tests : refactor test-save-load-state to accept token input#24073
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- Default prompt is now empty; when not provided, generate n_batch random tokens (useful for models without a tokenizer) - Tokenization happens once upfront; pass token vector to test functions - generate_tokens prints token IDs instead of decoded pieces - Use llama_model_get_vocab / llama_vocab_n_tokens API - Upgrade log level from LOG_TRC to LOG_INF for visibility Assisted-by: llama.cpp:local pi
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* origin/master: (57 commits) server : disable on-device spec checkpoints (ggml-org#24108) arg: fix double mtp downloads (ggml-org#24128) webui: [a11y] fix keyboard navigation issues in chat interface and sidebar (ggml-org#23132) Move duplicated imatrix code into single common imatrix-loader.cpp (ggml-org#22445) ui: Fixed packages (ggml-org#24119) ui: added single line reasoning preview (ggml-org#23601) return filter to save memory (ggml-org#24125) convert: Fix Gemma 4 Unified conversion (ggml-org#24118) ggml: vectorize ggml_vec_dot_q4_1_q8_1 with WASM SIMD128 (ggml-org#22209) server: avoid unnecessary checkpoint restore when new tokens are present (ggml-org#24110) agents: refactor, include more guidelines (ggml-org#24111) webui: fix tool selector toggle/counter, key tools by stable identity (ggml-org#24065) build : use umbrella Headers directory for XCFramework module map (ggml-org#23974) server : add header to tools/server/server-http.h (ggml-org#24089) cmake: skip cvector-generator and export-lora when CPU backend is disabled (ggml-org#24053) fix(mtmd): handle Gemma 4 audio projector embedding size (ggml-org#24091) readme : add status badges (ggml-org#24104) tests : refactor test-save-load-state to accept token input (ggml-org#24073) metal : reduce rset heartbeat from 500ms -> 5ms (ggml-org#24074) ggml-webgpu: FlashAttention refactor + standardize quantization support (ggml-org#23834) ...
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…#24073) * tests : refactor test-save-load-state to accept token input - Default prompt is now empty; when not provided, generate n_batch random tokens (useful for models without a tokenizer) - Tokenization happens once upfront; pass token vector to test functions - generate_tokens prints token IDs instead of decoded pieces - Use llama_model_get_vocab / llama_vocab_n_tokens API - Upgrade log level from LOG_TRC to LOG_INF for visibility Assisted-by: llama.cpp:local pi * cont : use llama_tokens alias (cherry picked from commit 65ef50a)
jimbothigpen
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Jun 6, 2026
…#24073) * tests : refactor test-save-load-state to accept token input - Default prompt is now empty; when not provided, generate n_batch random tokens (useful for models without a tokenizer) - Tokenization happens once upfront; pass token vector to test functions - generate_tokens prints token IDs instead of decoded pieces - Use llama_model_get_vocab / llama_vocab_n_tokens API - Upgrade log level from LOG_TRC to LOG_INF for visibility Assisted-by: llama.cpp:local pi * cont : use llama_tokens alias (cherry picked from commit 65ef50a)
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Overview
Refactor
test-save-load-state.cppto accept input as a token vector instead of a prompt string. This enables testing with models that lack a tokenizer.Key changes:
n_batchrandom tokensmain(); tokens are passed to all test functionsgenerate_tokens()prints token IDs instead of decoded text piecesAdditional information
The random token path is useful for model files that do not have a tokenizer, allowing the save/load state tests to run against any model.
Requirements