R: Interface to 'TensorFlow SIG Addons'

# Interface to 'TensorFlow SIG Addons'

## Documentation for package ‘tfaddons’ version 0.10.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

A C D E G H I L M O P R S T V

## -- 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 --

extend_with_decoupled_weight_decay | 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 | 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 | Parse time

## -- R --

register_all | Register all
register_custom_kernels | Register custom kernels
register_keras_objects | Register keras objects

## -- 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 | Viterbi decode