NeoML
latest
Submodules
neoml.Dnn
neoml.Clustering
neoml.ClassificationRegression
neoml.MathEngine
neoml.Algorithms
Tutorials
Neural network for CIFAR-10
Identity recurrent neural network (IRNN)
Neural network with custom loss function
Linear classifier
k
-means clustering
Linear regressor
Gradient tree boosting classifier
Porting neural networks
NeoML
Index
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Index
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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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K
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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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T
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U
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V
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W
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X
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Z
A
Abs (class in neoml.Dnn)
abs() (neoml.AutoDiff method)
AccumulativeLookup (class in neoml.Dnn)
Accuracy (class in neoml.Dnn)
activation (neoml.Dnn.IndRnn property)
(neoml.Dnn.Lstm property)
(neoml.Dnn.Qrnn property)
AdaptiveGradient (class in neoml.Dnn)
add() (neoml.AutoDiff method)
add_layer() (neoml.Dnn.Dnn method)
addends (neoml.Dnn.PositionalEmbedding property)
alpha (neoml.Dnn.ELU property)
(neoml.Dnn.LeakyReLU property)
(neoml.Dnn.Lrn property)
ams_grad (neoml.Dnn.AdaptiveGradient property)
(neoml.Dnn.NesterovGradient property)
apply_batch_normalization() (neoml.Dnn.ChannelwiseConv method)
(neoml.Dnn.Conv method)
(neoml.Dnn.Conv3D method)
(neoml.Dnn.FullyConnected method)
(neoml.Dnn.TransposedConv method)
(neoml.Dnn.TransposedConv3D method)
apply_softmax (neoml.Dnn.CrossEntropyLoss property)
arc_threshold (neoml.Dnn.CtcDecoding property)
area (neoml.Dnn.Softmax property)
Argmax (class in neoml.Dnn)
asarray() (neoml.Blob.Blob method)
asblob() (neoml.Blob method)
AttentionDecoder (class in neoml.Dnn)
B
BaseTraits (class in neoml.DifferentialEvolution)
batch_len (neoml.Blob.Blob property)
batch_width (neoml.Blob.Blob property)
(neoml.Dnn.CtcDecoding property)
BatchNormalization (class in neoml.Dnn)
batchwise (neoml.Dnn.Dropout property)
BestSequence (class in neoml.Dnn)
beta (neoml.Dnn.Lrn property)
bias (neoml.Dnn.HardSigmoid property)
(neoml.Dnn.IndRnn property)
(neoml.Dnn.Lrn property)
(neoml.Dnn.ObjectNormalization property)
binary_cross_entropy() (neoml.AutoDiff method)
BinaryCrossEntropyLoss (class in neoml.Dnn)
BinaryFocalLoss (class in neoml.Dnn)
bit_set_size (neoml.Dnn.BitSetVectorization property)
BitSetVectorization (class in neoml.Dnn)
blank (neoml.Dnn.CtcDecoding property)
(neoml.Dnn.CtcLoss property)
blank_threshold (neoml.Dnn.CtcDecoding property)
Blob (class in neoml.Blob)
build_next_generation() (neoml.DifferentialEvolution.DifferentialEvolution method)
BytePairEncoder (in module neoml)
C
calc() (neoml.Dnn.CustomLossCalculatorBase method)
calc_best_prev_class (neoml.Dnn.Crf property)
calculation_mode (neoml.Dnn.GELU property)
CenterLoss (class in neoml.Dnn)
channel (neoml.Dnn.TiedEmbeddings property)
channel_based (neoml.Dnn.BatchNormalization property)
channels (neoml.Blob.Blob property)
ChannelwiseConv (class in neoml.Dnn)
class_count (neoml.Dnn.CenterLoss property)
(neoml.Dnn.Crf property)
class_name (neoml.Dnn.Layer property)
classify() (neoml.DecisionTree.DecisionTreeClassificationModel method)
(neoml.GradientBoost.GradientBoostClassificationModel method)
(neoml.Linear.LinearClassificationModel method)
(neoml.SVM.SvmClassificationModel method)
clean_up() (neoml.MathEngine.MathEngine method)
clip() (neoml.AutoDiff method)
clusterize() (neoml.Clustering.FirstCome method)
(neoml.Clustering.Hierarchical method)
(neoml.Clustering.IsoData method)
(neoml.Clustering.KMeans method)
concat() (neoml.AutoDiff method)
ConcatBatchLength (class in neoml.Dnn)
ConcatBatchWidth (class in neoml.Dnn)
ConcatChannels (class in neoml.Dnn)
ConcatDepth (class in neoml.Dnn)
ConcatHeight (class in neoml.Dnn)
ConcatListSize (class in neoml.Dnn)
ConcatObject (class in neoml.Dnn)
ConcatWidth (class in neoml.Dnn)
ConfusionMatrix (class in neoml.Dnn)
connect() (neoml.Dnn.Layer method)
const() (neoml.AutoDiff method)
Conv (class in neoml.Dnn)
Conv3D (class in neoml.Dnn)
copy() (neoml.Blob.Blob method)
count (neoml.Dnn.AccumulativeLookup property)
CpuMathEngine (class in neoml.MathEngine)
Crf (class in neoml.Dnn)
CrfLoss (class in neoml.Dnn)
cross_validation_score() (neoml.CrossValidation method)
CrossEntropyLoss (class in neoml.Dnn)
CtcDecoding (class in neoml.Dnn)
CtcLoss (class in neoml.Dnn)
CumSum (class in neoml.Dnn)
cumsum() (neoml.AutoDiff method)
CustomLoss (class in neoml.Dnn)
CustomLossCalculatorBase (class in neoml.Dnn)
D
DecisionTreeClassificationModel (class in neoml.DecisionTree)
DecisionTreeClassifier (class in neoml.DecisionTree)
decoupled_weight_decay (neoml.Dnn.AdaptiveGradient property)
(neoml.Dnn.NesterovGradient property)
default_math_engine() (neoml.MathEngine method)
default_value (neoml.Dnn.ImageResize property)
delete_layer() (neoml.Dnn.Dnn method)
deltas (neoml.Dnn.ImageResize property)
depth (neoml.Blob.Blob property)
DifferentialEvolution (class in neoml.DifferentialEvolution)
dilation (neoml.Dnn.TimeConv property)
dilation_size (neoml.Dnn.Conv property)
(neoml.Dnn.TransposedConv property)
dimension (neoml.Dnn.Argmax property)
(neoml.Dnn.CumSum property)
(neoml.Dnn.ProjectionPooling property)
dimensions (neoml.Dnn.MultichannelLookup property)
div() (neoml.AutoDiff method)
Dnn (class in neoml.Dnn)
DotProduct (class in neoml.Dnn)
DoubleTraits (class in neoml.DifferentialEvolution)
Dropout (class in neoml.Dnn)
dropout (neoml.Dnn.Lstm property)
(neoml.Dnn.Qrnn property)
dropout_rate (neoml.Dnn.Crf property)
(neoml.Dnn.IndRnn property)
(neoml.Dnn.MultiheadAttention property)
E
element_count (neoml.Dnn.FullyConnected property)
EltwiseDiv (class in neoml.Dnn)
EltwiseMax (class in neoml.Dnn)
EltwiseMul (class in neoml.Dnn)
EltwiseNegMul (class in neoml.Dnn)
EltwiseSub (class in neoml.Dnn)
EltwiseSum (class in neoml.Dnn)
ELU (class in neoml.Dnn)
embeddings_layer_name (neoml.Dnn.TiedEmbeddings property)
enum_gpu() (neoml.MathEngine method)
enum_size (neoml.Dnn.EnumBinarization property)
EnumBinarization (class in neoml.Dnn)
epsilon (neoml.Dnn.AdaptiveGradient property)
(neoml.Dnn.NesterovGradient property)
(neoml.Dnn.ObjectNormalization property)
Equal (class in neoml.Dnn)
Erf (class in neoml.Dnn)
EuclideanLoss (class in neoml.Dnn)
Exp (class in neoml.Dnn)
exp() (neoml.AutoDiff method)
exponent (neoml.Dnn.Power property)
F
filter (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.Qrnn property)
(neoml.Dnn.TimeConv property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
filter_count (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.TimeConv property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
filter_len (neoml.Dnn.MaxOverTimePooling property)
filter_size (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.TimeConv property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
final_params (neoml.Dnn.BatchNormalization property)
first_dim (neoml.Dnn.Transpose property)
FirstCome (class in neoml.Clustering)
FocalLoss (class in neoml.Dnn)
force (neoml.Dnn.BinaryFocalLoss property)
(neoml.Dnn.FocalLoss property)
free_term (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.FullyConnected property)
(neoml.Dnn.Linear property)
(neoml.Dnn.Qrnn property)
(neoml.Dnn.TimeConv property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
free_terms (neoml.Dnn.Crf property)
FullyConnected (class in neoml.Dnn)
G
gate_free_term (neoml.Dnn.Gru property)
gate_weights (neoml.Dnn.Gru property)
GELU (class in neoml.Dnn)
generate() (neoml.DifferentialEvolution.BaseTraits method)
(neoml.DifferentialEvolution.DoubleTraits method)
(neoml.DifferentialEvolution.IntTraits method)
get_best_sequence() (neoml.Dnn.CtcDecoding method)
get_blob() (neoml.Dnn.Sink method)
(neoml.Dnn.Source method)
get_embeddings() (neoml.Dnn.MultichannelLookup method)
GlobalMaxPooling (class in neoml.Dnn)
GlobalMeanPooling (class in neoml.Dnn)
GlobalSumPooling (class in neoml.Dnn)
GpuMathEngine (class in neoml.MathEngine)
GradientBoostClassificationModel (class in neoml.GradientBoost)
GradientBoostClassifier (class in neoml.GradientBoost)
GradientBoostRegressionModel (class in neoml.GradientBoost)
GradientBoostRegressor (class in neoml.GradientBoost)
Gru (class in neoml.Dnn)
H
HardSigmoid (class in neoml.Dnn)
HardTanh (class in neoml.Dnn)
head_count (neoml.Dnn.MultiheadAttention property)
height (neoml.Blob.Blob property)
(neoml.Dnn.PixelToImage property)
height_copy_count (neoml.Dnn.Upsampling2D property)
hidden_layer_size (neoml.Dnn.AttentionDecoder property)
hidden_size (neoml.Dnn.Gru property)
(neoml.Dnn.IndRnn property)
(neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
(neoml.Dnn.MultiheadAttention property)
(neoml.Dnn.Qrnn property)
hidden_weights (neoml.Dnn.Crf property)
Hierarchical (class in neoml.Clustering)
HingeLoss (class in neoml.Dnn)
HSwish (class in neoml.Dnn)
I
identity_scale (neoml.Dnn.Irnn property)
image2d() (neoml.Blob method)
image3d() (neoml.Blob method)
ImageResize (class in neoml.Dnn)
ImageToPixel (class in neoml.Dnn)
IndRnn (class in neoml.Dnn)
info (neoml.MathEngine.GpuMathEngine property)
initialize() (neoml.Dnn.MultichannelLookup method)
initializer (neoml.Dnn.Dnn property)
input_free_term (neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
input_layers (neoml.Dnn.Dnn property)
input_links (neoml.Dnn.Layer property)
input_names (neoml.Dnn.Layer property)
input_weight_std (neoml.Dnn.Irnn property)
input_weights (neoml.Dnn.IndRnn property)
(neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
IntTraits (class in neoml.DifferentialEvolution)
Irnn (class in neoml.Dnn)
IsoData (class in neoml.Clustering)
K
KMeans (class in neoml.Clustering)
L
label_count (neoml.Dnn.CtcDecoding property)
last_loss (neoml.Dnn.CrfLoss property)
(neoml.Dnn.CtcLoss property)
Layer (class in neoml.Dnn)
layers (neoml.Dnn.Dnn property)
LeakyReLU (class in neoml.Dnn)
learn() (neoml.Dnn.Dnn method)
learning_enabled (neoml.Dnn.Layer property)
length (neoml.Dnn.SubSequence property)
Less (class in neoml.Dnn)
less() (neoml.AutoDiff method)
(neoml.DifferentialEvolution.BaseTraits method)
(neoml.DifferentialEvolution.DoubleTraits method)
(neoml.DifferentialEvolution.IntTraits method)
Linear (class in neoml.Dnn)
LinearClassificationModel (class in neoml.Linear)
LinearClassifier (class in neoml.Linear)
LinearRegressionModel (class in neoml.Linear)
LinearRegressor (class in neoml.Linear)
list_blob() (neoml.Blob method)
list_size (neoml.Blob.Blob property)
load() (neoml.Blob method)
(neoml.Dnn.Dnn method)
load_checkpoint() (neoml.Dnn.Dnn method)
Log (class in neoml.Dnn)
log() (neoml.AutoDiff method)
loss_weight (neoml.Dnn.CrfLoss property)
(neoml.Dnn.CtcLoss property)
lower_bound (neoml.Dnn.Uniform property)
Lrn (class in neoml.Dnn)
Lstm (class in neoml.Dnn)
M
main_free_term (neoml.Dnn.Gru property)
main_weights (neoml.Dnn.Gru property)
math_engine (neoml.Blob.Blob property)
(neoml.Dnn.Dnn property)
MathEngine (class in neoml.MathEngine)
matrix (neoml.Dnn.ConfusionMatrix property)
matrix() (neoml.Blob method)
MatrixMultiplication (class in neoml.Dnn)
max() (neoml.AutoDiff method)
max_count (neoml.Dnn.GlobalMaxPooling property)
max_gradient (neoml.Dnn.CrfLoss property)
(neoml.Dnn.CtcLoss property)
MaxOverTimePooling (class in neoml.Dnn)
MaxPooling (class in neoml.Dnn)
MaxPooling3D (class in neoml.Dnn)
mean() (neoml.AutoDiff method)
MeanPooling (class in neoml.Dnn)
MeanPooling3D (class in neoml.Dnn)
moment_decay_rate (neoml.Dnn.AdaptiveGradient property)
(neoml.Dnn.NesterovGradient property)
(neoml.Dnn.SimpleGradient property)
mul() (neoml.AutoDiff method)
MultichannelLookup (class in neoml.Dnn)
MultiheadAttention (class in neoml.Dnn)
MultiHingeLoss (class in neoml.Dnn)
multiplier (neoml.Dnn.Linear property)
MultiSquaredHingeLoss (class in neoml.Dnn)
mutate() (neoml.DifferentialEvolution.BaseTraits method)
(neoml.DifferentialEvolution.DoubleTraits method)
(neoml.DifferentialEvolution.IntTraits method)
N
name (neoml.Dnn.Layer property)
neg() (neoml.AutoDiff method)
NesterovGradient (class in neoml.Dnn)
Not (class in neoml.Dnn)
O
object_count (neoml.Blob.Blob property)
object_size (neoml.Blob.Blob property)
ObjectNormalization (class in neoml.Dnn)
optimal_vector (neoml.DifferentialEvolution.DifferentialEvolution property)
original_size (neoml.Dnn.ProjectionPooling property)
output_layers (neoml.Dnn.Dnn property)
output_object_size (neoml.Dnn.AttentionDecoder property)
output_seq_len (neoml.Dnn.AttentionDecoder property)
output_size (neoml.Dnn.MultiheadAttention property)
P
padding (neoml.Dnn.Crf property)
padding_back (neoml.Dnn.Qrnn property)
(neoml.Dnn.TimeConv property)
padding_front (neoml.Dnn.Qrnn property)
(neoml.Dnn.TimeConv property)
padding_size (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
PCA (in module neoml)
peak_memory_usage (neoml.MathEngine.MathEngine property)
PixelToImage (class in neoml.Dnn)
population (neoml.DifferentialEvolution.DifferentialEvolution property)
population_function_values (neoml.DifferentialEvolution.DifferentialEvolution property)
PositionalEmbedding (class in neoml.Dnn)
positive_weight (neoml.Dnn.BinaryCrossEntropyLoss property)
pow() (neoml.AutoDiff method)
Power (class in neoml.Dnn)
PrecisionRecall (class in neoml.Dnn)
predict() (neoml.GradientBoost.GradientBoostRegressionModel method)
(neoml.Linear.LinearRegressionModel method)
ProjectionPooling (class in neoml.Dnn)
Q
Qrnn (class in neoml.Dnn)
R
Random (class in neoml.Random)
rate (neoml.Dnn.CenterLoss property)
(neoml.Dnn.Dropout property)
recurrent_free_term (neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
recurrent_mode (neoml.Dnn.Qrnn property)
recurrent_weights (neoml.Dnn.IndRnn property)
(neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
ReLU (class in neoml.Dnn)
Reorg (class in neoml.Dnn)
reset (neoml.Dnn.Accuracy property)
(neoml.Dnn.ConfusionMatrix property)
(neoml.Dnn.PrecisionRecall property)
reset_matrix() (neoml.Dnn.ConfusionMatrix method)
reshape() (neoml.AutoDiff method)
result (neoml.Dnn.PrecisionRecall property)
reverse (neoml.Dnn.CumSum property)
reverse_sequence (neoml.Dnn.IndRnn property)
(neoml.Dnn.Irnn property)
(neoml.Dnn.Lstm property)
ReverseSequence (class in neoml.Dnn)
run() (neoml.DifferentialEvolution.DifferentialEvolution method)
(neoml.Dnn.Dnn method)
run_and_backward() (neoml.Dnn.Dnn method)
S
scale (neoml.Dnn.ObjectNormalization property)
ScatterND (class in neoml.Dnn)
score (neoml.Dnn.AttentionDecoder property)
second_dim (neoml.Dnn.Transpose property)
second_moment_decay_rate (neoml.Dnn.AdaptiveGradient property)
(neoml.Dnn.NesterovGradient property)
sequence_length (neoml.Dnn.CtcDecoding property)
SequenceSum (class in neoml.Dnn)
set_blob() (neoml.Dnn.Source method)
set_embeddings() (neoml.Dnn.MultichannelLookup method)
shape (neoml.Blob.Blob property)
Sigmoid (class in neoml.Dnn)
SimpleGradient (class in neoml.Dnn)
Sink (class in neoml.Dnn)
size (neoml.Blob.Blob property)
(neoml.Dnn.AccumulativeLookup property)
skip (neoml.Dnn.CtcLoss property)
slope (neoml.Dnn.HardSigmoid property)
slow_convergence_rate (neoml.Dnn.BatchNormalization property)
Softmax (class in neoml.Dnn)
solver (neoml.Dnn.Dnn property)
Source (class in neoml.Dnn)
spatial (neoml.Dnn.Dropout property)
SplitBatchLength (class in neoml.Dnn)
SplitBatchWidth (class in neoml.Dnn)
SplitChannels (class in neoml.Dnn)
SplitDepth (class in neoml.Dnn)
SplitHeight (class in neoml.Dnn)
SplitListSize (class in neoml.Dnn)
SplitWidth (class in neoml.Dnn)
SquaredHingeLoss (class in neoml.Dnn)
start_pos (neoml.Dnn.SubSequence property)
store() (neoml.Blob method)
(neoml.Dnn.Dnn method)
(neoml.GradientBoost.GradientBoostClassificationModel method)
(neoml.GradientBoost.GradientBoostRegressionModel method)
store_checkpoint() (neoml.Dnn.Dnn method)
stride (neoml.Dnn.Qrnn property)
(neoml.Dnn.Reorg property)
(neoml.Dnn.TimeConv property)
stride_len (neoml.Dnn.MaxOverTimePooling property)
stride_size (neoml.Dnn.ChannelwiseConv property)
(neoml.Dnn.Conv property)
(neoml.Dnn.Conv3D property)
(neoml.Dnn.TransposedConv property)
(neoml.Dnn.TransposedConv3D property)
sub() (neoml.AutoDiff method)
SubSequence (class in neoml.Dnn)
sum() (neoml.AutoDiff method)
svd() (in module neoml.PCA)
SvmClassificationModel (class in neoml.SVM)
SvmClassifier (class in neoml.SVM)
T
Tanh (class in neoml.Dnn)
tensor() (neoml.Blob method)
threshold (neoml.Dnn.ReLU property)
TiedEmbeddings (class in neoml.Dnn)
TimeConv (class in neoml.Dnn)
top_k() (neoml.AutoDiff method)
train() (neoml.DecisionTree.DecisionTreeClassifier method)
(neoml.GradientBoost.GradientBoostClassifier method)
(neoml.GradientBoost.GradientBoostRegressor method)
(neoml.Linear.LinearClassifier method)
(neoml.Linear.LinearRegressor method)
(neoml.SVM.SvmClassifier method)
Transform (class in neoml.Dnn)
transforms (neoml.Dnn.Transform property)
transitions (neoml.Dnn.Crf property)
Transpose (class in neoml.Dnn)
TransposedConv (class in neoml.Dnn)
TransposedConv3D (class in neoml.Dnn)
type (neoml.Dnn.PositionalEmbedding property)
U
Uniform (class in neoml.Dnn)
upper_bound (neoml.Dnn.Uniform property)
Upsampling2D (class in neoml.Dnn)
use_final_params_for_init (neoml.Dnn.BatchNormalization property)
use_mask (neoml.Dnn.MultiheadAttention property)
V
vector() (neoml.Blob method)
W
weights (neoml.Dnn.FullyConnected property)
Where (class in neoml.Dnn)
width (neoml.Blob.Blob property)
(neoml.Dnn.PixelToImage property)
width_copy_count (neoml.Dnn.Upsampling2D property)
window_size (neoml.Dnn.Lrn property)
(neoml.Dnn.Qrnn property)
X
Xavier (class in neoml.Dnn)
XavierUniform (class in neoml.Dnn)
Z
zero_free_term (neoml.Dnn.BatchNormalization property)
(neoml.Dnn.FullyConnected property)
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