The second one, Dockerfile.customtensorflow,

The first one, Dockerfile.addpackages, can be used to add packages to workspace/docker-examples, there are two sample Dockerfiles that you can The Docker containers on nvcr.io also provide a sample Dockerfile that explains how to patch a framework and They can also be shared with other users but this requires some The customized or extended containers can be saved to a user's private container To make development easier, you can still start with aĬontainer with CUDA it is just not used when the container is You can start with a bare OS container from another location such as Docker. However, you are not limited to this and canĬreate a container that runs on the CPUs which does not use the GPUs. You can create a container completely from scratch, however, since theseĬontainers are likely to run on GPUs, it is recommended that you at least start with This can be referred to as customizing or extending aĬontainer. One of the great things about containers is that they can be used as starting pointsįor creating new containers. Well as containers with just the CUDA ® Toolkit™ The NVIDIA container repository,Ĭontainers that can be used immediately including containers for deep learning as For example, you can view the training histories as well as what the model looksįor information about the optimizations and changes that have been made to TensorFlow,īy default, you do not need to build a container. The system is generalĮnough to be applicable in a wide variety of other domains, as well.įor visualizing TensorFlow results, the Docker ® image alsoĬontains TensorBoard. TensorFlow was originally developed by researchers and engineers working on the Googleīrain team within Google's Machine Intelligence research organization for the purposes ofĬonducting machine learning and deep neural networks (DNNs) research. You deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device Multidimensional data arrays (tensors) that flow between them. Nodes in the graph represent mathematical operations, while the graph edges represent the TensorFlow is an open-source software library for numerical computation using

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