Search Results for "python framework"

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,...

Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies...

PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly...

SageMaker Chainer Containers is an open-source library for making the Chainer framework run on Amazon SageMaker. This repository also contains Dockerfiles which install this library, Chainer, and dependencies for building SageMaker Chainer images. Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python version and processor type. ...

...Model: Database Model(like Table/View), Java POJO Model, Xml File Model and includes Transform/Mapping/Convert Tool Action: A Java Class can set Java variables to template. Support any kind of project Maven, Gradle, Web, Java, Android, PHP, Python etc. Support any kind of framework spring/springMVC, hibernate, ibatis/mybatis, struts/struts2, JPA etc. Support any kind of language Java the best.

...Register here: https://docs.google.com/forms/d/12tAH4f8CJ-3F-lK44Q9uQHFio_mGoK0oY829q5lD7i4/viewform GillesPy is a python interface for developing models and simulating them with StochKit. Please see: https://github.com/GillesPy/gillespy/ StochKit currently supports Linux, Windows, and OS X.

The Location Containment Object Model(LCOM) is a simulation framework written in Python. LCOM provides a rule-based solution to handling partial object containment, object migration, message passing, and simulation observation.

An AToM3 definition of a CASE framework for creating Zope products with files in the filesystem. The framework consists of a modelling notation ZProduct and a suit of related transformations.