Torchélie
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Pytorch Utils
torchelie.nn
torchelie.nn.utils
torchelie.optim
torchelie.lr_scheduler
torchelie.utils
torchelie.data_learning
torchelie.loss
torchelie.models
torchelie.distributions
torchelie.datasets
torchelie.transforms
torchelie.recipes
Algorithms and training
Understanding recipes
Using the predefined recipes and callbacks
torchelie.callbacks
torchelie.hyper
Torchélie
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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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I
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J
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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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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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Z
A
AccAvg (class in torchelie.callbacks)
AdaIN2d (class in torchelie.nn)
AdaptiveConcatPool2d (class in torchelie.nn)
AdaptPad (class in torchelie.transforms)
add_batchnorm() (torchelie.models.VGG method)
add_minibatch_stddev() (torchelie.models.ResidualDiscriminator method)
add_operation() (torchelie.nn.ModuleGraph method)
add_se() (torchelie.models.ResNet method)
add_skip() (torchelie.nn.ConvDeconvBlock method)
add_upsampling() (torchelie.nn.ConvBlock method)
AddSign (class in torchelie.optim)
affine (torchelie.nn.AttenNorm2d attribute)
AllAtOnceColor (class in torchelie.transforms.differentiable)
AllAtOnceGeometric (class in torchelie.transforms.differentiable)
apply() (torchelie.nn.utils.WeightLambda static method)
(torchelie.transforms.differentiable.AllAtOnceColor method)
as_multiclass_shape() (in module torchelie.utils)
AttenNorm2d (class in torchelie.nn)
attention56 (class in torchelie.models)
Attention56Bone (class in torchelie.models)
AutoGAN (class in torchelie.models)
autogan_128 (class in torchelie.models)
autogan_32 (class in torchelie.models)
autogan_64 (class in torchelie.models)
AutoGANGenBlock (class in torchelie.nn)
AutoStateDict (class in torchelie.utils)
B
backward() (torchelie.nn.GaussianPriorFunc static method)
berserk_mode() (torchelie.transforms.RandAugment method)
bgram() (in module torchelie.utils)
bias (torchelie.nn.AdaIN2d attribute)
(torchelie.nn.FiLM2d attribute)
(torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
blocks (torchelie.models.AutoGAN attribute)
branch (torchelie.nn.PreactResBlock attribute)
(torchelie.nn.PreactResBlockBottleneck attribute)
(torchelie.nn.ResidualDiscrBlock attribute)
(torchelie.nn.SpadeResBlock attribute)
brightness() (torchelie.transforms.differentiable.AllAtOnceColor method)
C
CachedDataset (class in torchelie.datasets)
CallRecipe (class in torchelie.callbacks)
Canny (class in torchelie.transforms)
center_crop() (in module torchelie.transforms.differentiable)
Checkpoint (class in torchelie.callbacks)
ChoiceSampler (class in torchelie.hyper)
classes (torchelie.datasets.HorizontalConcatDataset attribute)
Classification() (in module torchelie.recipes)
(in module torchelie.recipes.classification)
ClassificationHead (class in torchelie.models)
ClassificationInspector (class in torchelie.callbacks)
classifier (torchelie.models.ResidualDiscriminator attribute)
ColoredColumns (class in torchelie.datasets)
ColoredRows (class in torchelie.datasets)
commitment (torchelie.nn.VQ attribute)
condition() (torchelie.nn.AdaIN2d method)
(torchelie.nn.ConditionalBN2d method)
(torchelie.nn.CondSeq method)
(torchelie.nn.FiLM2d method)
(torchelie.nn.ModulatedConv method)
(torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlock method)
(torchelie.nn.ResBlockBottleneck method)
(torchelie.nn.Spade2d method)
(torchelie.nn.UBlock method)
ConditionalBN2d (class in torchelie.nn)
CondSeq (class in torchelie.nn)
ConfusionMatrix (class in torchelie.callbacks)
Const (class in torchelie.nn)
constant_init() (in module torchelie.utils)
continuous_cross_entropy() (in module torchelie.loss)
ContinuousCEWithLogits (class in torchelie.loss)
contrast() (torchelie.transforms.differentiable.AllAtOnceColor method)
conv (torchelie.models.ResNetInput attribute)
(torchelie.nn.ConvBlock attribute)
Conv1x1 (class in torchelie.nn)
Conv2d (class in torchelie.nn)
Conv3x3 (class in torchelie.nn)
ConvBlock (class in torchelie.nn)
ConvDeconvBlock (class in torchelie.nn)
CorrelateColors (class in torchelie.data_learning)
CosineDecay (class in torchelie.lr_scheduler)
Counter (class in torchelie.callbacks)
cpu() (torchelie.recipes.recipebase.Recipe method)
crop() (in module torchelie.transforms.differentiable)
CrossEntropyClassification() (in module torchelie.recipes)
(in module torchelie.recipes.classification)
cuda() (torchelie.recipes.recipebase.Recipe method)
CurriculumScheduler (class in torchelie.lr_scheduler)
Cutout (class in torchelie.transforms)
D
Debug (class in torchelie.nn)
DecaySampler (class in torchelie.hyper)
DeepDream (class in torchelie.recipes.deepdream)
DeepDreamLoss (class in torchelie.loss)
DeepDreamOptim (class in torchelie.optim)
DetachedModule (class in torchelie.utils)
dict_by_key() (in module torchelie.utils)
dilation (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
dim (torchelie.nn.VQ attribute)
dist_setup() (in module torchelie.utils)
downsample (torchelie.nn.UBlock attribute)
Dummy (class in torchelie.nn)
E
edit_model (class in torchelie.nn.utils)
EfficientNet (class in torchelie.models)
embedding (torchelie.nn.VQ attribute)
entropy() (in module torchelie.utils)
EpochMetricAvg (class in torchelie.callbacks)
eps (torchelie.nn.AttenNorm2d attribute)
experimental() (in module torchelie.utils)
ExpSampler (class in torchelie.hyper)
extra_repr() (torchelie.nn.GhostBatchNorm2d method)
(torchelie.nn.Interpolate2d method)
F
fake() (in module torchelie.loss.gan.hinge)
(in module torchelie.loss.gan.standard)
fast_zero_grad() (in module torchelie.utils)
FastImageFolder (class in torchelie.datasets)
FeatureVis (class in torchelie.recipes.feature_vis)
FiLM2d (class in torchelie.nn)
fit() (torchelie.recipes.deepdream.DeepDream method)
(torchelie.recipes.feature_vis.FeatureVis method)
(torchelie.recipes.neural_style.NeuralStyle method)
focal_loss() (in module torchelie.loss)
FocalLoss (class in torchelie.loss)
forever() (in module torchelie.utils)
forward() (torchelie.data_learning.ParameterizedImg method)
(torchelie.data_learning.PixelImage method)
(torchelie.data_learning.SpectralImage method)
(torchelie.loss.ContinuousCEWithLogits method)
(torchelie.loss.DeepDreamLoss method)
(torchelie.loss.FocalLoss method)
(torchelie.loss.NeuralStyleLoss method)
(torchelie.loss.OrthoLoss method)
(torchelie.loss.PerceptualLoss method)
(torchelie.loss.TemperedCrossEntropyLoss method)
(torchelie.loss.TotalVariationLoss method)
(torchelie.models.PixelCNN method)
(torchelie.models.ResidualDiscriminator method)
(torchelie.models.ResNet method)
(torchelie.models.ResNetInput method)
(torchelie.models.StyleGAN2Generator method)
(torchelie.nn.AdaIN2d method)
(torchelie.nn.AdaptiveConcatPool2d method)
(torchelie.nn.AttenNorm2d method)
(torchelie.nn.AutoGANGenBlock method)
(torchelie.nn.ConditionalBN2d method)
(torchelie.nn.CondSeq method)
(torchelie.nn.ConvDeconvBlock method)
(torchelie.nn.Debug method)
(torchelie.nn.Dummy method)
(torchelie.nn.FiLM2d method)
(torchelie.nn.GaussianPriorFunc static method)
(torchelie.nn.GhostBatchNorm2d method)
(torchelie.nn.HardSigmoid method)
(torchelie.nn.HardSwish method)
(torchelie.nn.ImageNetInputNorm method)
(torchelie.nn.Interpolate2d method)
(torchelie.nn.Lambda method)
(torchelie.nn.MaskedConv2d method)
(torchelie.nn.MinibatchStddev method)
(torchelie.nn.ModulatedConv method)
(torchelie.nn.ModuleGraph method)
(torchelie.nn.MultiVQ method)
(torchelie.nn.Noise method)
(torchelie.nn.PixelNorm method)
(torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlock method)
(torchelie.nn.ResBlockBottleneck method)
(torchelie.nn.Reshape method)
(torchelie.nn.SEBlock method)
(torchelie.nn.SelfAttention2d method)
(torchelie.nn.Spade2d method)
(torchelie.nn.TopLeftConv2d method)
(torchelie.nn.UBlock method)
(torchelie.nn.UnitGaussianPrior method)
(torchelie.nn.VQ method)
(torchelie.nn.WithSavedActivations method)
(torchelie.transforms.RandAugment method)
freeze() (in module torchelie.utils)
FrozenModule (class in torchelie.utils)
G
GANMetrics (class in torchelie.callbacks)
GANRecipe() (in module torchelie.recipes.gan)
GaussianMixture (class in torchelie.distributions)
GaussianPriorFunc (class in torchelie.nn)
gblur() (in module torchelie.transforms.differentiable)
generated() (in module torchelie.loss.gan.hinge)
(in module torchelie.loss.gan.standard)
get_acts_() (torchelie.loss.DeepDreamLoss method)
get_lr() (torchelie.lr_scheduler.HyperbolicTangentDecay method)
get_params() (torchelie.transforms.ResizedCrop static method)
get_style_content_() (torchelie.loss.NeuralStyleLoss method)
GhostBatchNorm2d (class in torchelie.nn)
gram() (in module torchelie.utils)
groups (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
H
HardSigmoid (class in torchelie.nn)
HardSwish (class in torchelie.nn)
HorizontalConcatDataset (class in torchelie.datasets)
Hourglass (class in torchelie.models)
HyperbolicTangentDecay (class in torchelie.lr_scheduler)
HyperparamSampler (class in torchelie.hyper)
HyperparamSearch (class in torchelie.hyper)
I
Identity (class in torchelie.transforms)
ilerp() (in module torchelie.utils)
ImageGradientVis (class in torchelie.callbacks)
ImageNetInputNorm (class in torchelie.nn)
Imagenette (class in torchelie.datasets)
ImagesPaths (class in torchelie.datasets)
Imagewoof (class in torchelie.datasets)
in_channels (torchelie.nn.ConvBlock attribute)
indent() (in module torchelie.utils)
InformationBottleneck (class in torchelie.nn)
init_mode (torchelie.nn.VQ attribute)
initialized (torchelie.nn.VQ attribute)
insert_after (class in torchelie.nn.utils)
insert_before (class in torchelie.nn.utils)
Interpolate2d (class in torchelie.nn)
InterpolateBilinear2d (class in torchelie.nn)
inverse() (torchelie.nn.ImageNetInputNorm method)
invert() (torchelie.data_learning.CorrelateColors method)
J
JPEGArtifacts (class in torchelie.transforms)
K
kaiming() (in module torchelie.utils)
kaiming_gain() (in module torchelie.utils)
kernel_size (torchelie.nn.ConvBlock attribute)
(torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
L
lam (torchelie.nn.Lambda attribute)
Lambda (class in torchelie.nn)
layer_by_name() (in module torchelie.utils)
leaky() (torchelie.models.ClassificationHead method)
(torchelie.models.Pix2PixHDGlobalGenerator method)
(torchelie.nn.ConvBlock method)
(torchelie.nn.ConvDeconvBlock method)
(torchelie.nn.UBlock method)
lerp() (in module torchelie.utils)
linear1 (torchelie.models.ClassificationHead attribute)
LinearDecay (class in torchelie.lr_scheduler)
load_recursive_state_dict() (in module torchelie.utils)
load_state_dict() (torchelie.optim.Lookahead method)
(torchelie.recipes.recipebase.Recipe method)
load_state_dict_forgiving() (in module torchelie.utils)
Log (class in torchelie.callbacks)
log_prob() (torchelie.distributions.GaussianMixture method)
(torchelie.distributions.LogisticMixture method)
log_result() (torchelie.hyper.HyperparamSearch method)
Logistic (class in torchelie.distributions)
LogisticMixture (class in torchelie.distributions)
Lookahead (class in torchelie.optim)
LRSched (class in torchelie.callbacks)
M
make_leaky (class in torchelie.nn.utils)
make_noise (torchelie.models.AutoGAN attribute)
make_weight_bias() (torchelie.nn.Spade2d method)
MaskedConv2d (class in torchelie.nn)
mblur() (in module torchelie.transforms.differentiable)
MConvBNReLU (class in torchelie.nn)
MConvNormReLU (class in torchelie.nn)
mean() (torchelie.distributions.GaussianMixture property)
(torchelie.distributions.LogisticMixture property)
MergedDataset (class in torchelie.datasets)
MetricsTable (class in torchelie.callbacks)
MinibatchStddev (class in torchelie.nn)
mixup() (in module torchelie.datasets)
MixUpDataset (class in torchelie.datasets)
ModulatedConv (class in torchelie.nn)
module
torchelie.data_learning
torchelie.distributions
torchelie.hyper
torchelie.loss.gan.hinge
torchelie.loss.gan.standard
torchelie.lr_scheduler
torchelie.recipes
torchelie.recipes.deepdream
torchelie.recipes.feature_vis
torchelie.recipes.image_prior
torchelie.recipes.neural_style
torchelie.transforms.differentiable
torchelie.utils
ModuleGraph (class in torchelie.nn)
modules() (torchelie.recipes.recipebase.Recipe method)
momentum (torchelie.nn.AttenNorm2d attribute)
MS1M (class in torchelie.datasets)
MultiBranch (class in torchelie.transforms)
MultiVQ (class in torchelie.nn)
N
n_skip_max (torchelie.models.AutoGAN attribute)
name (torchelie.nn.utils.WeightLambda attribute)
nb_parameters() (in module torchelie.utils)
net (torchelie.loss.NeuralStyleLoss attribute)
net_to_equal_lr (class in torchelie.nn.utils)
NeuralStyle (class in torchelie.recipes.neural_style)
NeuralStyleLoss (class in torchelie.loss)
no_bias() (torchelie.nn.ConvBlock method)
no_preact() (torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
no_relu() (torchelie.nn.ConvBlock method)
NoexceptDataset (class in torchelie.datasets)
Noise (class in torchelie.nn)
norm (torchelie.nn.ConvBlock attribute)
normal_init() (in module torchelie.utils)
num_features (torchelie.nn.AttenNorm2d attribute)
O
OneCycle (class in torchelie.lr_scheduler)
Optimizer (class in torchelie.callbacks)
ortho() (in module torchelie.loss)
OrthoLoss (class in torchelie.loss)
out_channels (torchelie.nn.ConvBlock attribute)
(torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
output_padding (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
P
padding (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
padding_mode (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
PairedDataset (class in torchelie.datasets)
parallel_run() (in module torchelie.utils)
parameterized_truncated_normal() (in module torchelie.distributions)
ParameterizedImg (class in torchelie.data_learning)
partial_sample() (torchelie.models.PixelCNN method)
patch16 (class in torchelie.models)
patch286 (class in torchelie.models)
patch34 (class in torchelie.models)
patch70 (class in torchelie.models)
PatchDiscriminator (class in torchelie.models)
PerceptualLoss (class in torchelie.loss)
PerceptualNet (class in torchelie.models)
pix2pix_256 (class in torchelie.models)
pix2pix_dev (class in torchelie.models)
Pix2PixDataset (class in torchelie.datasets)
Pix2PixGenerator (class in torchelie.models)
Pix2PixHDGlobalGenerator (class in torchelie.models)
PixelCNN (class in torchelie.models)
PixelImage (class in torchelie.data_learning)
PixelNorm (class in torchelie.nn)
Polyak (class in torchelie.callbacks)
pool (torchelie.models.ResNetInput attribute)
Posterize (class in torchelie.transforms)
preact_resnet101 (in module torchelie.models)
preact_resnet152 (in module torchelie.models)
preact_resnet18 (in module torchelie.models)
preact_resnet20_cifar (class in torchelie.models)
preact_resnet34 (in module torchelie.models)
preact_resnet50 (in module torchelie.models)
preact_resnext101_32x4d (class in torchelie.models)
preact_resnext152_32x4d (class in torchelie.models)
preact_resnext50_32x4d (class in torchelie.models)
preact_skip() (torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
preact_wide_resnet101 (class in torchelie.models)
preact_wide_resnet50 (class in torchelie.models)
PreactResBlock (class in torchelie.nn)
PreactResBlockBottleneck (class in torchelie.nn)
ProjectionDiscr (class in torchelie.models)
R
RAdamW (class in torchelie.optim)
RandAugment (class in torchelie.transforms)
RandomPairsDataset (class in torchelie.datasets)
read_idx() (torchelie.datasets.MS1M static method)
read_metadata() (torchelie.datasets.MS1M method)
real() (in module torchelie.loss.gan.hinge)
(in module torchelie.loss.gan.standard)
receptive_field_for (class in torchelie.nn.utils)
Recipe (class in torchelie.recipes.recipebase)
recursive_state_dict() (in module torchelie.utils)
register() (torchelie.recipes.recipebase.Recipe method)
relu (torchelie.nn.ConvBlock attribute)
remove() (torchelie.nn.utils.WeightLambda method)
remove_batchnorm (class in torchelie.nn.utils)
remove_batchnorm() (torchelie.models.PatchDiscriminator method)
(torchelie.nn.ConvBlock method)
(torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlock method)
(torchelie.nn.ResBlockBottleneck method)
(torchelie.nn.UBlock method)
remove_pool() (torchelie.models.ClassificationHead method)
remove_upsampling_conv() (torchelie.nn.UBlock method)
remove_weight_lambda (class in torchelie.nn.utils)
remove_weight_norm_and_equal_lr (class in torchelie.nn.utils)
remove_weight_scale (class in torchelie.nn.utils)
render() (torchelie.data_learning.ParameterizedImg method)
res_discr_3l (class in torchelie.models)
res_discr_4l (class in torchelie.models)
res_discr_5l (class in torchelie.models)
res_discr_6l (class in torchelie.models)
res_discr_7l (class in torchelie.models)
resample_dead() (torchelie.nn.VQ method)
ResBlock (class in torchelie.nn)
ResBlockBottleneck (class in torchelie.nn)
reset() (torchelie.nn.ConvBlock method)
Reshape (class in torchelie.nn)
residual_patch142 (class in torchelie.models)
residual_patch286 (class in torchelie.models)
residual_patch34 (class in torchelie.models)
residual_patch70 (class in torchelie.models)
ResidualDiscrBlock (class in torchelie.nn)
ResidualDiscriminator (class in torchelie.models)
ResizedCrop (class in torchelie.transforms)
ResizeNoCrop (class in torchelie.transforms)
ResNet (class in torchelie.models)
resnet101 (in module torchelie.models)
resnet152 (in module torchelie.models)
resnet18 (in module torchelie.models)
resnet20_cifar (class in torchelie.models)
ResNetInput (class in torchelie.models)
resnext() (torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlockBottleneck method)
resnext101_32x4d (class in torchelie.models)
resnext152_32x4d (class in torchelie.models)
restore_batchnorm() (torchelie.nn.ConvBlock method)
return_indices (torchelie.nn.VQ attribute)
rm_dropout() (torchelie.models.ClassificationHead method)
roll() (in module torchelie.transforms.differentiable)
rotate() (torchelie.transforms.differentiable.AllAtOnceGeometric method)
run() (torchelie.recipes.recipebase.Recipe method)
S
sample() (torchelie.hyper.ChoiceSampler method)
(torchelie.hyper.DecaySampler method)
(torchelie.hyper.ExpSampler method)
(torchelie.hyper.HyperparamSampler method)
(torchelie.hyper.HyperparamSearch method)
(torchelie.hyper.UniformSampler method)
(torchelie.models.PixelCNN method)
sample_() (torchelie.models.PixelCNN method)
sample_cond() (torchelie.models.PixelCNN method)
sample_truncated_normal() (in module torchelie.distributions)
scale() (torchelie.transforms.differentiable.AllAtOnceGeometric method)
SEBlock (class in torchelie.nn)
SegmentationInspector (class in torchelie.callbacks)
SelfAttention2d (class in torchelie.nn)
send_to_device() (in module torchelie.utils)
set_content() (torchelie.loss.NeuralStyleLoss method)
set_decoder_num_layers() (torchelie.nn.UBlock method)
set_encoder_num_layers() (torchelie.nn.UBlock method)
set_input_specs() (torchelie.models.PatchDiscriminator method)
(torchelie.models.ResidualDiscriminator method)
(torchelie.models.ResNet method)
(torchelie.models.ResNetInput method)
(torchelie.models.VGG method)
set_keep_layers() (torchelie.nn.WithSavedActivations method)
set_kernel_size() (torchelie.models.PatchDiscriminator method)
set_num_classes() (torchelie.models.ClassificationHead method)
set_padding_mode() (torchelie.models.Pix2PixGenerator method)
(torchelie.nn.UBlock method)
set_pool_size() (torchelie.models.ClassificationHead method)
set_stride() (torchelie.models.ResNetInput method)
set_style() (torchelie.loss.NeuralStyleLoss method)
shortcut (torchelie.nn.PreactResBlock attribute)
(torchelie.nn.PreactResBlockBottleneck attribute)
(torchelie.nn.ResidualDiscrBlock attribute)
(torchelie.nn.SpadeResBlock attribute)
SideBySideImagePairsDataset (class in torchelie.datasets)
SinePositionEncoding2d (class in torchelie.nn)
slerp() (in module torchelie.utils)
snres_discr_4l (class in torchelie.models)
snres_discr_5l (class in torchelie.models)
snres_discr_6l (class in torchelie.models)
snres_discr_7l (class in torchelie.models)
snres_projdiscr_4l (class in torchelie.models)
snres_projdiscr_5l (class in torchelie.models)
snres_projdiscr_6l (class in torchelie.models)
snres_projdiscr_7l (class in torchelie.models)
Solarize (class in torchelie.transforms)
Spade2d (class in torchelie.nn)
SpadeResBlock (class in torchelie.nn)
SpectralImage (class in torchelie.data_learning)
state_dict() (torchelie.optim.Lookahead method)
(torchelie.recipes.recipebase.Recipe method)
StdoutLogger (class in torchelie.callbacks)
step() (torchelie.lr_scheduler.CosineDecay method)
(torchelie.lr_scheduler.CurriculumScheduler method)
(torchelie.lr_scheduler.OneCycle method)
(torchelie.optim.AddSign method)
(torchelie.optim.DeepDreamOptim method)
(torchelie.optim.Lookahead method)
(torchelie.optim.RAdamW method)
stride (torchelie.nn.ConvBlock attribute)
(torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
StyleGAN2Block (class in torchelie.nn)
StyleGAN2Discriminator (class in torchelie.models)
StyleGAN2Generator (class in torchelie.models)
Subsample (class in torchelie.transforms)
Subset (class in torchelie.datasets)
T
tempered_cross_entropy() (in module torchelie.loss)
tempered_log_softmax() (in module torchelie.loss)
tempered_nll_loss() (in module torchelie.loss)
tempered_softmax() (in module torchelie.loss)
TemperedCrossEntropyLoss (class in torchelie.loss)
Throughput (class in torchelie.callbacks)
to() (torchelie.recipes.recipebase.Recipe method)
to_avg_pool() (torchelie.models.PatchDiscriminator method)
to_bilinear_sampling() (torchelie.nn.UBlock method)
to_binomial_downsampling() (torchelie.models.PatchDiscriminator method)
to_bottleneck() (torchelie.models.ResNet method)
to_concat_pool() (torchelie.models.ClassificationHead method)
to_convolutional() (torchelie.models.ClassificationHead method)
to_dot() (torchelie.nn.ModuleGraph method)
to_equal_lr() (torchelie.models.PatchDiscriminator method)
(torchelie.models.Pix2PixGenerator method)
(torchelie.models.Pix2PixHDGlobalGenerator method)
(torchelie.models.ResidualDiscriminator method)
(torchelie.nn.ModulatedConv method)
(torchelie.nn.ResidualDiscrBlock method)
to_input_specs() (torchelie.nn.ConvBlock method)
to_instance_norm() (torchelie.models.PatchDiscriminator method)
(torchelie.models.Pix2PixGenerator method)
to_preact() (torchelie.models.ResNet method)
(torchelie.nn.ConvBlock method)
to_preact_bottleneck() (torchelie.models.ResNet method)
to_preact_resnext() (torchelie.models.ResNet method)
to_preact_wide() (torchelie.models.ResNet method)
to_projection_discr() (torchelie.models.ResidualDiscriminator method)
to_resnet_style() (torchelie.models.ClassificationHead method)
to_resnext() (torchelie.models.ResNet method)
to_rgb (torchelie.models.AutoGAN attribute)
to_spectral_norm() (torchelie.models.ResidualDiscriminator method)
(torchelie.nn.ResidualDiscrBlock method)
to_standard_arch() (torchelie.models.Pix2PixHDGlobalGenerator method)
to_transposed_conv() (torchelie.nn.ConvBlock method)
to_two_layers() (torchelie.models.ClassificationHead method)
to_unet() (torchelie.models.Pix2PixHDGlobalGenerator method)
to_vgg_style() (torchelie.models.ClassificationHead method)
to_wide() (torchelie.models.ResNet method)
TopkAccAvg (class in torchelie.callbacks)
TopLeftConv2d (class in torchelie.nn)
torchelie.data_learning
module
torchelie.distributions
module
torchelie.hyper
module
torchelie.loss.gan.hinge
module
torchelie.loss.gan.standard
module
torchelie.lr_scheduler
module
torchelie.recipes
module
torchelie.recipes.deepdream
module
torchelie.recipes.feature_vis
module
torchelie.recipes.image_prior
module
torchelie.recipes.neural_style
module
torchelie.transforms.differentiable
module
torchelie.utils
module
total_variation() (in module torchelie.loss)
TotalVariationLoss (class in torchelie.loss)
track_running_stats (torchelie.nn.AttenNorm2d attribute)
TrainAndCall() (in module torchelie.recipes)
TrainAndTest() (in module torchelie.recipes)
(in module torchelie.recipes.trainandtest)
training (torchelie.loss.ContinuousCEWithLogits attribute)
(torchelie.loss.DeepDreamLoss attribute)
(torchelie.loss.FocalLoss attribute)
(torchelie.loss.OrthoLoss attribute)
(torchelie.loss.PerceptualLoss attribute)
(torchelie.loss.TemperedCrossEntropyLoss attribute)
(torchelie.loss.TotalVariationLoss attribute)
(torchelie.models.Attention56Bone attribute)
(torchelie.models.EfficientNet attribute)
(torchelie.models.Hourglass attribute)
(torchelie.models.PatchDiscriminator attribute)
(torchelie.models.PerceptualNet attribute)
(torchelie.models.Pix2PixGenerator attribute)
(torchelie.models.Pix2PixHDGlobalGenerator attribute)
(torchelie.models.PixelCNN attribute)
(torchelie.models.ProjectionDiscr attribute)
(torchelie.models.ResNet attribute)
(torchelie.models.UNet attribute)
(torchelie.models.VGG attribute)
(torchelie.nn.AdaptiveConcatPool2d attribute)
(torchelie.nn.AutoGANGenBlock attribute)
(torchelie.nn.ConditionalBN2d attribute)
(torchelie.nn.CondSeq attribute)
(torchelie.nn.Const attribute)
(torchelie.nn.ConvDeconvBlock attribute)
(torchelie.nn.Debug attribute)
(torchelie.nn.Dummy attribute)
(torchelie.nn.GhostBatchNorm2d attribute)
(torchelie.nn.HardSigmoid attribute)
(torchelie.nn.HardSwish attribute)
(torchelie.nn.ImageNetInputNorm attribute)
(torchelie.nn.InformationBottleneck attribute)
(torchelie.nn.Interpolate2d attribute)
(torchelie.nn.InterpolateBilinear2d attribute)
(torchelie.nn.MinibatchStddev attribute)
(torchelie.nn.ModuleGraph attribute)
(torchelie.nn.MultiVQ attribute)
(torchelie.nn.Noise attribute)
(torchelie.nn.PixelNorm attribute)
(torchelie.nn.ResBlock attribute)
(torchelie.nn.ResBlockBottleneck attribute)
(torchelie.nn.Reshape attribute)
(torchelie.nn.ResidualDiscrBlock attribute)
(torchelie.nn.SEBlock attribute)
(torchelie.nn.SelfAttention2d attribute)
(torchelie.nn.SinePositionEncoding2d attribute)
(torchelie.nn.Spade2d attribute)
(torchelie.nn.SpadeResBlock attribute)
(torchelie.nn.StyleGAN2Block attribute)
(torchelie.nn.TopLeftConv2d attribute)
(torchelie.nn.UnitGaussianPrior attribute)
(torchelie.nn.WithSavedActivations attribute)
translate() (torchelie.transforms.differentiable.AllAtOnceGeometric method)
transposed (torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
truncated_normal() (in module torchelie.distributions)
U
UBlock (class in torchelie.nn)
UNet (class in torchelie.models)
unfreeze() (in module torchelie.utils)
UniformSampler (class in torchelie.hyper)
UnitGaussianPrior (class in torchelie.nn)
UnlabeledImages (class in torchelie.datasets)
update_usage() (torchelie.nn.VQ method)
upsample_instead() (torchelie.nn.ResBlockBottleneck method)
use_affine_input() (torchelie.models.StyleGAN2Generator method)
use_se() (torchelie.nn.PreactResBlock method)
(torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlock method)
(torchelie.nn.ResBlockBottleneck method)
use_standard_input() (torchelie.models.ResNet method)
V
VGG (class in torchelie.models)
vgg11 (in module torchelie.models)
vgg11_bn (in module torchelie.models)
vgg13 (in module torchelie.models)
vgg13_bn (in module torchelie.models)
vgg16 (in module torchelie.models)
vgg16_bn (in module torchelie.models)
vgg19 (in module torchelie.models)
vgg19_bn (in module torchelie.models)
VisdomLogger (class in torchelie.callbacks)
VQ (class in torchelie.nn)
W
w_avg (torchelie.models.StyleGAN2Generator attribute)
w_to_dict() (torchelie.models.StyleGAN2Generator method)
weight (torchelie.nn.AdaIN2d attribute)
(torchelie.nn.FiLM2d attribute)
(torchelie.nn.MaskedConv2d attribute)
(torchelie.nn.ModulatedConv attribute)
weight_lambda (class in torchelie.nn.utils)
weight_norm_and_equal_lr (class in torchelie.nn.utils)
weight_scale (class in torchelie.nn.utils)
WeightLambda (class in torchelie.nn.utils)
wide() (torchelie.nn.PreactResBlockBottleneck method)
(torchelie.nn.ResBlockBottleneck method)
wide_resnet101 (class in torchelie.models)
wide_resnet50 (class in torchelie.models)
WindowedMetricAvg (class in torchelie.callbacks)
WithIndexDataset (class in torchelie.datasets)
WithSavedActivations (class in torchelie.nn)
X
xavier() (in module torchelie.utils)
Z
zero_grad() (torchelie.optim.Lookahead method)
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