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Merged
merged 5 commits into from
Mar 22, 2025
Merged

ggml : fix quantized cpy op #12310

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fb73be1
ggml : fix quantized cpy op
ggerganov Mar 10, 2025
b5f5b07
tests : add cpy tests for all types
ggerganov Mar 10, 2025
ad62ba1
tests : add BF16 copy tests
ggerganov Mar 11, 2025
b3be71a
tests : fix loop for same-type copy
ggerganov Mar 11, 2025
d266584
tests : add option to permute the dst tensor
ggerganov Mar 11, 2025
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58 changes: 31 additions & 27 deletions ggml/src/ggml-cpu/ggml-cpu.c
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Original file line number Diff line number Diff line change
Expand Up @@ -3110,17 +3110,17 @@ static void ggml_compute_forward_dup_same_cont(
const int ith = params->ith; // thread index
const int nth = params->nth; // number of threads

// parallelize by elements
const int ne = ggml_nelements(dst);
const int dr = (ne + nth - 1) / nth;
const int ie0 = dr * ith;
const int ie1 = MIN(ie0 + dr, ne);
// parallelize by blocks
const int nk = ggml_nelements(src0)/ggml_blck_size(src0->type);
const int dr = (nk + nth - 1) / nth;
const int k0 = dr * ith;
const int k1 = MIN(k0 + dr, nk);

if (ie0 < ie1) {
if (k0 < k1) {
memcpy(
((char *) dst->data + ie0*nb0),
((char *) src0->data + ie0*nb0),
(ie1 - ie0) * nb0);
((char *) dst->data + k0*nb0),
((char *) src0->data + k0*nb0),
(k1 - k0) * nb0);
}
}

Expand Down Expand Up @@ -4055,7 +4055,6 @@ static void ggml_compute_forward_dup_f32(
static void ggml_compute_forward_dup_bytes(
const struct ggml_compute_params * params,
struct ggml_tensor * dst) {

const struct ggml_tensor * src0 = dst->src[0];

GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0));
Expand All @@ -4069,10 +4068,10 @@ static void ggml_compute_forward_dup_bytes(
}

const size_t type_size = ggml_type_size(src0->type);

const int ith = params->ith; // thread index
const int nth = params->nth; // number of threads


// parallelize by rows
const int nr = ne01;
// number of rows per thread
Expand All @@ -4082,10 +4081,10 @@ static void ggml_compute_forward_dup_bytes(
const int ir1 = MIN(ir0 + dr, nr);

if (src0->type == dst->type &&
ne00 == ne0 &&
ggml_are_same_shape(src0, dst) &&
nb00 == type_size && nb0 == type_size) {
// copy by rows
const size_t rs = ne00 * type_size;
const size_t rs = ggml_row_size(src0->type, ne00);
for (int64_t i03 = 0; i03 < ne03; i03++) {
for (int64_t i02 = 0; i02 < ne02; i02++) {
for (int64_t i01 = ir0; i01 < ir1; i01++) {
Expand Down Expand Up @@ -4140,17 +4139,20 @@ static void ggml_compute_forward_dup_bytes(
}

// dst counters

int64_t i10 = 0;
int64_t k10 = 0;
int64_t i11 = 0;
int64_t i12 = 0;
int64_t i13 = 0;

// number of blocks in a row
const int64_t nk00 = ne00 / ggml_blck_size(src0->type);
const int64_t nk0 = ne0 / ggml_blck_size(dst->type);

for (int64_t i03 = 0; i03 < ne03; i03++) {
for (int64_t i02 = 0; i02 < ne02; i02++) {
i10 += ne00 * ir0;
while (i10 >= ne0) {
i10 -= ne0;
k10 += nk00 * ir0;
while (k10 >= nk0) {
k10 -= nk0;
if (++i11 == ne1) {
i11 = 0;
if (++i12 == ne2) {
Expand All @@ -4162,14 +4164,14 @@ static void ggml_compute_forward_dup_bytes(
}
}
for (int64_t i01 = ir0; i01 < ir1; i01++) {
for (int64_t i00 = 0; i00 < ne00; i00++) {
const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);
for (int64_t k00 = 0; k00 < nk00; k00++) {
const char * src0_ptr = ((char *) src0->data + k00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
char * dst_ptr = ((char *) dst->data + k10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);

memcpy(dst_ptr, src0_ptr, type_size);

if (++i10 == ne0) {
i10 = 0;
if (++k10 == nk0) {
k10 = 0;
if (++i11 == ne1) {
i11 = 0;
if (++i12 == ne2) {
Expand All @@ -4182,9 +4184,9 @@ static void ggml_compute_forward_dup_bytes(
}
}
}
i10 += ne00 * (ne01 - ir1);
while (i10 >= ne0) {
i10 -= ne0;
k10 += nk00 * (ne01 - ir1);
while (k10 >= nk0) {
k10 -= nk0;
if (++i11 == ne1) {
i11 = 0;
if (++i12 == ne2) {
Expand Down Expand Up @@ -14067,7 +14069,9 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
}

// extra_buffer op?
if (ggml_cpu_extra_compute_forward(params, tensor)) return;
if (ggml_cpu_extra_compute_forward(params, tensor)) {
return;
}

switch (tensor->op) {
case GGML_OP_DUP:
Expand Down
40 changes: 30 additions & 10 deletions tests/test-backend-ops.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1459,11 +1459,13 @@ struct test_cpy : public test_case {
const ggml_type type_src;
const ggml_type type_dst;
const std::array<int64_t, 4> ne;
const std::array<int64_t, 4> permute;
const std::array<int64_t, 4> permute_src;
const std::array<int64_t, 4> permute_dst;
bool _src_use_permute;
bool _dst_use_permute;

std::string vars() override {
return VARS_TO_STR4(type_src, type_dst, ne, permute);
return VARS_TO_STR5(type_src, type_dst, ne, permute_src, permute_dst);
}

double max_nmse_err() override {
Expand All @@ -1476,23 +1478,30 @@ struct test_cpy : public test_case {

test_cpy(ggml_type type_src = GGML_TYPE_F32, ggml_type type_dst = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 10, 10, 1},
std::array<int64_t, 4> permute = {0, 0, 0, 0})
: type_src(type_src), type_dst(type_dst), ne(ne), permute(permute),
_src_use_permute(permute[0] + permute[1] + permute[2] + permute[3] > 0) {}
std::array<int64_t, 4> permute_src = {0, 0, 0, 0},
std::array<int64_t, 4> permute_dst = {0, 0, 0, 0})
: type_src(type_src), type_dst(type_dst), ne(ne), permute_src(permute_src), permute_dst(permute_dst),
_src_use_permute(permute_src[0] + permute_src[1] + permute_src[2] + permute_src[3] > 0),
_dst_use_permute(permute_dst[0] + permute_dst[1] + permute_dst[2] + permute_dst[3] > 0) {}

ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * src = ggml_new_tensor(ctx, type_src, 4, ne.data());
ggml_set_param(ctx, src);
ggml_set_name(src, "src");

if (_src_use_permute) {
src = ggml_permute(ctx, src, permute[0], permute[1], permute[2], permute[3]);
src = ggml_permute(ctx, src, permute_src[0], permute_src[1], permute_src[2], permute_src[3]);
ggml_set_name(src, "src_permuted");
}

ggml_tensor* dst = ggml_new_tensor(ctx, type_dst, 4, src->ne);
ggml_tensor * dst = ggml_new_tensor(ctx, type_dst, 4, src->ne);
ggml_set_name(dst, "dst");

if (_dst_use_permute) {
dst = ggml_permute(ctx, dst, permute_dst[0], permute_dst[1], permute_dst[2], permute_dst[3]);
ggml_set_name(dst, "dst_permuted");
}

ggml_tensor * out = ggml_cpy(ctx, src, dst);
ggml_set_name(out, "out");

Expand Down Expand Up @@ -3929,14 +3938,25 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
test_cases.emplace_back(new test_set(GGML_TYPE_I32, GGML_TYPE_I32, {6, 5, 4, 3}, dim));
}

for (ggml_type type_src : {GGML_TYPE_F16, GGML_TYPE_F32}) {
// same-type copy
for (ggml_type type : all_types) {
const auto nk = ggml_blck_size(type);

for (int k = 1; k < 4; ++k) {
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {0, 3, 1, 2}, {0, 2, 1, 3}));
}
}

for (ggml_type type_src : {GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_F32}) {
for (ggml_type type_dst : all_types) {
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 4, 4, 4}));
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {0, 2, 1, 3})); // cpy by rows
}
}
for (ggml_type type_dst : {GGML_TYPE_F32}) {
for (ggml_type type_src : all_types) {
for (ggml_type type_src : all_types) {
for (ggml_type type_dst : {GGML_TYPE_F32}) {
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 4, 4, 4}));
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {0, 2, 1, 3})); // cpy by rows
}
Expand Down
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