 + i02*nb02 + i03 * nb03;

    const int64_t i13 = i/(ne10 * ne11 * ne12);
    const int64_t i12 = (i - i13*ne10*ne11*ne12) / (ne10*ne11);
    const int64_t i11 = (i - i13*ne10*ne11*ne12 - i12*ne10*ne11) / ne10;
    const int64_t i10 = i - i13*ne10*ne11*ne12 - i12*ne10*ne11 - i11*ne10;
    const int64_t dst_offset = i10*nb10 + i11*nb11 + i12*nb12 + i13 * nb13;

    cpy_1(cx + x_offset, cdst + dst_offset);
}

static __device__ void cpy_blck_f32_q8_0(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_q8_0 * dsti = (block_q8_0 *) cdsti;

    float amax = 0.0f; // absolute max

    for (int j = 0; j < QK8_0; j++) {
        const float v = xi[j];
        amax = fmaxf(amax, fabsf(v));
    }

    const float d = amax / ((1 << 7) - 1);
    const float id = d ? 1.0f/d : 0.0f;

    dsti->d = d;

    for (int j = 0; j < QK8_0; ++j) {
        const float x0 = xi[j]*id;

        dsti->qs[j] = roundf(x0);
    }
}

static __device__ void cpy_blck_q8_0_f32(const char * cxi, char * cdsti) {
    const block_q8_0 * xi = (const block_q8_0 *) cxi;
    float * dsti = (float *) cdsti;

    const float d = (float)xi->d;

    for (int j = 0; j < QK8_0; j++) {
       dsti[j] = xi->qs[j] * d;
    }
}

static __device__ void cpy_blck_f32_q4_0(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_q4_0 * dsti = (block_q4_0 *) cdsti;

    float amax = 0.0f;
    float vmax = 0.0f;

    for (int j = 0; j < QK4_0; ++j) {
        const float v = xi[j];
        if (amax < fabsf(v)) {
            amax = fabsf(v);
            vmax = v;
        }
    }

    const float d  = vmax / -8;
    const float id = d ? 1.0f/d : 0.0f;

    dsti->d = d;

    for (int j = 0; j < QK4_0/2; ++j) {
        const float x0 = xi[0       + j]*id;
        const float x1 = xi[QK4_0/2 + j]*id;

        const uint8_t xi0 = min(15, (int8_t)(x0 + 8.5f));
        const uint8_t xi1 = min(15, (int8_t)(x1 + 8.5f));

        dsti->qs[j]  = xi0;
        dsti->qs[j] |= xi1 << 4;
    }
}

static __device__ void cpy_blck_f32_q4_1(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_q4_1 * dsti = (block_q4_1 *) cdsti;

    float vmin = FLT_MAX;
    float vmax = -FLT_MAX;

    for (int j = 0; j < QK4_1; ++j) {
        const float v = xi[j];

        if (v < vmin) vmin = v;
        if (v > vmax) vmax = v;
    }

    const float d  = (vmax - vmin) / ((1 << 4) - 1);
    const float id = d ? 1.0f/d : 0.0f;

    dsti->dm.x = d;
    dsti->dm.y = vmin;

    for (int j = 0; j < QK4_1/2; ++j) {
        const float x0 = (xi[0       + j] - vmin)*id;
        const float x1 = (xi[QK4_1/2 + j] - vmin)*id;

        const uint8_t xi0 = min(15, (int8_t)(x0 + 0.5f));
        const uint8_t xi1 = min(15, (int8_t)(x1 + 0.5f));

        dsti->qs[j]  = xi0;
        dsti->qs[j] |= xi1 << 4;
    }
}

static __device__ void cpy_blck_f32_q5_0(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_q5_0 * dsti = (block_q5_0 *) cdsti;

    float amax = 0.0f;
    float vmax = 0.0f;

    for (int j = 0; j < QK5_0; ++j) {
        const float v = xi[j];
        if (amax < fabsf(v)) {
            amax = fabsf(v);
            vmax = v;
        }
    }

    const float d  = vmax / -16;
    const float id = d ? 1.0f/d : 0.0f;

    dsti->d = d;

    uint32_t qh = 0;
    for (int j = 0; j < QK5_0/2; ++j) {
        const float x0 = xi[0       + j]*id;
        const float x1 = xi[QK5_0/2 + j]*id;

        const uint8_t xi0 = min(31, (int8_t)(x0 + 16.5f));
        const uint8_t xi1 = min(31, (int8_t)(x1 + 16.5f));

        dsti->qs[j]  = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
        qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
        qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
    }
    memcpy(dsti->qh, &qh, sizeof(qh));
}

static __device__ void cpy_blck_f32_q5_1(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_q5_1 * dsti = (block_q5_1 *) cdsti;

    float min = xi[0];
    float max = xi[0];

    for (int j = 1; j < QK5_1; ++j) {
        const float v = xi[j];
        min = v < min ? v : min;
        max = v > max ? v : max;
    }

    const float d  = (max - min) / 31;
    const float id = d ? 1.0f/d : 0.0f;

    dsti->dm.x = d;
    dsti->dm.y = min;

    uint32_t qh = 0;
    for (int j = 0; j < QK5_1/2; ++j) {
        const float x0 = (xi[0       + j] - min)*id;
        const float x1 = (xi[QK5_1/2 + j] - min)*id;

        const uint8_t xi0 = (uint8_t)(x0 + 0.5f);
        const uint8_t xi1 = (uint8_t)(x1 + 0.5f);

        dsti->qs[j]  = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
        qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
        qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_1/2);
    }
    memcpy(dsti->qh, &qh, sizeof(qh));
}


static __device__ __forceinline__ int best_index_int8(int n, const int8_t * val, float x) {
    if (x <= val[0]) return 0;
    if (x >= val[n-1]) return n-1;
    int ml = 0, mu = n-1;
    while (mu-ml > 1) {
        int mav = (ml+mu)/2;
        if (x < val[mav]) mu = mav; else ml = mav;
    }
    return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
}

static __device__ void cpy_blck_f32_iq4_nl(const char * cxi, char * cdsti) {
    const float * xi = (const float *) cxi;
    block_iq4_nl * dsti = (block_iq4_nl *) cdsti;

    float amax = 0.0f;
    float vmax = 0.0f;

    for (int j = 0; j < QK4_NL; ++j) {
        const float v = xi[j];
        if (amax < fabsf(v)) {
            amax = fabsf(v);
            vmax = v;
        }
    }

    float d = vmax / kvalues_iq4nl[0];
    const float id = d ? 1.0f/d : 0.0f;

    float sumqx = 0, sumq2 = 0;
    for (int j = 0; j < QK4_NL/2; ++j) {
        const float x0 = xi[0        + j]*id;
        const float x1 = xi[QK4_NL/2 + j]*id;
        const uint8_t xi0 = best_index_int8(16, kvalues_iq4nl, x0);
        const uint8_t xi1 = best_index_int8(16, kvalues_iq4nl, x1);
        dsti->qs[j] = xi0 | (xi1 << 4);
        const float v0 = kvalues_iq4nl[xi0];
        const float v1 = kvalues_iq4nl[xi1];
        const float w0 = xi[0        + j]*xi[0        + j];
        const float w1 = xi[QK4_NL/2 + j]*xi[QK4_NL/2 + j];
        sumqx += w0*v0*xi[j] + w1*v1*xi[QK4_NL/2 + j];
        sumq2 += w0*v0*v0 + w1*v1*v1;
    }

    dsti->d = sumq2 > 0 ? sumqx/sumq2 : d;
}

template <cpy_kernel_t cpy_blck, int qk>
static __global__ void cpy_f32_q(const char * cx, char * cdst, const int ne,
                                 const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
                                 const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
                                 const int nb12, const int nb13) {
    const int i = (blockDim.x*blockIdx.x + threadIdx.x)*qk;

    if (i >= ne) {
        return;
    }

    const int i03 = i/(ne00 * ne01 * ne02);
    const int i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
    const int i01 = (i - i03*ne00*ne01*ne02  -  i02*ne01*ne00) / ne00;
    const int i00 = i - i03*ne00*ne01*ne02 - i02*ne01*ne00 - i01*ne00;
    const int x_offset = i00*nb00 + i01*nb01 + i02*nb02 + i03 * nb03;

    const int i13 = i/(ne10 * ne11 * ne12);
    const int i12 = (i - i13*ne10*ne11*ne12) / (ne10*ne11);
    const int i11 = (i - i13*ne10*ne11*ne12 - i12*ne10*ne11) / ne10;
    const int i10 = i - i13*ne10*ne11*ne12 - i12*ne10*ne11 - i11*ne10;
    const int dst_offset = (i10/qk)*nb10 + i11*nb11 + i12*nb12 + i13*nb13;

    cpy_blck(cx + x_offset, cdst + dst_offset);
}

template <cpy_kernel_t cpy_blck, int qk>
static __global__ void cpy_q_f32(const char * cx, char * cdst, const int ne,
                                 const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
                                 const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11,
                                 const int nb12, const int nb13) {
    const int i = (blockDim.x*blockIdx.x + threadIdx.x)*qk;

    if (i >= ne) {
        return;
    }

    const int i03 = i/(ne00 * ne01 * ne02);
    const int i02 = (i - i03*ne00*ne01*ne02 )/ (ne00*ne01);
    const int i01 = (i - i03*ne00*ne01*ne02  -  i02*ne01*ne00) / ne00;
    const int i00 = i - i03*ne00*ne01*ne02 - i02*ne01*ne00 - i01*ne00;
    const int x_offset = (i00/qk)*nb00 + i01*nb01 + i02*nb02 + i03 * nb03;

    const int i13 = i/(ne10 * ne11 * ne12);
    const int i12 = (i - i13*ne10*ne11*ne12) / (ne10*ne11);
    const int i11 = (i - i13*ne10*ne11*ne12 - i12*ne10*ne11) / ne10;
    const int i10 = i - i13*ne10*ne11*ne12 - i12*ne10*ne11 - i11*ne10;
    const int dst_offset = i10*nb10 + i11*nb11 + i12*nb12 + i13*nb13;

    cpy_blck(cx + x_offset, cdst + dst_offset);
}

static void ggml_cpy_f16_f32_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
    cpy_f32_f16<cpy_1_f16_f32><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_f32_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
    cpy_f32_f16<cpy_1_f32_f32><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_f16_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
    cpy_f32_f16<cpy_1_f32_f16><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_q8_0_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK8_0 == 0);
    const int num_blocks = ne / QK8_0;
    cpy_f32_q<cpy_blck_f32_q8_0, QK8_0><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_q8_0_f32_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    const int num_blocks = ne;
    cpy_q_f32<cpy_blck_q8_0_f32, QK8_0><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_q4_0_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK4_0 == 0);
    const int num_blocks = ne / QK4_0;
    cpy_f32_q<cpy_blck_f32_q4_0, QK4_0><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_q4_1_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK4_1 == 0);
    const int num_blocks = ne / QK4_1;
    cpy_f32_q<cpy_blck_f32_q4_1, QK4_1><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_q5_0_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK5_0 == 0);
    const int num_blocks = ne / QK5_0;
    cpy_f32_q<cpy_blck_f32_q5_0, QK5_0><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_q5_1_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK5_1 == 0);
    const int num_blocks = ne / QK5_1;
    cpy_f32_q<cpy_blck_f32_q5_1, QK5_1><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f32_iq4_nl_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    GGML_ASSERT(ne % QK4_NL == 0);
    const int num_blocks = ne / QK4_NL;
    cpy_f32_q<cpy_blck_f32_iq4_nl, QK4_NL><<<num_blocks, 1, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

static void ggml_cpy_f16_f16_cuda(
    const char * cx, char * cdst, const int ne,
    const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02,
    const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) {

    const int num_blocks = (ne + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE;
    cpy_f32_f16<cpy_1_f16_f16><<<num_blocks, CUDA_CPY_BLOCK_SIZE, 0, stream>>>
        (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13);
}

void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, ggml_tensor * src1) {
    const int64_t ne = ggml_nelements(src0);
    GGML_ASSERT(ne == ggml_nelements(src1));

    GGML_ASSERT(ggml_nbytes(src0) <= INT_MAX);
    GGML_ASSERT(ggml_nbytes(src1) <= INT_MAX);

    const int64_t ne00 = src0->ne[0];
    const int64_t ne01 = src0->ne[1];
    const int64_t ne02 = src0->ne[2];

    //GGML_ASSERT(src0->ne[3] == 1);

    const int64_t nb00 = src0->nb[0];
    const int64_t nb01 = src0->nb[1];
    const int64_t nb02 = src0->nb[2];
    const int64_t nb03 = src0->nb[3];

    const int64_t ne10 = src1->ne[0];
    const int64_t ne11 = src1->ne[1];
    const int64_t ne12 = src1->ne[2];

    //GGML_ASSERT(src1->ne[3] == 1);

    const int64_t nb10 = src1->nb[0];
    const int64_t nb11 = src1->nb[1];
    const int64_t nb12 = src1->nb[2];
    const int64_t nb13 = src1->nb[3];

    cudaStream_t main_stream = ctx.stream();

    char * src0_ddc = (char *) src0->data;
    char * src1_ddc = (char *) src1->data;

    if (src0->type == src1->type && ggml_is_contiguous(src0) && ggml_is_contiguous(src1)) {
        GGML_ASSERT(ggml_nbytes(src0) == ggml_nbytes(src1));
        CUDA_CHECK(cudaMemcpyAsync(src1_ddc, src0_ddc, ggml_nbytes(src0), cudaMemcpyDeviceToDevice, main_stream));
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32) {
        ggml_cpy_f32_f32_cuda (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16) {
        ggml_cpy_f32_f16_cuda (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
        ggml_cpy_f32_q8_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
        ggml_cpy_q8_0_f32_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
        ggml_cpy_f32_q4_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
        ggml_cpy_f32_q4_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) {
        ggml_cpy_f32_q5_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) {
        ggml_cpy_f32_iq4_nl_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) {
        ggml_cpy_f32_q5_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) {
        ggml_cpy_f16_f16_cuda (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) {
        ggml_cpy_f16_f32_cuda (src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
    } else {
        GGML_ABORT("%s: unsupported type combination (%s to %s)\n", __func__,
                ggml_type_name(src0->type), ggml_type_name(src1->type));
    }
}

void ggml_cuda_dup(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
    const ggml_tensor * src0 = dst->src[0];
    ggml_cuda_cpy(ctx, src0, dst);
}

void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) {
    if (src0->type == src1->type && ggml_is_contiguous(src0) && ggml_is_contiguous(src1)) {
        return nullptr;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32) {
        return (void*) cpy_f32_f16<cpy_1_f32_f32>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F16) {
        return (void*) cpy_f32_f16<cpy_1_f32_f16>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q8_0) {
        return (void*) cpy_f32_q<cpy_blck_f32_q8_0, QK8_0>;
    } else if (src0->type == GGML_TYPE_Q8_0 && src1->type == GGML_TYPE_F32) {
        return (void*) cpy_q_f32<cpy_blck_q8_0_f32, QK8_0>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_0) {
        return (void*) cpy_f32_q<cpy_blck_f32_q4_0, QK4_0>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q4_1) {
        return (void*) cpy_f32_q<cpy_blck_f32_q4_1, QK4_1>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) {
        return (void*) cpy_f32_q<cpy_blck_f32_q5_0, QK5_0>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) {
        return (void*) cpy_f32_q<cpy_blck_f32_iq4_nl, QK4_NL>;
    } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) {
        return (void*) cpy_f32_q<cpy_blck_f32_q5_1, QK5_1>;
    } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) {
        return (void*) cpy_f32_f16<cpy_1_f32_f16>;
    } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) {
        return (void*) cpy_f32_f16<cpy_1_f16_f32>;
    } else {
        GGML_ABORT("%s: unsupported type combination (%s to %s)\n", __func__,
                ggml_type_name(src0->type), ggml_type_name(src1->type));
    }
}