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
Image Classification with Pre-trained Model
Networks
Overview
Network Architecture
Layer Implementation
Mocha Network Topology Tips
Layers
Overview
Data Layers
Computation Layers
Loss Layers
Statistics Layers
Utility Layers
Neurons (Activation Functions)
Initializers
Regularizers
Data Transformers
Solvers
General Solver Parameters
Solver Algorithms
Solver Coffee Breaks
Mocha Backends
Pure Julia CPU Backend
CPU Backend with Native Extension
CUDA Backend
Tools
Importing Trained Model from Caffe
Image Classifier
Blob
Mocha
Docs
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Edit on GitHub
Index
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
K
|
L
|
M
|
N
|
O
|
P
|
R
|
S
|
T
|
V
|
W
|
X
A
AccuracyLayer (built-in class)
ArgmaxLayer (built-in class)
B
batch_size (HDF5DataLayer attribute)
(MemoryDataLayer attribute)
bias_init (ConvolutionLayer attribute)
(InnerProductLayer attribute)
bias_lr (ConvolutionLayer attribute)
(InnerProductLayer attribute)
bias_regu (ConvolutionLayer attribute)
(InnerProductLayer attribute)
bottoms (AccuracyLayer attribute)
(ArgmaxLayer attribute)
(ChannelPoolingLayer attribute)
(ConcatLayer attribute)
(ConvolutionLayer attribute)
(CropLayer attribute)
(DropoutLayer attribute)
(ElementWiseLayer attribute)
(HDF5OutputLayer attribute)
(InnerProductLayer attribute)
(LRNLayer attribute)
(MultinomialLogisticLossLayer attribute)
(PoolingLayer attribute)
(PowerLayer attribute)
(ReshapeLayer attribute)
(SoftmaxLayer attribute)
(SoftmaxLossLayer attribute)
(SplitLayer attribute)
C
ChannelPoolingLayer (built-in class)
channels (ReshapeLayer attribute)
ConcatLayer (built-in class)
ConstantInitializer (built-in class)
ConvolutionLayer (built-in class)
crop_size (CropLayer attribute)
CropLayer (built-in class)
D
data (MemoryDataLayer attribute)
datasets (HDF5OutputLayer attribute)
DataTransformers.Scale (built-in class)
DataTransformers.SubMean (built-in class)
dim (ConcatLayer attribute)
DropoutLayer (built-in class)
E
ElementWiseLayer (built-in class)
F
filename (HDF5OutputLayer attribute)
filter_init (ConvolutionLayer attribute)
filter_lr (ConvolutionLayer attribute)
filter_regu (ConvolutionLayer attribute)
force_overwrite (HDF5OutputLayer attribute)
G
GaussianInitializer (built-in class)
H
HDF5DataLayer (built-in class)
HDF5OutputLayer (built-in class)
height (ReshapeLayer attribute)
I
InnerProductLayer (built-in class)
K
kernel (ChannelPoolingLayer attribute)
(ConvolutionLayer attribute)
(LRNLayer attribute)
(PoolingLayer attribute)
L
L1Regu (built-in class)
L2Regu (built-in class)
load_from (SolverParameters attribute)
lr_policy (SolverParameters attribute)
LRNLayer (built-in class)
LRPolicy.Exp (built-in class)
LRPolicy.Fixed (built-in class)
LRPolicy.Inv (built-in class)
LRPolicy.Staged (built-in class)
LRPolicy.Step (built-in class)
M
max_iter (SolverParameters attribute)
mean (GaussianInitializer attribute)
mean_blob (DataTransformers.SubMean attribute)
mean_file (DataTransformers.SubMean attribute)
MemoryDataLayer (built-in class)
mode (LRNLayer attribute)
mom_policy (SolverParameters attribute)
MomPolicy.Fixed (built-in class)
MomPolicy.Linear (built-in class)
MomPolicy.Step (built-in class)
MultinomialLogisticLossLayer (built-in class)
N
n_filter (ConvolutionLayer attribute)
n_group (ConvolutionLayer attribute)
Nesterov (built-in class)
neuron (ConvolutionLayer attribute)
(InnerProductLayer attribute)
Neurons.Identity (built-in class)
Neurons.ReLU (built-in class)
Neurons.Sigmoid (built-in class)
NoRegu (built-in class)
normalize (MultinomialLogisticLossLayer attribute)
(SoftmaxLossLayer attribute)
NullInitializer (built-in class)
O
operation (ElementWiseLayer attribute)
output_dim (InnerProductLayer attribute)
P
pad (ChannelPoolingLayer attribute)
(ConvolutionLayer attribute)
(PoolingLayer attribute)
pooling (ChannelPoolingLayer attribute)
(PoolingLayer attribute)
PoolingLayer (built-in class)
power (LRNLayer attribute)
(PowerLayer attribute)
PowerLayer (built-in class)
R
random_crop (CropLayer attribute)
random_mirror (CropLayer attribute)
ratio (DropoutLayer attribute)
regu_coef (SolverParameters attribute)
ReshapeLayer (built-in class)
S
scale (DataTransformers.Scale attribute)
(LRNLayer attribute)
(PowerLayer attribute)
SGD (built-in class)
shift (LRNLayer attribute)
(PowerLayer attribute)
shuffle (HDF5DataLayer attribute)
Snapshot (built-in class)
SoftmaxLayer (built-in class)
SoftmaxLossLayer (built-in class)
SolverParameters (built-in class)
source (HDF5DataLayer attribute)
SplitLayer (built-in class)
std (GaussianInitializer attribute)
stride (ChannelPoolingLayer attribute)
(ConvolutionLayer attribute)
(PoolingLayer attribute)
T
tops (ArgmaxLayer attribute)
(ChannelPoolingLayer attribute)
(ConcatLayer attribute)
(ConvolutionLayer attribute)
(CropLayer attribute)
(ElementWiseLayer attribute)
(HDF5DataLayer attribute)
(InnerProductLayer attribute)
(LRNLayer attribute)
(MemoryDataLayer attribute)
(PoolingLayer attribute)
(PowerLayer attribute)
(ReshapeLayer attribute)
(SoftmaxLayer attribute)
(SplitLayer attribute)
TrainingSummary (built-in class)
transformers (HDF5DataLayer attribute)
(MemoryDataLayer attribute)
V
ValidationPerformance (built-in class)
value (ConstantInitializer attribute)
W
weight_init (InnerProductLayer attribute)
weight_lr (InnerProductLayer attribute)
weight_regu (InnerProductLayer attribute)
weights (MultinomialLogisticLossLayer attribute)
(SoftmaxLossLayer attribute)
width (ReshapeLayer attribute)
X
XavierInitializer (built-in class)
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