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server: stop generation at n_ctx_train
if n_predict
is not set (#6638)
* server: cap n_predict if not set to n_ctx_train * server: fix infinite loop * server: infinite loop, move in process_token server: infinite loop: set stop limit to true * minor: spaces * minor: spaces * server: include prompt tokens in the EOS limit
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@ -1207,6 +1207,27 @@ struct server_context {
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LOG_VERBOSE("eos token found", {});
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}
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auto n_ctx_train = llama_n_ctx_train(model);
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if (slot.params.n_predict < 1 && slot.ga_n == 1
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&& slot.n_prompt_tokens + slot.n_decoded >= n_ctx_train) {
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LOG_WARNING("n_predict is not set and self-context extend is disabled."
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" Limiting generated tokens to n_ctx_train to avoid EOS-less generation infinite loop", {
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{ "id_slot", slot.id },
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{ "params.n_predict", slot.params.n_predict },
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{ "slot.n_prompt_tokens", slot.n_prompt_tokens },
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{ "slot.n_decoded", slot.n_decoded },
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{ "slot.n_predict", slot.n_predict },
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{ "n_slots", params.n_parallel },
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{ "slot.n_ctx", slot.n_ctx },
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{ "n_ctx", n_ctx },
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{ "n_ctx_train", n_ctx_train },
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{ "ga_n", slot.ga_n },
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});
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slot.truncated = true;
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slot.stopped_limit = true;
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slot.has_next_token = false; // stop prediction
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}
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LOG_VERBOSE("next token", {
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{"id_slot", slot.id},
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{"id_task", slot.id_task},
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@ -2141,7 +2162,7 @@ struct server_context {
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});
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// process the created batch of tokens
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for (int32_t i = 0; i < (int32_t) batch.n_tokens; i += n_batch) {
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for (int32_t i = 0; i < batch.n_tokens; i += n_batch) {
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const int32_t n_tokens = std::min(n_batch, batch.n_tokens - i);
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for (auto & slot : slots) {
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