Feature add cublas support (#65)
* chore: add ggml import in the head of rwkv.h * chore: add ggml import in the head of rwkv.h * feat: add cublas support * feat: update rwkv.cpp * feat: remove unused change * chore: fix linux build issue * chore: sync ggml and offload tensor to gpu * chore: comment out tensors which occurs error on GPU * chore: update comment and readme * chore: update ggml to recent * chore: add more performance test results * chore: add more performance test results * chore: fix problem of reading file more than 2 gb * chore: merge master * chore: remove unused comment * chore: fix for comments * Update README.md * Update rwkv.cpp --------- Co-authored-by: Alex <saharNooby@users.noreply.github.com>
This commit is contained in:
YorkZero
GitHub
parent
dea929f8ca
commit
241350fde6
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@ -39,6 +39,7 @@ option(RWKV_FMA "rwkv: enable FMA"
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# 3rd party libs
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option(RWKV_ACCELERATE "rwkv: enable Accelerate framework" ON)
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option(RWKV_OPENBLAS "rwkv: use OpenBLAS" OFF)
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option(RWKV_CUBLAS "rwkv: use cuBLAS" OFF)
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#
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# Compile flags
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@ -97,6 +98,30 @@ if (RWKV_OPENBLAS)
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endif()
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endif()
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if (RWKV_CUBLAS)
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cmake_minimum_required(VERSION 3.17)
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find_package(CUDAToolkit)
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if (CUDAToolkit_FOUND)
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message(STATUS "cuBLAS found")
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enable_language(CUDA)
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set(GGML_CUDA_SOURCES ${CMAKE_SOURCE_DIR}/ggml/src/ggml-cuda.cu ${CMAKE_SOURCE_DIR}/ggml/src/ggml-cuda.h)
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add_compile_definitions(GGML_USE_CUBLAS)
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if (RWKV_STATIC)
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set(RWKV_EXTRA_LIBS ${RWKV_EXTRA_LIBS} CUDA::cudart_static CUDA::cublas_static CUDA::cublasLt_static)
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else()
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set(RWKV_EXTRA_LIBS ${RWKV_EXTRA_LIBS} CUDA::cudart CUDA::cublas CUDA::cublasLt)
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endif()
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else()
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message(WARNING "cuBLAS not found")
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endif()
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endif()
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if (RWKV_ALL_WARNINGS)
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if (NOT MSVC)
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set(c_flags
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@ -177,11 +202,18 @@ elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "^(x86_64|i686|AMD64)$")
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message(STATUS "x86 detected")
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if (MSVC)
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if (RWKV_AVX512)
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add_compile_options(/arch:AVX512)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX512>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX512>)
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# MSVC has no compile-time flags enabling specific
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# AVX512 extensions, neither it defines the
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# macros corresponding to the extensions.
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# Do it manually.
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elseif (RWKV_AVX2)
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add_compile_options(/arch:AVX2)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX2>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX2>)
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elseif (RWKV_AVX)
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add_compile_options(/arch:AVX)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX>)
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endif()
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else()
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add_compile_options(-mf16c)
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@ -212,7 +244,19 @@ if (MSVC)
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add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
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endif()
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add_subdirectory(ggml)
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add_library(ggml OBJECT
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${CMAKE_SOURCE_DIR}/ggml/src/ggml.c
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${CMAKE_SOURCE_DIR}/ggml/include/ggml/ggml.h
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${GGML_CUDA_SOURCES})
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target_include_directories(ggml PUBLIC ${CMAKE_SOURCE_DIR}/ggml/include/ggml)
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target_compile_features(ggml PUBLIC c_std_11) # Don't bump
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if (MSVC)
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target_link_libraries(ggml PUBLIC ${RWKV_EXTRA_LIBS} Threads::Threads)
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else()
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target_link_libraries(ggml PUBLIC m ${RWKV_EXTRA_LIBS} Threads::Threads)
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endif()
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if (RWKV_BUILD_SHARED_LIBRARY)
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set_target_properties(ggml PROPERTIES POSITION_INDEPENDENT_CODE ON)
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@ -233,5 +277,12 @@ if (RWKV_BUILD_SHARED_LIBRARY)
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target_compile_definitions(rwkv PRIVATE RWKV_SHARED RWKV_BUILD)
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endif()
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if (GGML_CUDA_SOURCES)
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message(STATUS "GGML CUDA sources found, configuring CUDA architecture")
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set_property(TARGET ggml PROPERTY CUDA_ARCHITECTURES OFF)
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set_property(TARGET ggml PROPERTY CUDA_SELECT_NVCC_ARCH_FLAGS "Auto")
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set_property(TARGET rwkv PROPERTY CUDA_ARCHITECTURES OFF)
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endif()
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enable_testing()
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add_subdirectory(tests)
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42
README.md
42
README.md
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@ -26,6 +26,21 @@ Below table is for reference only. Measurements were made on 4C/8T x86 CPU with
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| `FP16` | **15.623** | 117 | 2.82 |
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| `FP32` | **15.623** | 198 | 5.64 |
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#### With cuBLAS
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Measurements were made on 3060Ti 8G + i7 13700K. Latency per token shown.
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| Model | Layers on GPU | Format | 24 Threads | 8 Threads | 4 Threads | 2 Threads | 1 Threads |
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|-----------------------|---------------|--------|-------------|------------|------------|------------|------------|
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| `RWKV-4-Pile-169M` | 12 | `Q4_0` | 20.6 ms | 8.6 ms | 6.9 ms | 6.2 ms | 7.9 ms |
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| `RWKV-4-Pile-169M` | 12 | `Q4_1` | 21.4 ms | 8.6 ms | 6.9 ms | 6.7 ms | 7.8 ms |
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| `RWKV-4-Pile-169M` | 12 | `Q5_1` | 22.2 ms | 9.0 ms | 6.9 ms | 6.7 ms | 8.1 ms |
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| `RWKV-4-Raven-7B-v11` | 32 | `Q4_0` | 94.9 ms | 54.3 ms | 50.2 ms | 51.6 ms | 59.2 ms |
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| `RWKV-4-Raven-7B-v11` | 32 | `Q4_1` | 94.5 ms | 54.3 ms | 49.7 ms | 51.8 ms | 59.2 ms |
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| `RWKV-4-Raven-7B-v11` | 32 | `Q5_1` | 101.6 ms | 72.3 ms | 67.2 ms | 69.3 ms | 77.0 ms |
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Note: since there is only `ggml_mul_mat()` supported with cuBLAS, we still need to assign few CPU resources to execute remaining operations.
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## How to use
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### 1. Clone the repo
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@ -62,6 +77,17 @@ cmake --build . --config Release
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If everything went OK, `bin\Release\rwkv.dll` file should appear.
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##### Windows + cuBLAS
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**Important**: Since there is no cuBLAS static libraries for Windows, after compiling with dynamic libraries following DLLs should be copied from `{CUDA}/bin` into `build/bin/Release`: `cudart64_12.dll`, `cublas64_12.dll`, `cublasLt64_12.dll`.
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```commandline
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mkdir build
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cd build
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cmake .. -DRWKV_CUBLAS=ON
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cmake --build . --config Release
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```
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##### Linux / MacOS
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**Requirements**: CMake (Linux: `sudo apt install cmake`, MacOS: `brew install cmake`, anaconoda: [cmake package](https://anaconda.org/conda-forge/cmake)).
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@ -75,6 +101,16 @@ cmake --build . --config Release
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If everything went OK, `librwkv.so` (Linux) or `librwkv.dylib` (MacOS) file should appear in the base repo folder.
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##### Linux / MacOS + cuBLAS
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```commandline
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mkdir build
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cd build
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cmake .. -DRWKV_CUBLAS=ON
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cmake --build . --config Release
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```
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If everything went OK, `librwkv.so` (Linux) or `librwkv.dylib` (MacOS) file should appear in the base repo folder.
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### 3. Get an RWKV model
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@ -152,14 +188,16 @@ model_path = r'C:\rwkv.cpp-169M.bin'
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model = rwkv_cpp_model.RWKVModel(
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rwkv_cpp_shared_library.load_rwkv_shared_library(),
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model_path
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model_path,
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thread_count=4, #need to adjust when use cuBLAS
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gpu_layers_count=5 #only enabled when use cuBLAS
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)
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logits, state = None, None
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for token in [1, 2, 3]:
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logits, state = model.eval(token, state)
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print(f'Output logits: {logits}')
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# Don't forget to free the memory after you've done working with the model
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39
rwkv.cpp
39
rwkv.cpp
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@ -1,6 +1,10 @@
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#include "rwkv.h"
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#include "ggml.h"
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#ifdef GGML_USE_CUBLAS
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#include "ggml/src/ggml-cuda.h"
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#endif
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#include <string>
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#include <vector>
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#include <thread>
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@ -274,6 +278,8 @@ struct rwkv_context {
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struct rwkv_graph graph;
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enum rwkv_error_flags last_error;
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bool print_errors;
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size_t vram_total;
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int gpu_layers;
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};
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void rwkv_set_print_errors(struct rwkv_context * ctx, bool print_errors) {
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@ -461,6 +467,10 @@ struct rwkv_ggml_guard {
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};
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struct rwkv_context * rwkv_init_from_file(const char * file_path, const uint32_t n_threads) {
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return rwkv_init_from_file(file_path, n_threads, 0);
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}
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struct rwkv_context * rwkv_init_from_file(const char * file_path, const uint32_t n_threads, const uint32_t n_gpu_layers) {
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global_last_error = RWKV_ERROR_NONE;
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FILE * file = fopen(file_path, "rb");
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@ -481,7 +491,7 @@ struct rwkv_context * rwkv_init_from_file(const char * file_path, const uint32_t
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std::unique_ptr<rwkv_model> model(new(std::nothrow) struct rwkv_model());
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RWKV_ASSERT_NULL_MSG(RWKV_ERROR_MODEL | RWKV_ERROR_ALLOC, model.get(), "Failed to allocate model");
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL, read_uint32(file, &model->n_vocab, "n_vocab"));
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL, read_uint32(file, &model->n_embed, "n_embed"));
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL, read_uint32(file, &model->n_layer, "n_layer"));
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@ -600,6 +610,29 @@ struct rwkv_context * rwkv_init_from_file(const char * file_path, const uint32_t
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL_PARAMS, set_block_parameter(¶meters, i, "ffn.receptance.weight", &layer->ffn_receptance));
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}
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int n_gpu = 0;
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size_t vram_total = 0;
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#ifdef GGML_USE_CUBLAS
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{
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n_gpu = std::min(n_gpu_layers, model->n_layer);
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for (int i = 0; i < n_gpu; ++i) {
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const auto & layer = model->layers[i];
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// Use cuBLAS only for heavy matrices; other operations are not supported for GPU at the moment
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ggml_cuda_transform_tensor(layer.att_key); vram_total += ggml_nbytes(layer.att_key);
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ggml_cuda_transform_tensor(layer.att_value); vram_total += ggml_nbytes(layer.att_value);
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ggml_cuda_transform_tensor(layer.att_receptance); vram_total += ggml_nbytes(layer.att_receptance);
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ggml_cuda_transform_tensor(layer.att_output); vram_total += ggml_nbytes(layer.att_output);
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ggml_cuda_transform_tensor(layer.ffn_key); vram_total += ggml_nbytes(layer.ffn_key);
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ggml_cuda_transform_tensor(layer.ffn_value); vram_total += ggml_nbytes(layer.ffn_value);
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ggml_cuda_transform_tensor(layer.ffn_receptance); vram_total += ggml_nbytes(layer.ffn_receptance);
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}
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}
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#endif
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL_PARAMS, set_parameter(¶meters, "ln_out.weight", &model->ln_out_weight));
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL_PARAMS, set_parameter(¶meters, "ln_out.bias", &model->ln_out_bias));
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RWKV_ASSERT_NULL(RWKV_ERROR_MODEL_PARAMS, set_parameter(¶meters, "head.weight", &model->head));
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@ -621,6 +654,8 @@ struct rwkv_context * rwkv_init_from_file(const char * file_path, const uint32_t
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rwkv_ctx->graph = std::move(graph);
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rwkv_ctx->last_error = RWKV_ERROR_NONE;
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rwkv_ctx->print_errors = global_print_errors;
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rwkv_ctx->gpu_layers = n_gpu;
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rwkv_ctx->vram_total = vram_total;
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// Don't free ggml context
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ggml_guard.ctx = NULL;
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return rwkv_ctx.release();
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@ -936,4 +971,4 @@ const char * rwkv_get_system_info_string(void) {
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s += "VSX = " + std::to_string(ggml_cpu_has_vsx()) + " | ";
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return s.c_str();
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}
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}
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3
rwkv.h
3
rwkv.h
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@ -83,7 +83,8 @@ extern "C" {
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// Returns NULL on any error. Error messages would be printed to stderr.
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// - model_file_path: path to model file in ggml format.
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// - n_threads: count of threads to use, must be positive.
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RWKV_API struct rwkv_context * rwkv_init_from_file(const char * model_file_path, const uint32_t n_threads);
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// - n_gpu_layer: count of layers need to load to gpu (only works when cuBLAS is on)
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RWKV_API struct rwkv_context * rwkv_init_from_file(const char * model_file_path, const uint32_t n_threads, const uint32_t n_gpu_layers);
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// Evaluates the model for a single token.
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// Returns false on any error. Error messages would be printed to stderr.
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@ -13,6 +13,7 @@ import rwkv_cpp_model
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import rwkv_cpp_shared_library
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import json
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from typing import List, Dict, Optional
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import time
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# ======================================== Script settings ========================================
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@ -108,10 +109,13 @@ def split_last_end_of_line(tokens):
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return tokens
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# =================================================================================================
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T1 = time.time()
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print(f'Processing {prompt_token_count} prompt tokens, may take a while')
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process_tokens(split_last_end_of_line(tokenizer.encode(init_prompt).ids))
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T2 = time.time()
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print(f'Process time :{((T2 - T1)*1000)} ms')
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print(f'Process time per token :{(((T2 - T1)*1000)) / prompt_token_count} ms')
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save_thread_state('chat_init')
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save_thread_state('chat')
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@ -13,7 +13,8 @@ class RWKVModel:
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self,
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shared_library: rwkv_cpp_shared_library.RWKVSharedLibrary,
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model_path: str,
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thread_count: int = max(1, multiprocessing.cpu_count() // 2)
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thread_count: int = max(1, multiprocessing.cpu_count() // 2),
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gpu_layers_count: int = 4,
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):
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"""
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Loads the model and prepares it for inference.
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@ -31,10 +32,11 @@ class RWKVModel:
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assert os.path.isfile(model_path), f'{model_path} is not a file'
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assert thread_count > 0, 'Thread count must be positive'
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assert gpu_layers_count > 0, 'GPU layers count must be positive'
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self._library = shared_library
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self._ctx = self._library.rwkv_init_from_file(model_path, thread_count)
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self._ctx = self._library.rwkv_init_from_file(model_path, thread_count, gpu_layers_count)
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self._state_buffer_element_count = self._library.rwkv_get_state_buffer_element_count(self._ctx)
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self._logits_buffer_element_count = self._library.rwkv_get_logits_buffer_element_count(self._ctx)
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@ -37,7 +37,7 @@ class RWKVSharedLibrary:
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self.library = ctypes.cdll.LoadLibrary(shared_library_path)
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self.library.rwkv_init_from_file.argtypes = [ctypes.c_char_p, ctypes.c_uint32]
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self.library.rwkv_init_from_file.argtypes = [ctypes.c_char_p, ctypes.c_uint32, ctypes.c_uint32]
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self.library.rwkv_init_from_file.restype = ctypes.c_void_p
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self.library.rwkv_eval.argtypes = [
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@ -67,7 +67,7 @@ class RWKVSharedLibrary:
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self.library.rwkv_get_system_info_string.argtypes = []
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self.library.rwkv_get_system_info_string.restype = ctypes.c_char_p
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def rwkv_init_from_file(self, model_file_path: str, thread_count: int) -> RWKVContext:
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def rwkv_init_from_file(self, model_file_path: str, thread_count: int, gpu_layers_count: int) -> RWKVContext:
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"""
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Loads the model from a file and prepares it for inference.
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Throws an exception in case of any error. Error messages would be printed to stderr.
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@ -78,9 +78,13 @@ class RWKVSharedLibrary:
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Path to model file in ggml format.
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thread_count : int
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Count of threads to use, must be positive.
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gpu_layers_count : int
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Count of layers to load on gpu, must be positive only enabled with cuBLAS.
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"""
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ptr = self.library.rwkv_init_from_file(model_file_path.encode('utf-8'), ctypes.c_uint32(thread_count))
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ptr = self.library.rwkv_init_from_file(model_file_path.encode('utf-8'),
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ctypes.c_uint32(thread_count),
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ctypes.c_uint32(gpu_layers_count))
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assert ptr is not None, 'rwkv_init_from_file failed, check stderr'
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return RWKVContext(ptr)
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@ -186,6 +190,7 @@ class RWKVSharedLibrary:
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return self.library.rwkv_get_system_info_string().decode('utf-8')
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||||
|
||||
def load_rwkv_shared_library() -> RWKVSharedLibrary:
|
||||
"""
|
||||
Attempts to find rwkv.cpp shared library and load it.
|
||||
|
|
@ -208,6 +213,10 @@ def load_rwkv_shared_library() -> RWKVSharedLibrary:
|
|||
f'../bin/Release/{file_name}',
|
||||
# If we are in repo root directory
|
||||
f'bin/Release/{file_name}',
|
||||
# If we compiled in build directory
|
||||
f'build/bin/Release/{file_name}',
|
||||
# If we compiled in build directory
|
||||
f'build/{file_name}',
|
||||
# Search relative to this file
|
||||
str(repo_root_dir / 'bin' / 'Release' / file_name),
|
||||
# Fallback
|
||||
|
|
|
|||
|
|
@ -1,6 +1,9 @@
|
|||
function(rwkv_add_test source)
|
||||
get_filename_component(TEST_TARGET ${source} NAME_WE)
|
||||
add_executable(${TEST_TARGET} ${source})
|
||||
if (GGML_CUDA_SOURCES)
|
||||
set_property(TARGET ${TEST_TARGET} PROPERTY CUDA_ARCHITECTURES OFF)
|
||||
endif()
|
||||
target_link_libraries(${TEST_TARGET} PRIVATE ggml rwkv)
|
||||
add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}> ${ARGN})
|
||||
endfunction()
|
||||
|
|
|
|||
|
|
@ -21,12 +21,12 @@
|
|||
|
||||
#define N_VOCAB 256
|
||||
#define N_THREADS 2
|
||||
#define N_GPU_LAYERS 1
|
||||
|
||||
void test_model(const char * model_path, const float * expected_logits, const float max_diff) {
|
||||
fprintf(stderr, "Testing %s\n", model_path);
|
||||
|
||||
struct rwkv_context * model = rwkv_init_from_file(model_path, N_THREADS);
|
||||
|
||||
struct rwkv_context * model = rwkv_init_from_file(model_path, N_THREADS, N_GPU_LAYERS);
|
||||
enum rwkv_error_flags error = rwkv_get_last_error(NULL);
|
||||
ASSERT(error == 0, "Unexpected error %d", error);
|
||||
|
||||
|
|
@ -72,18 +72,27 @@ int main(void) {
|
|||
ASSERT(elements_read == N_VOCAB, "Failed to read expected_logits.bin, read %zd elements", elements_read);
|
||||
fclose(file);
|
||||
|
||||
// Somehow when using cuBLAS the calculation of Q4_1 may different from cpu only
|
||||
float expected_difference_sum[14] = {
|
||||
0.000000F,
|
||||
-0.005320F,
|
||||
|
||||
-0.160030F,
|
||||
#ifdef GGML_USE_CUBLAS
|
||||
-0.412408F,
|
||||
#else
|
||||
-0.370606F,
|
||||
#endif
|
||||
-0.170404F,
|
||||
0.278034F,
|
||||
0.071216F,
|
||||
|
||||
0.154614F,
|
||||
#ifdef GGML_USE_CUBLAS
|
||||
-0.405527F,
|
||||
#else
|
||||
-0.372169F,
|
||||
#endif
|
||||
-0.170043F,
|
||||
0.294953F,
|
||||
0.065571F,
|
||||
|
|
|
|||
Loading…
Reference in New Issue