From 828e5d2fcd6f0027296a34be1cce6908e8de099b Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Sun, 22 Jun 2025 18:45:30 +0300 Subject: [PATCH] tests : add ggml_set_rows --- tests/test-backend-ops.cpp | 81 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 81 insertions(+) diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 7be7f2205f..f5cd5b695b 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -1213,6 +1213,78 @@ struct test_get_rows_back : public test_case { } }; +// GGML_OP_SET_ROWS +struct test_set_rows : public test_case { + const ggml_type type; + const int n; // cols + const int m; // rows + const int r; // rows to set + const int b0; // batch size + const int b1; // batch size + const int bs; // batch size src (for testing broadcast) + const bool v; // view (non-contiguous src1) + + std::string vars() override { + return VARS_TO_STR7(type, n, m, r, b0, bs, v); + } + + test_set_rows(ggml_type type = GGML_TYPE_F32, int n = 10, int m = 5, int r = 3, int b = 1, int bs = 1, bool v = false) + : type(type), n(n), m(m), r(r), b0(b), b1(3), bs(bs), v(v) { + GGML_ASSERT(b0 % bs == 0 && "b0 must be a multiple of bs"); + GGML_ASSERT(r <= m && "r must be less than or equal to m"); + } + + ggml_tensor * build_graph(ggml_context * ctx) override { + ggml_tensor * dst = ggml_new_tensor_4d(ctx, type, n, m, b0, b1); + ggml_set_name(dst, "dst"); + + ggml_tensor * src = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, n, r, b0, b1); + ggml_set_name(src, "src"); + + ggml_tensor * row_idxs = ggml_new_tensor_3d(ctx, GGML_TYPE_I64, r, bs, b1); + ggml_set_name(row_idxs, "row_idxs"); + + if (v) { + src = ggml_view_4d(ctx, src, n, r/2, b0, b1, src->nb[1], src->nb[2], src->nb[3], 0); + row_idxs = ggml_view_3d(ctx, row_idxs, r/2, bs, b1, row_idxs->nb[1], row_idxs->nb[2], 0); + ggml_set_name(row_idxs, "view_of_rows"); + } + + ggml_tensor * out = ggml_set_rows(ctx, dst, src, row_idxs); + ggml_set_name(out, "out"); + + return out; + } + + void initialize_tensors(ggml_context * ctx) override { + std::random_device rd; + std::default_random_engine rng(rd()); + for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) { + if (t->type == GGML_TYPE_I64) { + if (ggml_is_view_op(t->op)) { + continue; + } + + for (int i2 = 0; i2 < t->ne[2]; i2++) { + for (int i1 = 0; i1 < t->ne[1]; i1++) { + std::vector data(m); + for (int i = 0; i < m; i++) { + data[i] = i; + } + std::shuffle(data.begin(), data.end(), rng); + data.resize(t->ne[0]); + + const size_t offs = i1*t->nb[1] + i2*t->nb[2]; + ggml_backend_tensor_set(t, data.data(), offs, t->ne[0]*sizeof(int64_t)); + } + } + } else { + init_tensor_uniform(t); + } + } + } +}; + // GGML_OP_ARGMAX struct test_argmax : public test_case { const ggml_type type; @@ -3984,6 +4056,15 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_get_rows_back(GGML_TYPE_I32, 256, 5, 4, 1, v)); } + test_cases.emplace_back(new test_set_rows(GGML_TYPE_F32, 1, 8, 2, 1, 1, false)); + for (ggml_type type : all_types) { + for (int b : {1, 7}) { + for (bool v : {false, true}) { + test_cases.emplace_back(new test_set_rows(type, 256, 5, 4, b, 1, v)); + } + } + } + for (ggml_type type_input : {GGML_TYPE_F32}) { for (ggml_op_pool pool_type : {GGML_OP_POOL_AVG, GGML_OP_POOL_MAX}) { for (int k0 : {1, 3}) {