sagemaker-distribution
libtensorflow_cc
sagemaker-distribution | libtensorflow_cc | |
---|---|---|
1 | 1 | |
74 | 50 | |
- | - | |
9.2 | 7.5 | |
5 days ago | 4 months ago | |
Dockerfile | Dockerfile | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sagemaker-distribution
libtensorflow_cc
-
[P] libtensorflow_cc: Pre-built TensorFlow C++ API
git clone https://github.com/ika-rwth-aachen/libtensorflow_cc.git && \ cd libtensorflow_cc && \ docker run --rm \ --volume $(pwd)/example:/example \ --workdir /example \ rwthika/tensorflow-cc:latest \ ./build-and-run.sh
What are some alternatives?
blender-docker-cli - :monkey_face: Blender in :whale: Docker
cppflow - Run TensorFlow models in C++ without installation and without Bazel
sagemaker-tensorflow-training-toolkit - Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.
dockerdl - Deep Learning Docker Image
oneAPI-samples - Samples for Intel® oneAPI Toolkits
amp-devcontainer - amp-devcontainer is a fully loaded devcontainer useable for, embedded, C++ or Rust development
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
tensorflow_cpp - Helpful model wrappers around TensorFlow C++ API
cresset - Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
tensorflow - An Open Source Machine Learning Framework for Everyone
sagemaker-python-sdk - A library for training and deploying machine learning models on Amazon SageMaker
sagemaker-training-toolkit - Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.