| 644 | } |
| 645 | |
| 646 | static bool handcrafted_check_tensor_data(const gguf_context * gguf_ctx, const unsigned int seed, FILE * file) { |
| 647 | if (!gguf_ctx) { |
| 648 | return false; |
| 649 | } |
| 650 | |
| 651 | std::mt19937 rng(seed); |
| 652 | |
| 653 | std::vector<tensor_config_t> tensor_configs = get_tensor_configs(rng); |
| 654 | |
| 655 | bool ok = true; |
| 656 | |
| 657 | for (int i = 0; i < int(tensor_configs.size()); ++i) { |
| 658 | const ggml_type type = tensor_configs[i].first; |
| 659 | const std::array<int64_t, GGML_MAX_DIMS> shape = tensor_configs[i].second; |
| 660 | |
| 661 | int64_t ne = shape[0]; |
| 662 | for (size_t j = 1; j < GGML_MAX_DIMS; ++j) { |
| 663 | ne *= shape[j]; |
| 664 | } |
| 665 | const size_t size = ggml_row_size(type, ne); |
| 666 | |
| 667 | const std::string name = "my_tensor_" + std::to_string(i); |
| 668 | const size_t offset = gguf_get_tensor_offset(gguf_ctx, gguf_find_tensor(gguf_ctx, name.c_str())); |
| 669 | |
| 670 | std::vector<uint8_t> data(size); |
| 671 | GGML_ASSERT(fseek(file, gguf_get_data_offset(gguf_ctx) + offset, SEEK_SET) == 0); |
| 672 | GGML_ASSERT(fread(data.data(), 1, data.size(), file) == data.size()); |
| 673 | |
| 674 | for (size_t j = 0; j < size; ++j) { |
| 675 | const uint8_t expected_byte = (j + offset) % 256; |
| 676 | if (data[j] != expected_byte) { |
| 677 | ok = false; |
| 678 | } |
| 679 | } |
| 680 | } |
| 681 | |
| 682 | return ok; |
| 683 | } |
| 684 | |
| 685 | static std::pair<int, int> test_handcrafted_file(const unsigned int seed) { |
| 686 | int npass = 0; |
no test coverage detected