llama.cpp/examples/cvector-generator/CMakeLists.txt

set(TARGET llama-cvector-generator)
add_executable(${TARGET} cvector-generator.cpp pca.hpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_17)
Add `cvector-generator` example (#7514) * add control-vector-generator * calc diff * add comments * proof-of-concept stdlib implementation Implements PCA and file writing using mostly standard libraries. The output is recognized as a functional control vector, but outputs gibberish. * param parsing, refactor, comments Added basic command-line parameters for outfile and one each positive/negative prompt. Refactored some messy code in PCA computation and GGUF exporting. Left a bunch of comments regarding further work needed. * example template completions Implements an example template set built from the positive/negative prompts like the control vector Python implementation. * add multi prompts, multi-thread for PCA * fix mem error * add debugs * fix matrix transpose multiplication you have got to be kidding me * preliminary template/multiprompt support model is running out of context and that ought to be fixed (segfaulting) but other than that it looks goodish * fix zero output & param parsing, functional templating fixed a bug where the output file had no tensor data/was all zero fixed a bug where single hyphen flags were not being correctly parsed implements creation of templated prompts from input (still need to adapt based on model) * fix square_diff matmul index range and CRLF->LF line endings fixed a logic error where square_diff would not multiply all rows fixed a formatting error where the provided completions.txt had CRLF line endings * add command-line args for num threads, num completions file lines, always reload model refactored a few things and did what the commit message says on the tin * code aestheticization * fix compiler warnings * in-series multithreading for prompt embedding? added commented-out code to attempt to start implementing mutlithreading for embedding in main * remove unnecessary multithreading * interim fix memory leak * translated everything but PCA (I think) * tentatively translate the rest * fix ggml errors and make new ones at least it compiles and runs * fix cb_eval * temporary commit while I move dev environments it finally outputs a functioning control vector - "functioning" in the sense that it can be loaded and it clearly has the right idea, but makes the model incoherent * update debug statements * pre-tokenize so we can allocate correct memory to ctx_diffs_wrapped * update comments * (wip) refactor * clean up PCA ggml implementation * fix shape of v_diff_original * add n_batch for pca * working version * remember to copy back the last_eigenvector * fix n_completions * bring back n_completions * default n_pca_batch to 20 * fix macos build * add to makefile all targets * use ggml_format_name * add readme * fix .editorconfig * use ggml_backend_tensor_copy * attemp to fix compile problem on mac * fix compile warn * reuse allocr * move param parser to common * better error handling * clean up a bit * add print_usage * shorten help msg * beautify help msg * escape prompt by default * change compile target to llama-cvector-generator * typo * disable GPU for PCA * code style --------- Co-authored-by: Christian Zhou-Zheng <christianzhouzheng@gmail.com> 2024-06-15 18:53:40 +02:00			`set(TARGET llama-cvector-generator)`
			`add_executable(${TARGET} cvector-generator.cpp pca.hpp)`
			`install(TARGETS ${TARGET} RUNTIME)`
			`target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})`
ggml : move AMX to the CPU backend (#10570) * ggml : move AMX to the CPU backend --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> 2024-11-29 21:54:58 +01:00			`target_compile_features(${TARGET} PRIVATE cxx_std_17)`