Chainer
v3.0.0
Installation Guide
Chainer Tutorial
Introduction to Chainer
How to Write a New Network
How to Train a Network
Using GPU(s) in Chainer
Define your own function
Type check
Chainer Reference Manual
Upgrade Guide from v1 to v2
Contribution Guide
API Compatibility Policy
Tips and FAQs
Comparison with Other Frameworks
License
Chainer
Docs
»
Chainer Tutorial
Edit on GitHub
Chainer Tutorial
ΒΆ
Introduction to Chainer
Core Concept
Forward/Backward Computation
Links
Write a model as a chain
Optimizer
Trainer
Serializer
Example: Multi-layer Perceptron on MNIST
How to Write a New Network
Convolutional Network for Visual Recognition Tasks
Recurrent Nets and their Computational Graph
How to Train a Network
How to write a training loop in Chainer
Using GPU(s) in Chainer
Relationship between Chainer and CuPy
Basics of
cupy.ndarray
Run Neural Networks on a Single GPU
Model-parallel Computation on Multiple GPUs
Data-parallel Computation on Multiple GPUs with Trainer
Data-parallel Computation on Multiple GPUs without Trainer
Define your own function
Differentiable Functions
Unified forward/backward methods with NumPy/CuPy functions
Write an Elementwise Kernel Function
Write a function with training/test mode
Links that wrap functions
Testing Function
Type check
Basic usage of type check
Detail of type information
Internal mechanism of type check
More powerful methods
Call functions
More complicated cases
Typical type check example
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v: v3.0.0
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