earlier container versions, refer to the Frameworks Support Matrix. Container Version Ubuntu CUDA Toolkit PyTorch TensorRT 23.07 2.1.0a0+b5021ba 23.06 2.1.0a0+4136153 TensorRT 8.6.1.6 23.05 22.04 NVIDIA 8.2.3 PyTorch Release 23.07 PyTorch RN-08516-001_v23.07 | 8 Container Version Ubuntu CUDA Toolkit PyTorch TensorRT 22.02 1.11.0a0+17540c5cTensorRT 8.2.3 22.01 NVIDIA CUDA 11.6.0 1.11.0a0+bfe5ad28TensorRT 7.0.0 PyTorch Release 23.07 PyTorch RN-08516-001_v23.07 | 9 Container Version Ubuntu CUDA Toolkit PyTorch TensorRT 20.01 1.4.0a0+a5b4d78 19.12 19.11 1.4.0a0+174e1ba 19.10 1.3.0a0+24ae9b5 19

model weights Similar to what we did in sparsity, we will use the Tensorflow Model Optimization Toolkit (TFMOT) library to cluster our model’s weights. Installing the library is fairly simple as we saw

modules, functions and variables that will be used later on. It initializes the Natural Language Toolkit (NLTK) and creates a text sequence from a sentence. from random import choice, randint from keras

Keras Keras runs on top of open source machine libraries like TensorFlow, Theano or Cognitive Toolkit (CNTK). Theano is a python library used for fast numerical computation tasks. TensorFlow is the

我们在这里下载CUDA 10.1。访问NVIDIA的官方存储库216 以找到下载链接，如 图16.3.11中所示。 216 https://developer.nvidia.com/cuda‐toolkit‐archive 16.3. 使用Amazon EC2实例 755 图16.3.11: 查找CUDA 10.1下载地址 将说明复制粘贴到终端上，以安装CUDA 10.1。 # 链接和文件