diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index da66ed856..3106887cd 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -2200,8 +2200,16 @@ struct test_rope : public test_case { ggml_set_param(ctx, a); ggml_set_name(a, "a"); } - - ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne_a[2]); + + const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE; + const bool is_vision = mode == GGML_ROPE_TYPE_VISION; + + ggml_tensor * pos; + if (is_mrope || is_vision) { + pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne_a[2] * 4); + } else { + pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne_a[2]); + } ggml_set_name(pos, "pos"); ggml_tensor * freq = nullptr; @@ -2210,7 +2218,20 @@ struct test_rope : public test_case { ggml_set_name(freq, "freq"); } - ggml_tensor * out = ggml_rope_ext(ctx, a, pos, freq, n_dims, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f); + ggml_tensor * out; + if (is_mrope) { + if (is_vision) { + GGML_ASSERT(n_dims/4 > 0); + int rope_sections[4] = {n_dims/4, n_dims/4, 0, 0}; // Vision-RoPE only use first two dimension for image (x, y) coordinate + out = ggml_rope_multi(ctx, a, pos, freq, n_dims/2, rope_sections, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f); + } else { + GGML_ASSERT(n_dims/3 > 0); + int rope_sections[4] = {n_dims/3, n_dims/3, n_dims/3, 0}; + out = ggml_rope_multi(ctx, a, pos, freq, n_dims, rope_sections, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f); + } + } else { + out = ggml_rope_ext(ctx, a, pos, freq, n_dims, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f); + } ggml_set_name(out, "out"); return out; @@ -2220,11 +2241,12 @@ struct test_rope : public test_case { for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) { if (t->type == GGML_TYPE_I32) { // pos - std::vector data(ne_a[2]); - for (int i = 0; i < ne_a[2]; i++) { + const int num_pos_ids = (mode & GGML_ROPE_TYPE_MROPE) ? ne_a[2] * 4 : ne_a[2]; + std::vector data(num_pos_ids); + for (int i = 0; i < num_pos_ids; i++) { data[i] = rand() % n_ctx; } - ggml_backend_tensor_set(t, data.data(), 0, ne_a[2] * sizeof(int)); + ggml_backend_tensor_set(t, data.data(), 0, num_pos_ids * sizeof(int)); } else { if (t->ne[0] == n_dims/2) { // frequency factors in the range [0.9f, 1.1f] @@ -3765,6 +3787,12 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_rope(type, { 80, 32, 2, 1}, 20, 2, 512, fs, ef, af, ff, v)); // neox (stablelm) test_cases.emplace_back(new test_rope(type, { 80, 32, 2, 1}, 32, 2, 512, fs, ef, af, ff, v)); // neox (phi-2) } + + if (all) { + test_cases.emplace_back(new test_rope(type, {128, 12, 2, 1}, 128, GGML_ROPE_TYPE_MROPE, 512, fs, ef, af, ff, v)); // rope_multi,m-rope (qwen2vl 2B) + test_cases.emplace_back(new test_rope(type, {128, 28, 2, 1}, 128, GGML_ROPE_TYPE_MROPE, 512, fs, ef, af, ff, v)); // rope_multi,m-rope (qwen2vl 7B) + test_cases.emplace_back(new test_rope(type, { 80, 16, 2, 1}, 80, GGML_ROPE_TYPE_VISION, 512, fs, ef, af, ff, v)); // rope_multi,m-rope (qwen2vl ViT) + } test_cases.emplace_back(new test_rope(type, { 64, 128, 2, 1}, 64, 2, 512, fs, ef, af, ff, v)); // neox (falcon 40B) }