mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-07-21 10:15:53 +00:00
tokenize : align usage by using common args (#25516)
Migrate the tokenize tool to common_params_parse, replacing its hand-rolled argv parsing, Windows UTF-8 handling and file reading with the shared common helpers. Expose the model-sourcing flags (-m, -mu, -dr, -hf, -hff, --offline, HF_TOKEN) to LLAMA_EXAMPLE_TOKENIZE, and register --ids, --stdin, --no-bos, --no-parse-special and --show-count as common args. parse_special defaults to true for TOKENIZE to preserve the old behavior. Errors now go through LOG_ERR instead of fprintf(stderr). Signed-off-by: Adrien Gallouët <angt@huggingface.co>
This commit is contained in:
+44
-7
@@ -1179,6 +1179,8 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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params.sampling.temp = 0.2; // lower temp by default for better quality
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} else if (ex == LLAMA_EXAMPLE_SERVER) {
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params.n_parallel = -1; // auto by default
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} else if (ex == LLAMA_EXAMPLE_TOKENIZE) {
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params.parse_special = true; // parse special tokens by default, like the old tokenize tool
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}
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params.use_color = tty_can_use_colors();
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@@ -2746,14 +2748,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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params.model.path = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_MODEL"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_MODEL"));
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add_opt(common_arg(
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{"-mu", "--model-url"}, "MODEL_URL",
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"model download url (default: unused)",
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[](common_params & params, const std::string & value) {
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params.model.url = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_MODEL_URL"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_MODEL_URL"));
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add_opt(common_arg(
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{ "-dr", "--docker-repo" }, "[<repo>/]<model>[:quant]",
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"Docker Hub model repository. repo is optional, default to ai/. quant is optional, default to :latest.\n"
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@@ -2762,7 +2764,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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params.model.docker_repo = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_DOCKER_REPO"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_DOCKER_REPO"));
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add_opt(common_arg(
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{"-hf", "-hfr", "--hf-repo"}, "<user>/<model>[:quant]",
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"Hugging Face model repository; quant is optional, case-insensitive, default to Q4_K_M, or falls back to the first file in the repo if Q4_K_M doesn't exist.\n"
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@@ -2772,14 +2774,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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params.model.hf_repo = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_HF_REPO"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_HF_REPO"));
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add_opt(common_arg(
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{"-hff", "--hf-file"}, "FILE",
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"Hugging Face model file. If specified, it will override the quant in --hf-repo (default: unused)",
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[](common_params & params, const std::string & value) {
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params.model.hf_file = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_HF_FILE"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_HF_FILE"));
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add_opt(common_arg(
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{"-hfv", "-hfrv", "--hf-repo-v"}, "<user>/<model>[:quant]",
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"Hugging Face model repository for the vocoder model (default: unused)",
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@@ -2800,7 +2802,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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params.hf_token = value;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("HF_TOKEN"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("HF_TOKEN"));
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add_opt(common_arg(
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{"--mtp"},
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"also download the multi-token prediction (MTP) head, if available (default: unused)",
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@@ -2916,6 +2918,41 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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params.parse_special = true;
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}
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).set_examples({LLAMA_EXAMPLE_IMATRIX}));
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add_opt(common_arg(
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{"--ids"},
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string_format("only print the token IDs, in a Python-parseable list form like [1, 2, 3] (default: %s)", params.tokenize_ids ? "true" : "false"),
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[](common_params & params) {
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params.tokenize_ids = true;
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}
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).set_examples({LLAMA_EXAMPLE_TOKENIZE}));
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add_opt(common_arg(
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{"--stdin"},
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string_format("read the prompt from stdin (mutually exclusive with -f/--file and -p/--prompt) (default: %s)", params.tokenize_stdin ? "true" : "false"),
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[](common_params & params) {
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params.tokenize_stdin = true;
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}
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).set_examples({LLAMA_EXAMPLE_TOKENIZE}));
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add_opt(common_arg(
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{"--no-bos"},
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string_format("do not add a BOS token to the prompt, even if the model normally uses one (default: %s)", params.tokenize_no_bos ? "true" : "false"),
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[](common_params & params) {
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params.tokenize_no_bos = true;
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}
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).set_examples({LLAMA_EXAMPLE_TOKENIZE}));
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add_opt(common_arg(
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{"--no-parse-special"},
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string_format("do not parse special tokens (chat, tool, etc) (default: %s)", !params.parse_special ? "true" : "false"),
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[](common_params & params) {
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params.parse_special = false;
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}
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).set_examples({LLAMA_EXAMPLE_TOKENIZE}));
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add_opt(common_arg(
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{"--show-count"},
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string_format("print the total number of tokens (default: %s)", params.tokenize_show_count ? "true" : "false"),
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[](common_params & params) {
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params.tokenize_show_count = true;
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}
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).set_examples({LLAMA_EXAMPLE_TOKENIZE}));
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add_opt(common_arg(
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{"-pps"},
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string_format("is the prompt shared across parallel sequences (default: %s)", params.is_pp_shared ? "true" : "false"),
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@@ -3506,7 +3543,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params) {
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params.offline = true;
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}
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_OFFLINE"));
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).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_OFFLINE"));
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add_opt(common_arg(
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{"-lv", "--verbosity", "--log-verbosity"}, "N",
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string_format("Set the verbosity threshold. Messages with a higher verbosity will be ignored. Values:\n"
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@@ -105,6 +105,7 @@ enum llama_example {
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LLAMA_EXAMPLE_RESULTS,
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LLAMA_EXAMPLE_EXPORT_GRAPH_OPS,
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LLAMA_EXAMPLE_DOWNLOAD,
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LLAMA_EXAMPLE_TOKENIZE,
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LLAMA_EXAMPLE_COUNT,
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};
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@@ -716,6 +717,12 @@ struct common_params {
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// batched-bench params
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bool batched_bench_output_jsonl = false;
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// tokenize params
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bool tokenize_ids = false; // if true, only print the token IDs
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bool tokenize_stdin = false; // if true, read the prompt from stdin
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bool tokenize_no_bos = false; // if true, do not add the BOS token
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bool tokenize_show_count = false; // if true, print the total token count
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// common params
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std::string out_file; // output filename for all example programs
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// optional callback for model loading progress and cancellation:
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