stable
Table of Contents
1. Documentation Variations
2. The Open Software License 3.0 (OSL-3.0)
3. Fully Homomorphic Encryption
4. Installation
5. Examples
6. Neural Network
7. Traversal
8. Layers
9. Activations
10. Optimisers
11. Loss Functions
12. Operations
Python-FHEz
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Index
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Index
A
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B
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C
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D
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E
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F
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G
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H
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I
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L
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M
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N
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O
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P
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Q
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R
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S
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U
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W
A
Adam (class in fhez.nn.optimiser.adam)
adaptation() (fhez.nn.traverse.firing.Firing method)
alpha (fhez.nn.optimiser.adam.Adam property)
ANN (class in fhez.nn.layer.ann)
Argmax (class in fhez.nn.activation.argmax)
B
b (fhez.nn.layer.ann.ANN property)
(fhez.nn.operations.cc.CC property)
backward() (fhez.nn.activation.argmax.Argmax method)
(fhez.nn.activation.linear.Linear method)
(fhez.nn.activation.relu.RELU method)
(fhez.nn.activation.sigmoid.Sigmoid method)
(fhez.nn.activation.softmax.Softmax method)
(fhez.nn.graph.node.Node method)
(fhez.nn.layer.ann.ANN method)
(fhez.nn.loss.cce.CCE method)
(fhez.nn.loss.loss.Loss method)
(fhez.nn.loss.mae.MAE method)
(fhez.nn.loss.mse.MSE method)
(fhez.nn.nn.NeuralNetwork method)
(fhez.nn.operations.cc.CC method)
(fhez.nn.operations.decrypt.Decrypt method)
(fhez.nn.operations.dequeue.Dequeue method)
(fhez.nn.operations.encrypt.Encrypt method)
(fhez.nn.operations.enqueue.Enqueue method)
(fhez.nn.operations.one_hot_decode.OneHotDecode method)
(fhez.nn.operations.one_hot_encode.OneHotEncode method)
(fhez.nn.operations.sum.Sum method)
backwards() (fhez.nn.graph.node.Node method)
(fhez.nn.nn.NeuralNetwork method)
beta_1 (fhez.nn.optimiser.adam.Adam property)
beta_2 (fhez.nn.optimiser.adam.Adam property)
bias (fhez.nn.layer.ann.ANN property)
(fhez.nn.operations.cc.CC property)
C
c (fhez.nn.activation.linear.Linear property)
cache (fhez.nn.graph.node.Node property)
(fhez.nn.loss.loss.Loss property)
(fhez.nn.optimiser.adam.Adam property)
CategoricalCrossEntropy (in module fhez.nn.loss.cce)
CC (class in fhez.nn.operations.cc)
CCE (class in fhez.nn.loss.cce)
correction() (fhez.nn.traverse.firing.Firing method)
cost (fhez.nn.activation.argmax.Argmax property)
(fhez.nn.activation.linear.Linear property)
(fhez.nn.activation.relu.RELU property)
(fhez.nn.activation.sigmoid.Sigmoid property)
(fhez.nn.activation.softmax.Softmax property)
(fhez.nn.graph.node.Node property)
(fhez.nn.layer.ann.ANN property)
(fhez.nn.loss.mse.MSE property)
(fhez.nn.operations.cc.CC property)
(fhez.nn.operations.decrypt.Decrypt property)
(fhez.nn.operations.dequeue.Dequeue property)
(fhez.nn.operations.encrypt.Encrypt property)
(fhez.nn.operations.enqueue.Enqueue property)
(fhez.nn.operations.one_hot_decode.OneHotDecode property)
(fhez.nn.operations.one_hot_encode.OneHotEncode property)
(fhez.nn.operations.sum.Sum property)
cost() (fhez.nn.loss.mae.MAE method)
D
Decrypt (class in fhez.nn.operations.decrypt)
Dequeue (class in fhez.nn.operations.dequeue)
disable_cache() (fhez.nn.graph.node.Node method)
(fhez.nn.loss.loss.Loss method)
E
enable_cache() (fhez.nn.graph.node.Node method)
(fhez.nn.loss.loss.Loss method)
Encrypt (class in fhez.nn.operations.encrypt)
Enqueue (class in fhez.nn.operations.enqueue)
epsilon (fhez.nn.optimiser.adam.Adam property)
F
fhez.nn.activation.softmax
module
fhez.nn.layer.ann
module
fhez.nn.layer.cnn
module
fhez.nn.loss.cce
module
fhez.nn.loss.loss
module
fhez.nn.loss.mae
module
fhez.nn.loss.mse
module
fhez.nn.operations.cc
module
fhez.nn.operations.decrypt
module
fhez.nn.operations.dequeue
module
fhez.nn.operations.encrypt
module
fhez.nn.operations.enqueue
module
fhez.nn.operations.one_hot_decode
module
fhez.nn.operations.one_hot_encode
module
fhez.nn.operations.sum
module
fhez.nn.traverse.firing
module
Firing (class in fhez.nn.traverse.firing)
forward() (fhez.nn.activation.argmax.Argmax method)
(fhez.nn.activation.linear.Linear method)
(fhez.nn.activation.relu.RELU method)
(fhez.nn.activation.sigmoid.Sigmoid method)
(fhez.nn.activation.softmax.Softmax method)
(fhez.nn.graph.node.Node method)
(fhez.nn.layer.ann.ANN method)
(fhez.nn.loss.cce.CCE method)
(fhez.nn.loss.loss.Loss method)
(fhez.nn.loss.mae.MAE method)
(fhez.nn.loss.mse.MSE method)
(fhez.nn.nn.NeuralNetwork method)
(fhez.nn.operations.cc.CC method)
(fhez.nn.operations.decrypt.Decrypt method)
(fhez.nn.operations.dequeue.Dequeue method)
(fhez.nn.operations.encrypt.Encrypt method)
(fhez.nn.operations.enqueue.Enqueue method)
(fhez.nn.operations.one_hot_decode.OneHotDecode method)
(fhez.nn.operations.one_hot_encode.OneHotEncode method)
(fhez.nn.operations.sum.Sum method)
forwards() (fhez.nn.graph.node.Node method)
(fhez.nn.nn.NeuralNetwork method)
G
g (fhez.nn.nn.NeuralNetwork property)
GD (class in fhez.nn.optimiser.gd)
gradients (fhez.nn.graph.node.Node property)
graph (fhez.nn.traverse.firing.Firing property)
H
harvest() (fhez.nn.traverse.firing.Firing method)
I
inputs (fhez.nn.graph.node.Node property)
(fhez.nn.loss.loss.Loss property)
is_cache_enabled (fhez.nn.graph.node.Node property)
(fhez.nn.loss.loss.Loss property)
L
length (fhez.nn.operations.dequeue.Dequeue property)
(fhez.nn.operations.enqueue.Enqueue property)
(fhez.nn.operations.one_hot_encode.OneHotEncode property)
Linear (class in fhez.nn.activation.linear)
local_dfdq() (fhez.nn.activation.relu.RELU method)
local_dfdx() (fhez.nn.activation.relu.RELU method)
Loss (class in fhez.nn.loss.loss)
loss() (fhez.nn.loss.cce.CCE method)
M
m (fhez.nn.activation.linear.Linear property)
MAE (class in fhez.nn.loss.mae)
module
fhez.nn.activation.softmax
fhez.nn.layer.ann
fhez.nn.layer.cnn
fhez.nn.loss.cce
fhez.nn.loss.loss
fhez.nn.loss.mae
fhez.nn.loss.mse
fhez.nn.operations.cc
fhez.nn.operations.decrypt
fhez.nn.operations.dequeue
fhez.nn.operations.encrypt
fhez.nn.operations.enqueue
fhez.nn.operations.one_hot_decode
fhez.nn.operations.one_hot_encode
fhez.nn.operations.sum
fhez.nn.traverse.firing
momentum() (fhez.nn.optimiser.adam.Adam method)
MSE (class in fhez.nn.loss.mse)
N
NeuralNetwork (class in fhez.nn.nn)
NeuronalFiring (in module fhez.nn.traverse.firing)
NN (in module fhez.nn.nn)
Node (class in fhez.nn.graph.node)
O
OneHotDecode (class in fhez.nn.operations.one_hot_decode)
OneHotEncode (class in fhez.nn.operations.one_hot_encode)
optimise() (fhez.nn.optimiser.adam.Adam method)
optimiser (fhez.nn.activation.linear.Linear property)
(fhez.nn.graph.node.Node property)
P
parameters (fhez.nn.operations.encrypt.Encrypt property)
probe_shape() (fhez.nn.graph.node.Node method)
(fhez.nn.nn.NeuralNetwork method)
(fhez.nn.operations.cc.CC method)
(fhez.nn.traverse.firing.Firing method)
provider (fhez.nn.operations.encrypt.Encrypt property)
Q
q (fhez.nn.activation.relu.RELU property)
queue (fhez.nn.operations.dequeue.Dequeue property)
(fhez.nn.operations.enqueue.Enqueue property)
R
ReCache (class in fhez.recache)
RELU (class in fhez.nn.activation.relu)
ReScheme (class in fhez.rescheme)
rmsprop() (fhez.nn.optimiser.adam.Adam method)
S
schema (fhez.nn.activation.linear.Linear property)
(fhez.nn.operations.cc.CC property)
(fhez.nn.operations.one_hot_decode.OneHotDecode property)
(fhez.nn.operations.one_hot_encode.OneHotEncode property)
(fhez.nn.optimiser.adam.Adam property)
Sigmoid (class in fhez.nn.activation.sigmoid)
sigmoid() (fhez.nn.activation.sigmoid.Sigmoid method)
Softmax (class in fhez.nn.activation.softmax)
stimulate() (fhez.nn.traverse.firing.Firing method)
stride (fhez.nn.operations.cc.CC property)
Sum (class in fhez.nn.operations.sum)
U
update() (fhez.nn.activation.argmax.Argmax method)
(fhez.nn.activation.linear.Linear method)
(fhez.nn.activation.relu.RELU method)
(fhez.nn.activation.sigmoid.Sigmoid method)
(fhez.nn.activation.softmax.Softmax method)
(fhez.nn.graph.node.Node method)
(fhez.nn.layer.ann.ANN method)
(fhez.nn.loss.loss.Loss method)
(fhez.nn.loss.mae.MAE method)
(fhez.nn.loss.mse.MSE method)
(fhez.nn.nn.NeuralNetwork method)
(fhez.nn.operations.cc.CC method)
(fhez.nn.operations.decrypt.Decrypt method)
(fhez.nn.operations.dequeue.Dequeue method)
(fhez.nn.operations.encrypt.Encrypt method)
(fhez.nn.operations.enqueue.Enqueue method)
(fhez.nn.operations.one_hot_decode.OneHotDecode method)
(fhez.nn.operations.one_hot_encode.OneHotEncode method)
(fhez.nn.operations.sum.Sum method)
updater() (fhez.nn.graph.node.Node method)
updates() (fhez.nn.activation.argmax.Argmax method)
(fhez.nn.activation.linear.Linear method)
(fhez.nn.activation.relu.RELU method)
(fhez.nn.activation.sigmoid.Sigmoid method)
(fhez.nn.activation.softmax.Softmax method)
(fhez.nn.graph.node.Node method)
(fhez.nn.layer.ann.ANN method)
(fhez.nn.loss.loss.Loss method)
(fhez.nn.loss.mae.MAE method)
(fhez.nn.loss.mse.MSE method)
(fhez.nn.nn.NeuralNetwork method)
(fhez.nn.operations.cc.CC method)
(fhez.nn.operations.decrypt.Decrypt method)
(fhez.nn.operations.dequeue.Dequeue method)
(fhez.nn.operations.encrypt.Encrypt method)
(fhez.nn.operations.enqueue.Enqueue method)
(fhez.nn.operations.one_hot_decode.OneHotDecode method)
(fhez.nn.operations.one_hot_encode.OneHotEncode method)
(fhez.nn.operations.sum.Sum method)
W
w (fhez.nn.layer.ann.ANN property)
(fhez.nn.operations.cc.CC property)
weights (fhez.nn.layer.ann.ANN property)
(fhez.nn.operations.cc.CC property)
windex() (fhez.nn.operations.cc.CC method)
windex_to_slice() (fhez.nn.operations.cc.CC method)
windows (fhez.nn.operations.cc.CC property)
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