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Merge commit 'd6f3030047f85a98b009189e76f441fe818ea44d' into concedo_experimental
# Conflicts: # examples/model-conversion/scripts/causal/run-casual-gen-embeddings-org.py # examples/model-conversion/scripts/utils/semantic_check.py # ggml/CMakeLists.txt # ggml/src/CMakeLists.txt # ggml/src/ggml-cann/ggml-cann.cpp # ggml/src/ggml-cpu/amx/amx.cpp # ggml/src/ggml-cuda/CMakeLists.txt # ggml/src/ggml-hexagon/ggml-hexagon.cpp # ggml/src/ggml-hip/CMakeLists.txt # ggml/src/ggml-opencl/ggml-opencl.cpp # ggml/src/ggml-openvino/ggml-openvino.cpp # ggml/src/ggml-rpc/ggml-rpc.cpp # ggml/src/ggml-sycl/ggml-sycl.cpp # ggml/src/ggml-virtgpu/ggml-backend-buffer.cpp # ggml/src/ggml-virtgpu/ggml-backend.cpp # ggml/src/ggml-webgpu/ggml-webgpu.cpp # ggml/src/ggml-zdnn/ggml-zdnn.cpp # ggml/src/ggml-zendnn/ggml-zendnn.cpp # pyproject.toml # requirements/requirements-convert_legacy_llama.txt # requirements/requirements-tool_bench.txt # src/llama-model.cpp # src/llama.cpp # tests/test-llama-archs.cpp # tests/test-tokenizer-0.py # tests/test-tokenizer-random.py # tools/llama-bench/llama-bench.cpp # tools/perplexity/perplexity.cpp
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@@ -2351,19 +2351,21 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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}
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).set_env("LLAMA_ARG_N_GPU_LAYERS"));
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add_opt(common_arg(
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{"-sm", "--split-mode"}, "{none,layer,row}",
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{"-sm", "--split-mode"}, "{none,layer,row,tensor}",
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"how to split the model across multiple GPUs, one of:\n"
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"- none: use one GPU only\n"
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"- layer (default): split layers and KV across GPUs\n"
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"- row: split rows across GPUs",
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"- layer (default): split layers and KV across GPUs (pipelined)\n"
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"- row: split weight across GPUs by rows (parallelized)\n"
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"- tensor: split weights and KV across GPUs (parallelized)",
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[](common_params & params, const std::string & value) {
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std::string arg_next = value;
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if (arg_next == "none") {
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if (value == "none") {
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params.split_mode = LLAMA_SPLIT_MODE_NONE;
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} else if (arg_next == "layer") {
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} else if (value == "layer") {
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params.split_mode = LLAMA_SPLIT_MODE_LAYER;
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} else if (arg_next == "row") {
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} else if (value == "row") {
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params.split_mode = LLAMA_SPLIT_MODE_ROW;
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} else if (value == "tensor") {
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params.split_mode = LLAMA_SPLIT_MODE_TENSOR;
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} else {
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throw std::invalid_argument("invalid value");
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}
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