api
org.
jetbrains.
kotlinx.
dl.
api.
core
Functional
Graph
Trainable
Model
K
Graph
Saving
Format
J
S
O
N_
C
O
N
F
I
G_
C
U
S
T
O
M_
V
A
R
I
A
B
L
E
S
T
F_
G
R
A
P
H
T
F_
G
R
A
P
H_
C
U
S
T
O
M_
V
A
R
I
A
B
L
E
S
Sequential
Trainable
Model
Writing
Mode
A
P
P
E
N
D
F
A
I
L_
I
F_
E
X
I
S
T
S
O
V
E
R
R
I
D
E
org.
jetbrains.
kotlinx.
dl.
api.
core.
activation
Activation
Activations
Elu
Exponential
Hard
Sigmoid
Linear
Log
Softmax
Relu
Relu6
Selu
Sigmoid
Softmax
Soft
Plus
Soft
Sign
Swish
Tanh
Elu
Activation
Exponential
Activation
Hard
Sigmoid
Activation
Linear
Activation
Log
Softmax
Activation
Relu6
Activation
Relu
Activation
Selu
Activation
Sigmoid
Activation
Softmax
Activation
Soft
Plus
Activation
Soft
Sign
Activation
Swish
Activation
Tanh
Activation
org.
jetbrains.
kotlinx.
dl.
api.
core.
callback
Callback
Early
Stopping
Early
Stopping
Mode
A
U
T
O
M
A
X
M
I
N
Terminate
On
Na
N
org.
jetbrains.
kotlinx.
dl.
api.
core.
exception
Repeatable
Layer
Name
Exception
org.
jetbrains.
kotlinx.
dl.
api.
core.
history
Batch
Event
Batch
Training
Event
Epoch
Training
Event
History
Training
History
org.
jetbrains.
kotlinx.
dl.
api.
core.
initializer
Constant
Distribution
T
R
U
N
C
A
T
E
D_
N
O
R
M
A
L
U
N
I
F
O
R
M
U
N
T
R
U
N
C
A
T
E
D_
N
O
R
M
A
L
Glorot
Normal
Glorot
Uniform
He
Normal
He
Uniform
Initializer
Le
Cun
Normal
Le
Cun
Uniform
Mode
F
A
N_
A
V
G
F
A
N_
I
N
F
A
N_
O
U
T
Ones
Parametrized
Truncated
Normal
Random
Normal
Random
Uniform
Truncated
Normal
Variance
Scaling
Zeros
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer
Layer
No
Gradients
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
activation
Re
L
U
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
convolutional
Conv2
D
Conv
Padding
F
U
L
L
S
A
M
E
V
A
L
I
D
Depthwise
Conv2
D
Separable
Conv2
D
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
core
Activation
Layer
Dense
Input
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
merge
Abstract
Merge
Add
Average
Concatenate
Maximum
Minimum
Multiply
Subtract
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
normalization
Batch
Norm
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
pooling
Avg
Pool2
D
Global
Avg
Pool2
D
Max
Pool2
D
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
regularization
Dropout
org.
jetbrains.
kotlinx.
dl.
api.
core.
layer.
reshaping
Cropping2
D
Flatten
Reshape
Zero
Padding2
D
org.
jetbrains.
kotlinx.
dl.
api.
core.
loss
Binary
Cross
Entropy
Hinge
Huber
Log
Cosh
Losses
B
I
N
A
R
Y_
C
R
O
S
S
E
N
T
R
O
P
Y
H
I
N
G
E
H
U
B
E
R
L
O
G_
C
O
S
H
M
A
E
M
A
P
E
M
S
E
M
S
L
E
P
O
I
S
S
O
N
S
O
F
T_
M
A
X_
C
R
O
S
S_
E
N
T
R
O
P
Y_
W
I
T
H_
L
O
G
I
T
S
S
Q
U
A
R
E
D_
H
I
N
G
E
Loss
Function
M
A
E
M
A
P
E
M
S
E
M
S
L
E
Poisson
Reduction
Type
S
U
M
S
U
M_
O
V
E
R_
B
A
T
C
H_
S
I
Z
E
Softmax
Cross
Entropy
With
Logits
Squared
Hinge
org.
jetbrains.
kotlinx.
dl.
api.
core.
metric
Accuracy
Evaluation
Result
M
A
E
M
A
P
E
Metric
Metrics
A
C
C
U
R
A
C
Y
M
A
E
M
S
E
M
S
L
E
M
S
E
M
S
L
E
org.
jetbrains.
kotlinx.
dl.
api.
core.
model
resnet101()
resnet101
Light()
resnet101v2()
resnet101v2
Light()
resnet152()
resnet152
Light()
resnet152v2()
resnet152v2
Light()
resnet50()
resnet50
Light()
resnet50v2()
resnet50v2
Light()
vgg16()
vgg19()
org.
jetbrains.
kotlinx.
dl.
api.
core.
optimizer
Ada
Delta
Ada
Grad
Ada
Grad
D
A
Adam
Adamax
Clip
Gradient
Action
Clip
Gradient
By
Norm
Clip
Gradient
By
Value
Ftrl
Momentum
No
Clip
Gradient
Optimizer
R
M
S
Prop
S
G
D
org.
jetbrains.
kotlinx.
dl.
api.
core.
shape
reshape3
D
To1
D()
tail()
Tensor
Shape
org.
jetbrains.
kotlinx.
dl.
api.
core.
util
serialize
Labels
To
Buffer()
serialize
To
Buffer
T
F
org.
jetbrains.
kotlinx.
dl.
api.
extension
convert
Tensor
To
Flatten
Float
Array()
convert
Tensor
To
Multi
Dim
Array()
get2
D()
get3
D()
set2
D()
set3
D()
org.
jetbrains.
kotlinx.
dl.
api.
inference
Inference
Model
org.
jetbrains.
kotlinx.
dl.
api.
inference.
keras
Layer
Batch
Norm
Paths
Layer
Conv
Or
Dense
Paths
Layer
Paths
Layer
Separable
Conv2
D
Paths
load
Weights
load
Weights
By
Paths
load
Weights
By
Path
Templates
load
Weights
For
Frozen
Layers()
load
Weights
For
Frozen
Layers
By
Path
Templates()
Missed
Weights
Strategy
I
N
I
T
I
A
L
I
Z
E
L
O
A
D_
N
E
W_
F
O
R
M
A
T
recursive
Print
Group
In
H
D
F5
File()
save
Model
Configuration()
org.
jetbrains.
kotlinx.
dl.
api.
inference.
keras.
loaders
caffe
Style
Preprocessing()
Input
Type
C
A
F
F
E
T
F
T
O
R
C
H
Loading
Mode
O
V
E
R
R
I
D
E_
I
F_
E
X
I
S
T
S
S
K
I
P_
L
O
A
D
I
N
G_
I
F_
E
X
I
S
T
S
Model
Type
Mobile
Net
Mobile
Netv2
Res
Net_101
Res
Net_101_v2
Res
Net_151_v2
Res
Net_152
Res
Net_50
Res
Net_50_v2
V
G
G_16
V
G
G_19
Model
Zoo
predict
Top5
Labels()
prepare
Human
Readable
Class
Labels()
preprocess
Input()
reshape
Input()
torch
Style
Preprocessing()
org.
jetbrains.
kotlinx.
dl.
api.
inference.
savedmodel
Input
P
L
A
C
E
H
O
L
D
E
R
Output
A
R
G
M
A
X
Saved
Model
org.
jetbrains.
kotlinx.
dl.
dataset
cifar10
Paths()
Data
Batch
Dataset
dogs
Cats
Dataset
Path()
dogs
Cats
Small
Dataset
Path()
fashion
Mnist()
mnist()
On
Fly
Image
Dataset
On
Heap
Dataset
org.
jetbrains.
kotlinx.
dl.
dataset.
handler
extract
Cifar10
Images()
extract
Cifar10
Labels()
extract
Cifar10
Labels
Ans
Sort()
extract
Fashion
Images()
extract
Fashion
Labels()
extract
Images()
extract
Labels()
F
A
S
H
I
O
N_
T
E
S
T_
I
M
A
G
E
S_
A
R
C
H
I
V
E
F
A
S
H
I
O
N_
T
E
S
T_
L
A
B
E
L
S_
A
R
C
H
I
V
E
F
A
S
H
I
O
N_
T
R
A
I
N_
I
M
A
G
E
S_
A
R
C
H
I
V
E
F
A
S
H
I
O
N_
T
R
A
I
N_
L
A
B
E
L
S_
A
R
C
H
I
V
E
N
U
M
B
E
R_
O
F_
C
L
A
S
S
E
S
T
E
S
T_
I
M
A
G
E
S_
A
R
C
H
I
V
E
T
E
S
T_
L
A
B
E
L
S_
A
R
C
H
I
V
E
T
R
A
I
N_
I
M
A
G
E
S_
A
R
C
H
I
V
E
T
R
A
I
N_
L
A
B
E
L
S_
A
R
C
H
I
V
E
org.
jetbrains.
kotlinx.
dl.
dataset.
image
Color
Order
B
G
R
R
G
B
Image
Converter
org.
jetbrains.
kotlinx.
dl.
dataset.
preprocessor
Image
Shape
preprocess()
Preprocessing
Preprocessor
rescale()
Rescaling
Sharpen
sharpen()
Tensor
Preprocessing
transform
Image()
transform
Tensor()
org.
jetbrains.
kotlinx.
dl.
dataset.
preprocessor.
generator
From
Folders
Label
Generator
org.
jetbrains.
kotlinx.
dl.
dataset.
preprocessor.
image
crop()
Cropping
Image
Preprocessing
Image
Preprocessor
Interpolation
Type
B
I
C
U
B
I
C
B
I
L
I
N
E
A
R
N
E
A
R
E
S
T
load()
Loading
Rendering
Speed
F
A
S
T
M
E
D
I
U
M
S
L
O
W
Resize
resize()
Rotate
rotate()
Save
save()
examples
[root]
Le
Net
Classic
examples.
cnn.
cifar10
main()
vgg()
examples.
cnn.
dogscats
main
resnet101on
Dogs
Vs
Cats
Dataset()
resnet101v2on
Dogs
Vs
Cats
Dataset()
resnet152on
Dogs
Vs
Cats
Dataset()
resnet152v2on
Dogs
Vs
Cats
Dataset()
resnet50on
Dogs
Vs
Cats
Dataset()
resnet50v2on
Dogs
Vs
Cats
Dataset()
examples.
cnn.
fashionmnist
main
resnet50
On
Fashion
Mnist
Dataset()
vgg()
examples.
cnn.
mnist
dense
Only()
lenet
Classic()
lenet
With
Alternative
Loss
Function()
lenet
With
Early
Stopping
Callback()
main
modern
Lenet()
vgg()
examples.
custom
Custom
Callback
lenet
Mnist
With
Custom
Callback()
main()
examples.
dataset
Images
J
Panel3
main
examples.
experimental.
batchnorm
get
J
S
O
N
Config
File()
get
Weights
File()
main
examples.
inference
lenet5()
examples.
inference.
fashionmnist
lenet
On
Fashion
Mnist
Export
Import
To
Txt()
main
examples.
inference.
mnist
lenet
On
Mnist
Dataset
Export
Import
To
Txt()
lenet
On
Mnist
Export
Import
To
Json()
main
examples.
inference.
optimizers
lenet
On
Mnist
Export
Import
To
J
S
O
N
With
Adam
Optimizer
State()
main()
examples.
inference.
savedmodel
lenet
On
Mnist
Inference()
lenet
On
Mnist
Inference
With
Tensor
Names()
main
print
Out
Graph
Ops()
examples.
ml
iris
Classification()
linear
Regression()
main
examples.
transferlearning.
lenet
additional
Training()
additional
Training
And
Freezing()
additional
Training
And
New
Top
Dense
Layers()
additional
Training
And
Partial
Freezing
And
Partial
Initialization()
get
J
S
O
N
Config
File()
get
Weights
File()
load
Model
Without
Weights
Init
And
Evaluate()
load
Model
With
Weights
And
Evaluate()
main
examples.
transferlearning.
modelzoo.
mobilenet
main
mobile
Net
Prediction()
mobile
Net
V2
Prediction()
mobilenet
With
Additional
Training()
examples.
transferlearning.
modelzoo.
resnet
main
resnet101prediction()
resnet101v2prediction()
resnet152prediction()
resnet152v2prediction()
resnet50v2prediction()
examples.
transferlearning.
modelzoo.
resnet.
resnet50
main
resnet50additional
Training()
resnet50prediction()
examples.
transferlearning.
modelzoo.
vgg16
get
File
From
Resource()
main
vgg16prediction()
examples.
transferlearning.
modelzoo.
vgg19
main
vgg19additional
Training()
vgg19prediction()
examples.
transferlearning.
toyresnet
get
Toy
Res
Net
J
S
O
N
Config
File()
get
Toy
Res
Net
Weights
File()
main
examples.
visualisation
Conv2d
J
Panel
Conv2d
J
Panel1
draw
Activations()
draw
Filters()
main
Relu
Graphics
Relu
Graphics2
api
/
org.jetbrains.kotlinx.dl.dataset
/
Dataset
Dataset
abstract class
Dataset
Content copied to clipboard
Just abstract Dataset.
Types
Constructors
Functions
Inheritors
Constructors
Dataset
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fun
Dataset
()
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On this page
On this page
Types
BatchIterator
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inner class
BatchIterator
:
Iterator
<
DataBatch
?>
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An iterator over a
Dataset
.
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Functions
batchIterator
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fun
batchIterator
(batchSize:
Int
):
Dataset.BatchIterator
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Returns
BatchIterator
with fixed
batchSize
.
getX
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abstract fun
getX
(idx:
Int
):
FloatArray
Content copied to clipboard
Returns row by index
idx
.
getY
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abstract fun
getY
(idx:
Int
):
Float
Content copied to clipboard
Returns label as
Int
by index
idx
.
shuffle
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abstract fun
shuffle
():
Dataset
Content copied to clipboard
Shuffles the dataset.
split
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abstract fun
split
(splitRatio:
Double
):
Pair
<
Dataset
,
Dataset
>
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Splits datasets on two sub-datasets according
splitRatio
.
xSize
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abstract fun
xSize
():
Int
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Returns amount of data rows.
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Inheritors
OnFlyImageDataset
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OnHeapDataset
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