Man pages for tfaddons
Interface to 'TensorFlow SIG Addons'
| 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... |
| attention_monotonic | Monotonic attention |
| attention_wrapper | Attention Wrapper |
| attention_wrapper_state | Attention Wrapper State |
| 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 |
| decode_dynamic | Dynamic decode |
| 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 |
| extend_with_decoupled_weight_decay | Factory function returning an optimizer class with decoupled... |
| gather_tree | Gather tree |
| gather_tree_from_array | Gather tree from array |
| hardmax | Hardmax |
| 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 |
| 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 |
| 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.... |
| metrics_f1score | F1Score |
| optimizer_conditional_gradient | Conditional Gradient |
| optimizer_decay_adamw | Optimizer that implements the Adam algorithm with weight... |
| optimizer_decay_sgdw | Optimizer that implements the Momentum algorithm with... |
| 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 |
| parse_time | Parse time |
| reexports | Objects exported from other packages |
| register_all | Register all |
| register_custom_kernels | Register custom kernels |
| register_keras_objects | Register keras objects |
| safe_cumprod | Safe cumprod |
| sample_bernoulli | Bernoulli sample |
| sample_categorical | Categorical sample |
| sampler | Sampler |
| sampler_custom | Base abstract class that allows the user to customize... |
| 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. |
| skip_gram_sample | Skip gram sample |
| skip_gram_sample_with_text_vocab | Skip gram sample with text vocab |
| tfaddons_version | Version of TensorFlow SIG Addons |
| tile_batch | Tile batch |
| viterbi_decode | Viterbi decode |
