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Merge branch 'upstream' into concedo_experimental
# Conflicts: # scripts/sync_vendor.py # src/llama-model-loader.cpp # tests/test-backend-ops.cpp # tests/test-chat-auto-parser.cpp # tests/test-chat.cpp # tools/cli/cli.cpp # tools/server/README.md
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+14
-5
@@ -955,10 +955,11 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
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LOG_INF("%s: - block_size=%d, mask_token_id=%d, n_extract=%u\n", __func__, block_size, mask_token_id, target_layer_ids_n);
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// DFlash input is [id_last, <mask> * (block_size-1)], so it can draft at most block_size-1 tokens per step
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if (this->params.n_max > block_size - 1) {
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LOG_WRN("%s: requested draft size %d exceeds the trained DFlash block size %d -- clamping to %d draft tokens per step\n",
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__func__, this->params.n_max, block_size - 1, block_size - 1);
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this->params.n_max = block_size - 1;
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if (this->params.n_max > block_size - 1 || this->params.n_min > block_size - 1) {
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LOG_WRN("%s: requested draft size (n_max=%d, n_min=%d) exceeds the trained DFlash block size %d -- clamping to %d\n",
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__func__, this->params.n_max, this->params.n_min, block_size, block_size - 1);
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this->params.n_max = std::min(this->params.n_max, block_size - 1);
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this->params.n_min = std::min(this->params.n_min, block_size - 1);
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}
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batch = llama_batch_init(llama_n_batch(ctx_dft), 0, n_seq);
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@@ -968,7 +969,7 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
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for (auto & s : smpls) {
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common_params_sampling sparams;
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sparams.no_perf = false;
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sparams.top_k = 1;
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sparams.top_k = 10;
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sparams.samplers = { COMMON_SAMPLER_TYPE_TOP_K };
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s.reset(common_sampler_init(model_dft, sparams));
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}
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@@ -1173,10 +1174,18 @@ struct common_speculative_impl_draft_dflash : public common_speculative_impl {
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const llama_token id = cur_p->data[0].id;
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if (cur_p->data[0].p < params.p_min) {
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break;
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}
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common_sampler_accept(smpl, id, true);
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result.push_back(id);
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}
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if (result.size() < (size_t) params.n_min) {
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result.clear();
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}
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}
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}
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