Interface to 'TensorFlow SIG Addons'

Documentation for package ‘tfaddons’ version 0.10.0

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-- A --

activation_gelu	Gelu
activation_hardshrink	Hardshrink
activation_lisht	Lisht
activation_mish	Mish
activation_rrelu	Rrelu
activation_softshrink	Softshrink
activation_sparsemax	Sparsemax
activation_tanhshrink	Tanhshrink
attention_bahdanau	Bahdanau Attention
attention_bahdanau_monotonic	Bahdanau Monotonic Attention
attention_luong	Implements Luong-style (multiplicative) attention scoring.
attention_luong_monotonic	Monotonic attention mechanism with Luong-style energy function.
attention_monotonic	Monotonic attention
attention_wrapper	Attention Wrapper
attention_wrapper_state	Attention Wrapper State

-- C --

callback_average_model_checkpoint	Average Model Checkpoint
callback_time_stopping	Time Stopping
callback_tqdm_progress_bar	TQDM Progress Bar
crf_binary_score	CRF binary score
crf_decode	CRF decode
crf_decode_backward	CRF decode backward
crf_decode_forward	CRF decode forward
crf_forward	CRF forward
crf_log_likelihood	CRF log likelihood
crf_log_norm	CRF log norm
crf_multitag_sequence_score	CRF multitag sequence score
crf_sequence_score	CRF sequence score
crf_unary_score	CRF unary score

-- D --

decoder	An RNN Decoder abstract interface object.
decoder_base	Base Decoder
decoder_basic	Basic Decoder
decoder_basic_output	Basic decoder output
decoder_beam_search	BeamSearch sampling decoder
decoder_beam_search_output	Beam Search Decoder Output
decoder_beam_search_state	Beam Search Decoder State
decoder_final_beam_search_output	Final Beam Search Decoder Output
decode_dynamic	Dynamic decode

-- E --

Factory function returning an optimizer class with decoupled weight decay

-- G --

gather_tree	Gather tree
gather_tree_from_array	Gather tree from array

-- H --

Hardmax

-- I --

img_adjust_hsv_in_yiq	Adjust hsv in yiq
img_angles_to_projective_transforms	Angles to projective transforms
img_blend	Blend
img_compose_transforms	Compose transforms
img_connected_components	Connected components
img_cutout	Cutout
img_dense_image_warp	Dense image warp
img_equalize	Equalize
img_euclidean_dist_transform	Euclidean dist transform
img_flat_transforms_to_matrices	Flat transforms to matrices
img_from_4D	From 4D image
img_get_ndims	Get ndims
img_interpolate_bilinear	Interpolate bilinear
img_interpolate_spline	Interpolate spline
img_matrices_to_flat_transforms	Matrices to flat transforms
img_mean_filter2d	Mean filter2d
img_median_filter2d	Median filter2d
img_random_cutout	Random cutout
img_random_hsv_in_yiq	Random hsv in yiq
img_resampler	Resampler
img_rotate	Rotate
img_sharpness	Sharpness
img_shear_x	Shear x-axis
img_shear_y	Shear y-axis
img_sparse_image_warp	Sparse image warp
img_to_4D	To 4D image
img_transform	Transform
img_translate	Translate
img_translate_xy	Translate xy dims
img_translations_to_projective_transforms	Translations to projective transforms
img_unwrap	Uwrap
img_wrap	Wrap
install_tfaddons	Install TensorFlow SIG Addons

-- L --

layer_activation_gelu	Gaussian Error Linear Unit
layer_correlation_cost	Correlation Cost Layer.
layer_filter_response_normalization	FilterResponseNormalization
layer_group_normalization	Group normalization layer
layer_instance_normalization	Instance normalization layer
layer_maxout	Maxout layer
layer_multi_head_attention	Keras-based multi head attention layer
layer_nas_cell	Neural Architecture Search (NAS) recurrent network cell.
layer_norm_lstm_cell	LSTM cell with layer normalization and recurrent dropout.
layer_poincare_normalize	Project into the Poincare ball with norm <= 1.0 - epsilon
layer_sparsemax	Sparsemax activation function
layer_weight_normalization	Weight Normalization layer
lookahead_mechanism	Lookahead mechanism
loss_contrastive	Contrastive loss
loss_giou	Implements the GIoU loss function.
loss_hamming	Hamming loss
loss_lifted_struct	Lifted structured loss
loss_npairs	Npairs loss
loss_npairs_multilabel	Npairs multilabel loss
loss_pinball	Pinball loss
loss_sequence	Weighted cross-entropy loss for a sequence of logits.
loss_sigmoid_focal_crossentropy	Sigmoid focal crossentropy loss
loss_sparsemax	Sparsemax loss
loss_triplet_hard	Triplet hard loss
loss_triplet_semihard	Triplet semihard loss

-- M --

metrics_f1score	F1Score
metric_cohen_kappa	Computes Kappa score between two raters
metric_fbetascore	FBetaScore
metric_hamming_distance	Hamming distance
metric_mcc	MatthewsCorrelationCoefficient
metric_multilabel_confusion_matrix	MultiLabelConfusionMatrix
metric_rsquare	RSquare This is also called as coefficient of determination. It tells how close are data to the fitted regression line. Highest score can be 1.0 and it indicates that the predictors perfectly accounts for variation in the target. Score 0.0 indicates that the predictors do not account for variation in the target. It can also be negative if the model is worse.

-- O --

optimizer_conditional_gradient	Conditional Gradient
optimizer_decay_adamw	Optimizer that implements the Adam algorithm with weight decay
optimizer_decay_sgdw	Optimizer that implements the Momentum algorithm with weight_decay
optimizer_lamb	Layer-wise Adaptive Moments
optimizer_lazy_adam	Lazy Adam
optimizer_moving_average	Moving Average
optimizer_novograd	NovoGrad
optimizer_radam	Rectified Adam (a.k.a. RAdam)
optimizer_swa	Stochastic Weight Averaging
optimizer_yogi	Yogi

-- P --

Parse time

-- R --

-- S --

safe_cumprod	Safe cumprod
sampler	Sampler
sampler_custom	Base abstract class that allows the user to customize sampling.
sampler_greedy_embedding	Greedy Embedding Sampler
sampler_inference	Inference Sampler
sampler_sample_embedding	Sample Embedding Sampler
sampler_scheduled_embedding_training	A training sampler that adds scheduled sampling
sampler_scheduled_output_training	Scheduled Output Training Sampler
sampler_training	A Sampler for use during training.
sample_bernoulli	Bernoulli sample
sample_categorical	Categorical sample
skip_gram_sample	Skip gram sample
skip_gram_sample_with_text_vocab	Skip gram sample with text vocab

-- T --

tfaddons_version	Version of TensorFlow SIG Addons
tile_batch	Tile batch

-- V --

Viterbi decode