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ggml-opencl, llama: using reserve() if count already known (#7272)
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@ -1,4 +1,4 @@
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#include "ggml.h"
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#include "ggml.h"
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#include "ggml-opencl.h"
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#include "ggml-backend-impl.h"
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@ -1835,7 +1835,10 @@ static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor *
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CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, &offset, &global, local > 0 ? &local : NULL, events.size(), !events.empty() ? events.data() : NULL, NULL));
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}
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for (int64_t i12 = i02 * r2, e12 = i12 + r2; i12 < e12; i12++) {
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int64_t i12 = i02 * r2;
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int64_t e12 = i12 + r2;
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events.reserve(e12 - i12);
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for (; i12 < e12; i12++) {
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if (mul_mat_vec) { // specialized dequantize_mul_mat_vec kernel
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// copy src1 to device
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events.emplace_back();
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@ -16162,6 +16162,7 @@ static bool llama_control_vector_init(struct llama_control_vector & cvec, const
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}
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// make tensors
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cvec.tensors.reserve(model.hparams.n_layer);
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cvec.tensors.push_back(nullptr); // there's never a tensor for layer 0
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for (size_t il = 1; il < model.hparams.n_layer; il++) {
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struct ggml_context * ctx = ctx_map.at(model.buft_layer[il].buft);
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@ -16170,6 +16171,8 @@ static bool llama_control_vector_init(struct llama_control_vector & cvec, const
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}
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// allocate tensors / buffers and zero
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cvec.ctxs.reserve(ctx_map.size());
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cvec.bufs.reserve(ctx_map.size());
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for (auto it : ctx_map) {
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ggml_backend_buffer_type_t buft = it.first;
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ggml_context * ctx = it.second;
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