diff --git a/README.md b/README.md index 25676af..2fd5ef6 100644 --- a/README.md +++ b/README.md @@ -207,22 +207,17 @@ clang: error: unsupported option '-fopenmp' ```bash # 第一步: 参考`https://mac.r-project.org/openmp/` -## 假设gcc -v是14.x版本,其他版本见R-Project提供的表格 +## 假设: gcc(clang)是14.x版本,其他版本见R-Project提供的表格 curl -O https://mac.r-project.org/openmp/openmp-14.0.6-darwin20-Release.tar.gz sudo tar fvxz openmp-14.0.6-darwin20-Release.tar.gz -C / -## 此时会安装下面几个文件: -# usr/local/lib/libomp.dylib -# usr/local/include/ompt.h -# usr/local/include/omp.h -# usr/local/include/omp-tools.h ``` -针对`chatglm-6b-int4`, 修改[quantization.py](https://huggingface.co/THUDM/chatglm-6b-int4/blob/main/quantization.py),主要是把硬编码的`gcc -O3 -fPIC -pthread -fopenmp -std=c99`命令修改成`gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99`,[对应代码](https://huggingface.co/THUDM/chatglm-6b-int4/blob/63d66b0572d11cedd5574b38da720299599539b3/quantization.py#L168)见下: +此时会安装下面几个文件:`/usr/local/lib/libomp.dylib`, `/usr/local/include/ompt.h`, `/usr/local/include/omp.h`, `/usr/local/include/omp-tools.h`。 + +然后针对`chatglm-6b-int4`, 修改[quantization.py](https://huggingface.co/THUDM/chatglm-6b-int4/blob/main/quantization.py),主要是把硬编码的`gcc -O3 -fPIC -pthread -fopenmp -std=c99`命令修改成`gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99`,[对应代码](https://huggingface.co/THUDM/chatglm-6b-int4/blob/63d66b0572d11cedd5574b38da720299599539b3/quantization.py#L168)见下: ```python -# 第二步 -## 找到包含`gcc -O3 -fPIC -pthread -fopenmp -std=c99`的这一行 -## 修改成 +# 第二步: 找到包含`gcc -O3 -fPIC -pthread -fopenmp -std=c99`的这一行,并修改成 compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99 {} -shared -o {}".format(source_code, kernel_file) ``` @@ -233,7 +228,7 @@ import platform ## ... ## 上述相应部分修改为(请自行改一下缩进): if platform.uname()[0] == 'Darwin': - compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99-o {}".format( + compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99 -o {}".format( source_code, kernel_file) else: compile_command = "gcc -O3 -fPIC -pthread -fopenmp -std=c99 {} -shared -o {}".format( diff --git a/README_en.md b/README_en.md index 2f256dd..f63bc01 100644 --- a/README_en.md +++ b/README_en.md @@ -200,26 +200,22 @@ clang: error: unsupported option '-fopenmp' Take the quantified int4 version [chatglm-6b-int4](https://huggingface.co/THUDM/chatglm-6b-int4) for example, the following extra steps are needed: -1. Install `libomp`; -2. Configure `gcc`. +#### Install `libomp` ```bash # STEP 1: install libopenmp, check `https://mac.r-project.org/openmp/` for details -## Assumption: `gcc -v >= 14.x`, read the R-Poject before run the code: +## Assumption: `gcc(clang) >= 14.x`, read the R-Poject before run the code: curl -O https://mac.r-project.org/openmp/openmp-14.0.6-darwin20-Release.tar.gz sudo tar fvxz openmp-14.0.6-darwin20-Release.tar.gz -C / -## Four files are installed: -# usr/local/lib/libomp.dylib -# usr/local/include/ompt.h -# usr/local/include/omp.h -# usr/local/include/omp-tools.h ``` +Four files (`/usr/local/lib/libomp.dylib`, `/usr/local/include/ompt.h`, `/usr/local/include/omp.h`, `/usr/local/include/omp-tools.h`) are installed accordingly. -For `chatglm-6b-int4`, modify the [quantization.py](https://huggingface.co/THUDM/chatglm-6b-int4/blob/main/quantization.py)file. In the file, change the `gcc -O3 -fPIC -pthread -fopenmp -std=c99` configuration to `gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99`,[corresponding python code](https://huggingface.co/THUDM/chatglm-6b-int4/blob/63d66b0572d11cedd5574b38da720299599539b3/quantization.py#L168), i.e.: +#### Configure `gcc` with `-fopenmp` + +Next, modify the [quantization.py](https://huggingface.co/THUDM/chatglm-6b-int4/blob/main/quantization.py) file of the `chatglm-6b-int4` project. In the file, change the `gcc -O3 -fPIC -pthread -fopenmp -std=c99` configuration to `gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99` (check the corresponding python code [HERE](https://huggingface.co/THUDM/chatglm-6b-int4/blob/63d66b0572d11cedd5574b38da720299599539b3/quantization.py#L168)), i.e.: ```python -# STEP -## Change the line contains `gcc -O3 -fPIC -pthread -fopenmp -std=c99` to: +# STEP 2: Change the line contains `gcc -O3 -fPIC -pthread -fopenmp -std=c99` to: compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99 {} -shared -o {}".format(source_code, kernel_file) ``` @@ -231,14 +227,14 @@ import platform ## ... ## change the corresponding lines to: if platform.uname()[0] == 'Darwin': - compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99-o {}".format( + compile_command = "gcc -O3 -fPIC -Xclang -fopenmp -pthread -lomp -std=c99 -o {}".format( source_code, kernel_file) else: compile_command = "gcc -O3 -fPIC -pthread -fopenmp -std=c99 {} -shared -o {}".format( source_code, kernel_file) ``` -> Notice: If you have run the `chatglm` project and failed, you may want to clean the cache of Huggingface before your next try, i.e. `rm -rf ${HOME}/.cache/huggingface/modules/transformers_modules/chatglm-6b-int4`. Since `rm` is used, please MAKE SURE that the command deletes the right files. +> Notice: If you have run the `ChatGLM` project and failed, you may want to clean the cache of Huggingface before your next try, i.e. `rm -rf ${HOME}/.cache/huggingface/modules/transformers_modules/chatglm-6b-int4`. Since `rm` is used, please MAKE SURE that the command deletes the right files. ### GPU Inference on Mac For Macs (and MacBooks) with Apple Silicon, it is possible to use the MPS backend to run ChatGLM-6B on the GPU. First, you need to refer to Apple's [official instructions](https://developer.apple.com/metal/pytorch) to install PyTorch-Nightly. @@ -248,7 +244,7 @@ Currently you must [load the model locally](README_en.md#load-the-model-locally) model = AutoModel.from_pretrained("your local path", trust_remote_code=True).half().to('mps') ``` -For Mac users with Mac >= 13.3, one may encounter errors related to `half()` method. Use `float()` instead: +For Mac users with Mac OS >= 13.3, one may encounter errors related to the `half()` method. Use the `float()` method instead: ```python model = AutoModel.from_pretrained("your local path", trust_remote_code=True).float().to('mps') @@ -256,7 +252,7 @@ model = AutoModel.from_pretrained("your local path", trust_remote_code=True).flo Then you can use GPU-accelerated model inference on Mac. -> Notice: there is no promblem to run the non-quantified version of ChatGLM with MPS. One could check [this issue](https://github.com/THUDM/ChatGLM-6B/issues/462) to run the quantified version with MPS as the backend (and get `ERRORS`). Unzip/unpack [kernel](https://huggingface.co/THUDM/chatglm-6b/blob/658202d88ac4bb782b99e99ac3adff58b4d0b813/quantization.py#L27) as an `ELF` file shows its backend is `cuda`. +> Notice: there is no promblem to run the non-quantified version of ChatGLM with MPS. One could check [this issue](https://github.com/THUDM/ChatGLM-6B/issues/462) to run the quantified version with MPS as the backend (and get `ERRORS`). Unpacking [kernel](https://huggingface.co/THUDM/chatglm-6b/blob/658202d88ac4bb782b99e99ac3adff58b4d0b813/quantization.py#L27) as an `ELF` file shows its backend is `cuda`, which fails on MPS currently (`torch 2.1.0.dev20230502`). ### Multi-GPU Deployment If you have multiple GPUs, but the memory size of each GPU is not sufficient to accommodate the entire model, you can split the model across multiple GPUs.