25 篇文章带有标签 “apple-silicon”

准备音频文件

macOS 上打开 QuickTimePlayer

1. [文件] -> [新建音频录制]
2. 录制
3. 朗读：荷兰发布了一份主题为“宣布即将对先进半导体制造设备采取的出口管制措施”的公告表示，鉴于技术的发展和地缘政治的背景，政府已经得出结论，有必要扩大现有的特定半导体制造设备的出口管制。
4. 停止
5. 保存(test.m4a)

• 荷兰限制部分型号光刻机出口 中国市场影响几何

m4a 转换 wav

ffmpeg -i test.m4a -ar 16000 -ac 1 -c:a pcm_s16le test.wav

OpenAI Whisper

创建虚拟环境

conda create --name whisper python
conda activate whisper

安装

pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git

wget https://raw.githubusercontent.com/openai/whisper/main/requirements.txt
pip install -r requirements.txt

测试 模型默认保存在 ~/.cache/whisper ls ~/.cache/whisper base.pt large-v2.

Apple 芯片上进行硬件加速的框架

Video Toolbox

VideoToolbox 是一个低级框架，可提供对硬件编码器和解码器的直接访问。它提供视频压缩和解压缩服务，以及存储在 CoreVideo 像素缓冲区中的光栅图像格式之间的转换。这些服务以会话对象（压缩、解压缩和像素传输）的形式提供。

VideoToolbox还包括一些命令行工具，例如vttool、vtenc、vtdecode等，可以在终端中使用。这些工具可以用来检查视频的属性、转码视频、将视频转换为图像序列等任务。

Audio Toolbox

AudioToolbox 是一个音频处理框架，支持音频处理的硬件加速，它提供了一系列用于音频编码、解码、转换和处理的API接口。

安装 FFmpeg

• static FFmpeg binaries for macOS 64-bit

创建目录

mkdir /opt/ffmpeg && cd /opt/ffmpeg

方法一：使用 curl

curl https://evermeet.cx/ffmpeg/ffmpeg-6.0.7z | tar -xz
curl https://evermeet.cx/ffmpeg/ffprobe-6.0.7z | tar -xz
curl https://evermeet.cx/ffmpeg/ffplay-6.0.7z | tar -xz

安装 OpenVINO（手动编译）

brew install cmake
brew install automake
brew install --build-from-source libtool
brew install --build-from-source libunistring
brew install --build-from-source libidn2
brew install --build-from-source wget
brew install --build-from-source libusb

sudo conda install scons -y                                                                        

# 克隆时把依赖的子模块进行克隆（先克隆OpenVINO，再进行子模块克隆失败）
git clone --depth 1 --recurse-submodules https://github.com/openvinotoolkit/openvino.git

cd openvino
python3 -m pip install -r src/bindings/python/wheel/requirements-dev.txt

# 安装OpenCV（可选）
sudo conda install -c conda-forge opencv

mkdir build && cd build

# 配置（-DOPENVINO_EXTRA_MODULES=../openvino_contrib/modules/arm_plugin 好像不需要）
cmake -DCMAKE_BUILD_TYPE=Release ..

# 编译
cmake --build . --config Release --parallel $(sysctl -n hw.ncpu)
**没有生成 wheel**

# 安装
sudo mkdir /opt/openvino
sudo cmake -DCMAKE_INSTALL_PREFIX=/opt/openvino -P cmake_install.cmake

# 查看可用设备
./bin/arm64/Release/hello_query_device 
[ INFO ] Build ................................. 2023.0.0-1-b300df1be6c
[ INFO ] 
[ INFO ] Available devices: 
[ INFO ] CPU
[ INFO ] 	SUPPORTED_PROPERTIES: 
[ INFO ] 		Immutable: SUPPORTED_METRICS : SUPPORTED_METRICS SUPPORTED_CONFIG_KEYS RANGE_FOR_ASYNC_INFER_REQUESTS RANGE_FOR_STREAMS
[ INFO ] 		Immutable: SUPPORTED_CONFIG_KEYS : LP_TRANSFORMS_MODE DUMP_GRAPH PERF_COUNT CPU_THROUGHPUT_STREAMS CPU_BIND_THREAD CPU_THREADS_NUM CPU_THREADS_PER_STREAM BIG_CORE_STREAMS SMALL_CORE_STREAMS THREADS_PER_STREAM_BIG THREADS_PER_STREAM_SMALL SMALL_CORE_OFFSET ENABLE_HYPER_THREAD NUM_STREAMS INFERENCE_NUM_THREADS AFFINITY
[ INFO ] 		Mutable: PERF_COUNT : YES
[ INFO ] 		Immutable: AVAILABLE_DEVICES : NEON
[ INFO ] 		Immutable: FULL_DEVICE_NAME : arm_compute::NEON
[ INFO ] 		Immutable: OPTIMIZATION_CAPABILITIES : FP16 FP32
[ INFO ] 		Immutable: RANGE_FOR_ASYNC_INFER_REQUESTS : 1 12 1
[ INFO ] 		Mutable: PERFORMANCE_HINT : ""
[ INFO ] 		Immutable: RANGE_FOR_STREAMS : 1 12
[ INFO ] 		Mutable: CPU_THROUGHPUT_STREAMS : 1
[ INFO ] 		Mutable: CPU_BIND_THREAD : NO
[ INFO ] 		Mutable: CPU_THREADS_NUM : 0
[ INFO ] 		Mutable: CPU_THREADS_PER_STREAM : 12
[ INFO ] 		Mutable: BIG_CORE_STREAMS : 0
[ INFO ] 		Mutable: SMALL_CORE_STREAMS : 0
[ INFO ] 		Mutable: THREADS_PER_STREAM_BIG : 0
[ INFO ] 		Mutable: THREADS_PER_STREAM_SMALL : 0
[ INFO ] 		Mutable: SMALL_CORE_OFFSET : 0
[ INFO ] 		Mutable: ENABLE_HYPER_THREAD : YES
[ INFO ] 		Mutable: NUM_STREAMS : 1
[ INFO ] 		Mutable: INFERENCE_NUM_THREADS : 0
[ INFO ] 		Mutable: AFFINITY : NONE
[ INFO ] 

安装 PyTorch

sudo conda create --name pytorch python
conda activate pytorch

conda install pytorch torchvision torchaudio -c pytorch

安装每日构建版本

pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu

升级

pip3 install --upgrade --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu

训练模型 import torch import torchvision import torchvision.transforms as transforms print(f"PyTorch version: {torch.

安装 TensorFlow

sudo conda create --name tensorflow python
conda activate tensorflow

# 不指定环境(-n)，默认安装到base环境
sudo conda install -c apple -n tensorflow tensorflow-deps
pip install tensorflow-macos
pip install tensorflow-metal
sudo conda install notebook -y

pip install numpy  --upgrade
pip install pandas  --upgrade
pip install matplotlib  --upgrade
pip install scikit-learn  --upgrade
pip install scipy  --upgrade
pip install plotly  --upgrade

验证 import sys import tensorflow.keras import tensorflow as tf import platform print(f"Python Platform: {platform.