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tests : extend bin bcast for permuted src1

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This commit is contained in:
Georgi Gerganov
2026-02-10 12:23:07 +02:00
parent ff77be289e
commit 0b0bfb20f4
2 changed files with 39 additions and 27 deletions
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8
ggml/src/ggml-cpu/binary-ops.cpp
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@@ -59,11 +59,7 @@ static void apply_binary_op(const ggml_compute_params * params, ggml_tensor * ds
GGML_ASSERT(nb00 == sizeof(src0_t));
const auto [ir0, ir1] = get_thread_range(params, src0);
const bool is_src1_contiguous = (nb10 == sizeof(src1_t));
if (!is_src1_contiguous) { // broadcast not implemented yet for non-contiguous
GGML_ASSERT(ggml_are_same_shape(src0, src1));
}
const bool is_src1_contiguous_rows = ggml_is_contiguous_rows(src1);
#ifdef GGML_USE_ACCELERATE
vDSP_fn_t vDSP_op = nullptr;
@@ -94,7 +90,7 @@ static void apply_binary_op(const ggml_compute_params * params, ggml_tensor * ds
const src0_t * src0_ptr = (const src0_t *) ((const char *) src0->data + i03*nb03 + i02*nb02 + i01*nb01);
const src1_t * src1_ptr = (const src1_t *) ((const char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11);
if (is_src1_contiguous) {
if (is_src1_contiguous_rows) {
// src1 is broadcastable across src0 and dst in i1, i2, i3
const int64_t nr0 = ne00 / ne10;

58
tests/test-backend-ops.cpp
View File

@@ -2964,11 +2964,12 @@ struct test_bin_bcast : public test_case {
const std::array<int64_t, 4> ne;
const std::array<int, 4> nr;
int nf; // number of fused ops, nf == 1 -> single op (no fusion)
bool perm1; // permute src1?
bool run_whole_graph() override { return nf > 1; }
bool run_whole_graph() override { return nf > 1 || perm1; }
std::string vars() override {
return VARS_TO_STR4(type, ne, nr, nf);
return VARS_TO_STR5(type, ne, nr, nf, perm1);
}
size_t op_size(ggml_tensor * t) override {
@@ -2978,8 +2979,9 @@ struct test_bin_bcast : public test_case {
test_bin_bcast(op_t op, ggml_type type = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 10, 1, 1},
std::array<int, 4> nr = {1, 2, 1, 1},
int nf = 1)
: op(op), type(type), ne(ne), nr(nr), nf(nf) {}
int nf = 1,
bool perm1 = false)
: op(op), type(type), ne(ne), nr(nr), nf(nf), perm1(perm1) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
GGML_ASSERT(nf <= 16);
@@ -2989,12 +2991,24 @@ struct test_bin_bcast : public test_case {
ggml_tensor * b[16];
for (int i = 0; i < nf; ++i) {
b[i] = ggml_new_tensor(ctx, type, 4, ne.data());
if (perm1) {
const int p[4] = { 1, 2, 0, 3 }; // hardcoded for now
int64_t ne_b[4];
ne_b[0] = ne[p[0]];
ne_b[1] = ne[p[1]];
ne_b[2] = ne[p[2]];
ne_b[3] = ne[p[3]];
b[i] = ggml_new_tensor_4d(ctx, type, ne_b[0], ne_b[1], ne_b[2], ne_b[3]);
b[i] = ggml_permute(ctx, b[i], p[0], p[1], p[2], p[3]);
} else {
b[i] = ggml_new_tensor(ctx, type, 4, ne.data());
}
ggml_set_name(b[i], (std::string("b") + std::to_string(i)).c_str());
}
// The backward pass supports broadcasting only for GGML_ADD:
const bool grad_supported = op == ggml_add && ggml_are_same_shape(a, b[0]) && nf == 1;
const bool grad_supported = op == ggml_add && ggml_are_same_shape(a, b[0]) && nf == 1 && !perm1;
if (grad_supported) {
ggml_set_param(a);
ggml_set_param(b[0]);
@@ -7477,25 +7491,27 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
}
}
auto add_test_bin_bcast = [&](ggml_type type, std::array<int64_t, 4> ne, std::array<int, 4> nr) {
auto add_test_bin_bcast = [&](ggml_type type, std::array<int64_t, 4> ne, std::array<int, 4> nr, bool perm1 = false) {
for (auto op : {ggml_add, ggml_sub, ggml_mul, ggml_div}) {
test_cases.emplace_back(new test_bin_bcast(op, type, ne, nr));
test_cases.emplace_back(new test_bin_bcast(op, type, ne, nr, 1, perm1));
}
};
for (ggml_type type : {GGML_TYPE_F16, GGML_TYPE_F32}) {
add_test_bin_bcast(type, {1, 1, 8, 1}, {1, 1, 1, 1});
add_test_bin_bcast(type, {1, 1, 1, 1}, {32, 1, 1, 1});
add_test_bin_bcast(type, {1, 1, 320, 320}, {1, 1, 1, 1});
add_test_bin_bcast(type, {10, 5, 1, 1}, {1, 1, 1, 1});
add_test_bin_bcast(type, {10, 5, 4, 1}, {1, 1, 1, 1});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 1, 1});
add_test_bin_bcast(type, {10, 5, 4, 3}, {2, 1, 1, 1});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 2, 1, 1});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 2, 1});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 1, 2});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 2, 2});
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 2, 2, 2});
add_test_bin_bcast(type, {10, 5, 4, 3}, {2, 2, 2, 2});
for (bool perm1 : {false, true}) {
add_test_bin_bcast(type, {1, 1, 8, 1}, {1, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {1, 1, 1, 1}, {32, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {1, 1, 320, 320}, {1, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 1, 1}, {1, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 1}, {1, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {2, 1, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 2, 1, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 2, 1}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 1, 2}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 1, 2, 2}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {1, 2, 2, 2}, perm1);
add_test_bin_bcast(type, {10, 5, 4, 3}, {2, 2, 2, 2}, perm1);
}
// test case for k_bin_bcast_unravel in CUDA backend
add_test_bin_bcast(type, {1, 1, 65536, 1}, {256, 1, 1, 1});