vbatts/llama.cpp
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revise test code

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This commit is contained in:
Johannes Gäßler 2024-10-23 23:53:58 +02:00
parent b87dc5a44f
commit 4004bb7015
1 changed files with 28 additions and 24 deletions
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52
tests/test-backend-ops.cpp
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@ -1676,33 +1676,37 @@ struct test_mul_mat : public test_case {
ggml_tensor * build_graph(ggml_context * ctx) override {
// C^T = A * B^T: (k, m) * (k, n) => (m, n)
ggml_tensor * a = ggml_new_tensor_4d(ctx, type_a, k, m, bs[0] , bs[1]);
ggml_tensor * b = ggml_new_tensor_4d(ctx, type_b, k, n, bs[0]*nr[0], bs[1]*nr[1]);
ggml_set_param(ctx, a);
ggml_set_param(ctx, b);
ggml_set_name(a, "a");
ggml_set_name(b, "b");
ggml_tensor * a;
ggml_tensor * b;
// If the permutation is not {0, 1, 2, 3}, replace a and b with views that have the same data in a different order.
// This test only works correctly if exactly 2 indices != 0 are swapped.
if (per[0] != 0 || per[1] != 1 || per[2] != 2 || per[3] != 3) {
GGML_ASSERT(per[0] == 0);
const size_t rsa = ggml_row_size(a->type, a->ne[0]);
const size_t rsb = ggml_row_size(b->type, b->ne[0]);
size_t nba[GGML_MAX_DIMS] = {ggml_type_size(a->type), rsa, rsa, rsa};
size_t nbb[GGML_MAX_DIMS] = {ggml_type_size(b->type), rsb, rsb, rsb};
for (int64_t i = 1; i < GGML_MAX_DIMS; ++i) {
for (int64_t j = 1; j < per[i]; ++j) {
nba[i] *= a->ne[per[j]];
nbb[i] *= b->ne[per[j]];
}
}
a = ggml_view_4d(ctx, a, a->ne[0], a->ne[1], a->ne[2], a->ne[3], nba[1], nba[2], nba[3], /*offset =*/ 0);
b = ggml_view_4d(ctx, b, b->ne[0], b->ne[1], b->ne[2], b->ne[3], nbb[1], nbb[2], nbb[3], /*offset =*/ 0);
GGML_ASSERT(ggml_nbytes(a) == ggml_nbytes(a->src[0]));
GGML_ASSERT(ggml_nbytes(b) == ggml_nbytes(b->src[0]));
const int npermuted = (per[0] != 0) + (per[1] != 1) + (per[2] != 2) + (per[3] != 3);
if (npermuted > 0) {
GGML_ASSERT(npermuted == 2);
GGML_ASSERT(!ggml_is_quantized(type_a) || per[0] == 0);
GGML_ASSERT(!ggml_is_quantized(type_b) || per[0] == 0);
// Create tensors with the permuted dimensions, then permute them back to the dimensions given by m,n,k.
const int64_t ne_a[4] = {k, m, bs[0], bs[1]};
const int64_t ne_b[4] = {k, n, bs[0]*nr[0], bs[1]*nr[1]};
a = ggml_new_tensor_4d(ctx, type_a, ne_a[per[0]], ne_a[per[1]], ne_a[per[2]], ne_a[per[3]]);
b = ggml_new_tensor_4d(ctx, type_b, ne_b[per[0]], ne_b[per[1]], ne_b[per[2]], ne_b[per[3]]);
ggml_set_param(ctx, a);
ggml_set_param(ctx, b);
ggml_set_name(a, "a");
ggml_set_name(b, "b");
a = ggml_permute(ctx, a, per[0], per[1], per[2], per[3]);
b = ggml_permute(ctx, b, per[0], per[1], per[2], per[3]);
ggml_set_name(a, "a_permuted");
ggml_set_name(b, "b_permuted");
} else {
a = ggml_new_tensor_4d(ctx, type_a, k, m, bs[0], bs[1]);
b = ggml_new_tensor_4d(ctx, type_b, k, n, bs[0]*nr[0], bs[1]*nr[1]);
ggml_set_param(ctx, a);
ggml_set_param(ctx, b);
ggml_set_name(a, "a");
ggml_set_name(b, "b");
}
ggml_tensor * out = ggml_mul_mat(ctx, a, b);