# From tensorflow/models/ export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim # switch back to object_detection after this and re run the above command 否则,你应该有一个新的目录,在我的情况下,我的是mac_n_cheese_inference_graph,里面,我有新的检查点数据,saved_model目录,最重要的是,forzen_inferenc...
Step 1:安装Xcode Command Line Tools,Apple Developer下载安装即可。 Step 2:安装arm版本miniforge。 从miniforge github选择最新的ARM64版本,一路yes就行。 之后终端conda --version或conda info -e检查是否成功。 Step 3: 从Mac-optimized TensorFlow2.4 and TensorFlow Addons下载ARM64版本的TensorFlow2.4,具体的安...
如果成功运行,会显示下列信息: bai@ubuntu:~/cudnn_samples_v8/mnistCUDNN$sudo./mnistCUDNNExecuting:mnistCUDNNcudnnGetVersion():8101,CUDNN_VERSIONfromcudnn.h:8101(8.1.1)Hostcompilerversion:GCC9.3.0Thereare2CUDAcapabledevicesonyourmachine:device0:sms30Capabilities6.1,SmClock1582.0Mhz,MemSize(Mb)12196,...
Xcode command-line tools:xcode-select --install Get started 1. Set up the environment Virtual environment: python3-m venv~/venv-metalsource~/venv-metal/bin/activatepython-m pip install-U pip 2. Install base TensorFlow For TensorFlow version 2.13 or later: ...
TensorFlow version (use command below): ('unknown', '1.4.0') Python version: python2.7 Bazel version (if compiling from source): unknown GCC/Compiler version (if compiling from source): gcc 4.8 CUDA/cuDNN version: 9.0 / 7.0 GPU model and memory: ...
nvcc --version 可查询CUDA的版本 Do you wish to build TensorFlow with MPI support? [y/N]: No MPI support will be enabled for TensorFlow. 这个选项是询问是否使用MPI。MPI(Message-Passing-Interface 消息传递接口)是实现进程级别的并行程序的通信协议,它通过在进程之间进行消息传递。如果不是基于TensorFlow做...
For JetPack 4, please check the command below: Jetson Nano Our official TensorFlow release for Jetson Nano! Python 3.6+JetPack4.6.3 $ sudo apt-get update $ sudo apt-get install -y python3-pip pkg-config $ sudo apt-get install -y libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev ...
I still could not make it fully automated, sop I have to run the last command manually by.. I found level 2 sufficient for debugging, use =3 if needed. Create symlinks (mind the proper path) Restart docker container / reboot Test. Launch python and type ...
TensorFlow 模型在开发环境中经过训练和验证。一旦发布,它们需要托管在某个地方,提供用工程师和软件工程师使用,以集成到各种应用中。 TensorFlow 为此提供了一个高表现服务器,称为 TensorFlow 服务。 要在生产中提供 TensorFlow 模型,需要在离线训练后保存它们,然后在生产环境中恢复经过训练的模型。 TensorFlow 模型在保存...
Reinstall miniforge3 with Python 3.9 version. Command- conda create --prefix ./env python=3.8 conda activate ./env 2.conda install -c apple tensorflow-deps. 3.python -m pip install tensorflow-macos==2.9 4.python -m pip install tensorflow-metal==0.5.0 5. Run sample script available on ht...