ChainerWhat is Chainer?
It is an open source deep learning framework written purely in Python on top of Numpy and CuPy Python libraries aiming at flexibility. It supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
Chainer is a tool in the Development & Training Tools category of a tech stack.
Key Features
Supports CUDA computationRuns on multiple GPUsSupports various network architecturesSupports per-batch architectures
Chainer Pros & Cons
Pros of Chainer
No pros listed yet.
Cons of Chainer
No cons listed yet.
Chainer Alternatives & Comparisons
What are some alternatives to Chainer?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
