$mkdir build
$cd build
$cmake ..
-- The C compiler identification is GNU 9.5.0
-- The CXX compiler identification is GNU 9.5.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success
-- Found Threads: TRUE
-- CMAKE_SYSTEM_PROCESSOR: x86_64
-- x86 detected
-- Linux detected
-- Configuring done
-- Generating done
-- Build files have been written to: /home/pdd/le/bark.cpp/build
$cmake --build . --config Release
[ 7%] Building C object ggml/src/CMakeFiles/ggml.dir/ggml.c.o
[ 14%] Building C object ggml/src/CMakeFiles/ggml.dir/ggml-alloc.c.o
[ 21%] Linking C static library libggml.a
[ 21%] Built target ggml
[ 28%] Building CXX object CMakeFiles/bark.cpp.dir/bark.cpp.o
[ 42%] Linking CXX static library libbark.cpp.a
[ 42%] Built target bark.cpp
[ 50%] Building CXX object examples/main/CMakeFiles/main.dir/main.cpp.o
[ 57%] Linking CXX executable ../../bin/main
[ 57%] Built target main
[ 64%] Building CXX object examples/server/CMakeFiles/server.dir/server.cpp.o
[ 71%] Linking CXX executable ../../bin/server
[ 71%] Built target server
[ 78%] Building CXX object examples/quantize/CMakeFiles/quantize.dir/quantize.cpp.o
[ 85%] Linking CXX executable ../../bin/quantize
[ 85%] Built target quantize
[ 92%] Building CXX object tests/CMakeFiles/test-tokenizer.dir/test-tokenizer.cpp.o
[100%] Linking CXX executable ../bin/test-tokenizer
[100%] Built target test-tokenizer
权重下载与转换
$cd ../
# text_2.pt, coarse_2.pt, fine_2.pt,https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
$python3 download_weights.py --download-dir ./models
# convert the model to ggml format
$python3 convert.py --dir-model ./models --codec-path ./models --vocab-path ./ggml_weights/ --out-dir ./ggml_weights/
$ ls -ahl ./models/
总用量 13G
drwxrwxr-x 2 pdd pdd 4.0K Jan 29 08:22 .
drwxrwxr-x 13 pdd pdd 4.0K Jan 29 06:50 ..
-rwxrwxrwx 1 pdd pdd 3.7G Jan 29 07:34 coarse_2.pt
-rw-rw-r-- 1 pdd pdd 89M Jan 29 07:29 encodec_24khz-d7cc33bc.th
-rwxrwxrwx 1 pdd pdd 3.5G Jan 29 07:53 fine_2.pt
-rwxrwxrwx 1 pdd pdd 5.0G Jan 29 07:22 text_2.pt
$ ls -ahl ./ggml_weights/
总用量 4.2G
drwxrwxr-x 2 pdd pdd 4.0K Jan 29 08:34 .
drwxrwxr-x 13 pdd pdd 4.0K Jan 29 06:50 ..
-rw-rw-r-- 1 pdd pdd 1.3M Jan 29 08:33 ggml_vocab.bin
-rw-rw-r-- 1 pdd pdd 1.3G Jan 29 08:34 ggml_weights_coarse.bin
-rw-rw-r-- 1 pdd pdd 45M Jan 29 08:34 ggml_weights_codec.bin
-rw-rw-r-- 1 pdd pdd 1.2G Jan 29 08:34 ggml_weights_fine.bin
-rw-rw-r-- 1 pdd pdd 1.7G Jan 29 08:33 ggml_weights_text.bin
-rw-rw-r-- 1 pdd pdd 973K Jan 29 05:23 vocab.txt
$ ./main -m ./ggml_weights/ -p "this is an audio"
运行
$ ./build/bin/main -h
usage: ./build/bin/main [options]options:-h, --help show this help message and exit-t N, --threads N number of threads to use during computation (default: 4)-s N, --seed N seed for random number generator (default: 0)-p PROMPT, --prompt PROMPTprompt to start generation with (default: random)-m FNAME, --model FNAMEmodel path (default: /home/pdd/le/bark.cpp/ggml_weights)-o FNAME, --outwav FNAMEoutput generated wav (default: output.wav)
$ ./build/bin/main -m ./ggml_weights/ -p "this is an audio"
bark_load_model_from_file: loading model from './ggml_weights/'
bark_load_model_from_file: reading bark text model
gpt_model_load: n_in_vocab = 129600
gpt_model_load: n_out_vocab = 10048
gpt_model_load: block_size = 1024
gpt_model_load: n_embd = 1024
gpt_model_load: n_head = 16
gpt_model_load: n_layer = 24
gpt_model_load: n_lm_heads = 1
gpt_model_load: n_wtes = 1
gpt_model_load: ftype = 0
gpt_model_load: qntvr = 0
gpt_model_load: ggml tensor size = 304 bytes
gpt_model_load: ggml ctx size = 1894.87 MB
gpt_model_load: memory size = 192.00 MB, n_mem = 24576
gpt_model_load: model size = 1701.69 MB
bark_load_model_from_file: reading bark vocabbark_load_model_from_file: reading bark coarse model
gpt_model_load: n_in_vocab = 12096
gpt_model_load: n_out_vocab = 12096
gpt_model_load: block_size = 1024
gpt_model_load: n_embd = 1024
gpt_model_load: n_head = 16
gpt_model_load: n_layer = 24
gpt_model_load: n_lm_heads = 1
gpt_model_load: n_wtes = 1
gpt_model_load: ftype = 0
gpt_model_load: qntvr = 0
gpt_model_load: ggml tensor size = 304 bytes
gpt_model_load: ggml ctx size = 1443.87 MB
gpt_model_load: memory size = 192.00 MB, n_mem = 24576
gpt_model_load: model size = 1250.69 MBbark_load_model_from_file: reading bark fine model
gpt_model_load: n_in_vocab = 1056
gpt_model_load: n_out_vocab = 1056
gpt_model_load: block_size = 1024
gpt_model_load: n_embd = 1024
gpt_model_load: n_head = 16
gpt_model_load: n_layer = 24
gpt_model_load: n_lm_heads = 7
gpt_model_load: n_wtes = 8
gpt_model_load: ftype = 0
gpt_model_load: qntvr = 0
gpt_model_load: ggml tensor size = 304 bytes
gpt_model_load: ggml ctx size = 1411.25 MB
gpt_model_load: memory size = 192.00 MB, n_mem = 24576
gpt_model_load: model size = 1218.26 MBbark_load_model_from_file: reading bark codec model
encodec_model_load: model size = 44.32 MBbark_load_model_from_file: total model size = 4170.64 MBbark_tokenize_input: prompt: 'this is an audio'
bark_tokenize_input: number of tokens in prompt = 513, first 8 tokens: 20579 20172 20199 33733 129595 129595 129595 129595
bark_forward_text_encoder: ...........................................................................................................bark_print_statistics: mem per token = 4.81 MB
bark_print_statistics: sample time = 16.03 ms / 109 tokens
bark_print_statistics: predict time = 9644.73 ms / 87.68 ms per token
bark_print_statistics: total time = 9663.29 msbark_forward_coarse_encoder: ...................................................................................................................................................................................................................................................................................................................................bark_print_statistics: mem per token = 8.53 MB
bark_print_statistics: sample time = 4.43 ms / 324 tokens
bark_print_statistics: predict time = 52071.64 ms / 160.22 ms per token
bark_print_statistics: total time = 52080.24 msggml_new_object: not enough space in the context's memory pool (needed 4115076720, available 4112941056)
段错误 (核心已转储)
一开始以为是内存不足，去增加了虚拟内存，但仍然报错
$ sudo dd if=/dev/zero of=swapfile bs=1024 count=10000000
记录了10000000+0 的读入
记录了10000000+0 的写出
10240000000字节（10 GB，9.5 GiB）已复制，55.3595 s，185 MB/s
$ sudo chmod 600./swapfile # delete the swapfile if you dont need it
$ sudo mkswap -f ./swapfile
正在设置交换空间版本 1，大小 =9.5 GiB (10239995904 个字节)
无标签， UUID=f3e2a0be-b880-48da-b598-950b7d69f94f
$ sudo swapon ./swapfile
$ free -mtotal used free shared buff/cache available
内存： 157316441307124289827713
交换： 1181320479765$ ./build/bin/main -m ./ggml_weights/-p "this is an audio"
ggml_new_object:notenough space in the context's memory pool (needed 4115076720, available 4112941056)
去看了报错的函数，应该不是内存的原因
static struct ggml_object * ggml_new_object(struct ggml_context * ctx, enum ggml_object_type type, size_t size) {// always insert objects at the end of the context's memory poolstruct ggml_object * obj_cur = ctx->objects_end;const size_t cur_offs = obj_cur == NULL ? 0 : obj_cur->offs;const size_t cur_size = obj_cur == NULL ? 0 : obj_cur->size;const size_t cur_end = cur_offs + cur_size;// align to GGML_MEM_ALIGNsize_t size_needed = GGML_PAD(size, GGML_MEM_ALIGN);char * const mem_buffer = ctx->mem_buffer;struct ggml_object * const obj_new = (struct ggml_object *)(mem_buffer + cur_end);if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) {GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",__func__, cur_end + size_needed, ctx->mem_size);assert(false);return NULL;}*obj_new = (struct ggml_object) {.offs = cur_end + GGML_OBJECT_SIZE,.size = size_needed,.next = NULL,.type = type,};ggml_assert_aligned(mem_buffer + obj_new->offs);if (obj_cur != NULL) {obj_cur->next = obj_new;} else {// this is the first object in this contextctx->objects_begin = obj_new;}ctx->objects_end = obj_new;//printf("%s: inserted new object at %zu, size = %zu\n", __func__, cur_end, obj_new->size);return obj_new;
}
#include<iostream>
using namespace std;//抽象不同的零件//抽象的cpu类
class Cpu
{
public://抽象的计算函数virtual void calculate() 0;
};//抽象的显卡类
class VideoCard
{
public://抽象的显示函数virtual void display() 0;
};//抽象的内存条类
class Memory
…
)
