Mocha
Training LeNet on MNIST
Preparing the Data
Defining the Network Architecture
Configuring Backend and Building Network
Configuring Solver
Coffee Breaks for the Solver
Training
Remarks
Alex’s CIFAR-10 tutorial in Mocha
Caffe’s Tutorial and Code
Preparing the Data
Computation and Loss Layers
Constructing the Network
Configuring the Solver
Training
Networks
Overview
Network Architecture
Layer Implementation
Layers
Overview
Data Layers
Computation Layers
Loss Layers
Neurons (Activation Functions)
Initializers
Regularizers
Solvers
Mocha Backends
Pure Julia CPU Backend
CPU Backend with Native Extension
CUDA Backend
Tools
Importing Trained Model from Caffe
Blob
Mocha
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Mocha Documentation
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Mocha Documentation
¶
Mocha
is a Deep Learning framework for
Julia
.
Tutorials
¶
Training LeNet on MNIST
Preparing the Data
Defining the Network Architecture
Configuring Backend and Building Network
Configuring Solver
Coffee Breaks for the Solver
Training
Remarks
Alex’s CIFAR-10 tutorial in Mocha
Caffe’s Tutorial and Code
Preparing the Data
Computation and Loss Layers
Constructing the Network
Configuring the Solver
Training
User’s Guide
¶
Networks
Overview
Network Architecture
Layer Implementation
Layers
Overview
Data Layers
Computation Layers
Loss Layers
Neurons (Activation Functions)
Initializers
Regularizers
Solvers
Mocha Backends
Pure Julia CPU Backend
CPU Backend with Native Extension
CUDA Backend
Tools
Importing Trained Model from Caffe
Developer’s Guide
¶
Blob
Indices and tables
¶
Index
Module Index
Search Page
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