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RFC: Move from tf.contrib to addons (#37)
* Checkpoint addons RFC for review * Add code review to RFC Add future pull request information to criteria Update modified date added some description RFC Move to addons * Add weight decay optimizers * Remove conv2d_in_plane * Add group_norm * Accept addons RFC
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‎rfcs/20181214-move-to-addons.md‎

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# Move from tf.contrib to tensorflow/addons
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| Status | Accepted |
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:-------------- |:---------------------------------------------------- |
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| **Author(s)** | Sean Morgan ([email protected]), Armando Fandango ([email protected]) |
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| **Sponsor** | Karmel Allison ([email protected]) |
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| **Updated** | 2018-12-16 |
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## Objective
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With the upcoming removal of tf.contrib in TF 2.0, we are in the process
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of deciding what existing functionality will be moved and maintained in
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the [tensorflow/addons](https://github.com/tensorflow/addons)
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repository.
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This document details what functionality the SIG plans to move and
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invites discussion around the decisions.
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## Motivation
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In this RFC, we are soliciting discussion regarding what tf.contrib code
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should be moved to tensorflow/addons. This RFC discussion will help us
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determine the value of moving code and their respective
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maintainability aspects.
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## Design Proposal
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### Criteria for moving
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1) The functionality is not otherwise available in TensorFlow
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1) There is sufficient interest in the community to maintain the code being moved
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1) The code conforms to an established API pattern (Some pieces can be refactored if needed)
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It is worth noting that just because some functionality isn't part of
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the initial move, does not mean it won't be eventually part of addons
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if there is value. We will begin reviewing pull requests to the
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repository after the directory structure is shaped during the initial move.
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### Code to be moved from tf.contrib to addons
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| Module (tf.contrib) | Class/Function | Rationale |
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|:----------------------- |:----------- |:------------------------------------ |
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| opt.external_optimizer | ExternalOptimizerInferface | Base class for external optimizers used in OSS projects |
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| opt.external_optimizer | ScipyOptimizerInterface | Significant usage in OSS projects |
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| opt.lazy_adam_optimizer | LazyAdamOptimizer | Significant usage in OSS projects / discussions |
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| opt.moving_average_optimizer | MovingAverageOptimizer | Significant usage in OSS projects |
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| layers.layers | dense_to_sparse | Useful functionality and discussion around it |
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| layers.layers | layer_norm | Heavily used is OSS projects / From impactful paper |
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| layers.layers | maxout | From impactful paper |
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| layers.layers | poincare_normalize | Functionality not available / Useful for hyperbolic embeddings |
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| layers.normalization | instance_norm | Heavily used is OSS projects / Used for style xfer |
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| layers.normalization | group_norm | Will be moved as a generalized case of layer_norm and instance_norm |
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| losses.metric_loss_ops | pairwise_distance | Useful functionality not otherwise available |
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| losses.metric_loss_ops | contrastive_loss | Useful functionality not otherwise available |
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| losses.metric_loss_ops | masked_maximum | Useful functionality not otherwise available |
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| losses.metric_loss_ops | masked_minimum | Useful functionality not otherwise available |
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| losses.metric_loss_ops | triplet_semihard_loss | Useful functionality not otherwise available / From impactful paper |
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| losses.metric_loss_ops | npairs_loss | Useful functionality not otherwise available |
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| losses.metric_loss_ops | npairs_loss_multilabel | Useful functionality not otherwise available |
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| losses.metric_loss_ops | lifted_struct_loss | Useful functionality not otherwise available |
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| sparsemax.sparsemax | ALL | Useful functionality not otherwise available / Volunteers to maintain |
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| image.dense_image_warp | dense_image_warp | Useful functionality not otherwise available |
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| image.distort_image_ops | random_hsv_in_yiq | Useful functionality not otherwise available |
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| image.distort_image_ops | adjust_hsv_in_yiq | Useful functionality not otherwise available |
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| image.image_ops | rotate | Useful functionality not otherwise available / Several uses in OSS found |
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| image.image_ops | translate | Useful functionality not otherwise available |
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| image.image_ops | angles_to_projective_transforms | Useful functionality not otherwise available / Several uses in OSS found |
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| image.image_ops | translations_to_projective_transforms | Useful functionality not otherwise available |
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| image.image_ops | transform | Useful functionality not otherwise available / Several uses in OSS found |
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| image.image_ops | compose_transforms | Useful functionality not otherwise available / Several uses in OSS found |
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| image.image_ops | flat_transforms_to_matrices | Helper util used a few times in module |
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| image.image_ops | matrices_to_flat_transforms | Helper util used a few times in module |
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| image.image_ops | connected_components | Useful functionality not otherwise available |
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| text.skip_gram_ops | ALL | Useful functionality not otherwise available |
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| crf.crf | ALL | Heavily used by the NLP community |
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| opt.weight_decay_optimizers | DecoupledWeightDecayExtension | ~SOTA convergence speeds / Needs refactored as Wrapper subclass |
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| opt.weight_decay_optimizers | AdamWOptimizer | ~SOTA convergence speeds / Needs refactored as wrapper + keras Adam |
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| opt.weight_decay_optimizers | MomentumWOptimizer | ~SOTA convergence speeds / Needs refactored as wrapper + keras SGD|
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### Code that will not be moved from tf.contrib pending objections
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| Module (tf.contrib) | Class/Function | Rationale |
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|:----------------------- |:----------- |:------------------------------------ |
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| opt.addsign | AddSignOptimizer | No OSS uses found / Needs refactored as OptimizerV2 subclass |
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| opt.agn_optimizer | AGNOptimizer | No OSS uses found / Needs refactored as OptimizerV2 subclass |
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| opt.drop_stale_gradient_optimizer | DropStaleGradientOptimizer | No OSS uses found / Needs refactored as Wrapper subclass |
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| opt.elastic_average_optimizer | ElasticAverageOptimizer | No OSS uses found / Needs refactored as Wrapper subclass |
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| opt.ggt | GGTOptimizer | No OSS uses found |
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| opt.lars_optimizer | LARSOptimizer | No OSS uses found / Needs refactored as OptimizerV2 subclass |
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| opt.shampoo | ShampooOptimizer | No OSS uses found / Needs refactored as OptimizerV2 subclass |
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| opt.matrix_functions | matrix_inverse_pth_root | Used in opt.shampoo |
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| opt.model_average_optimizer | ModelAverageOptimizer | No OSS uses found / Needs refactored as Wrapper subclass |
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| opt.multitask_optimizer_wrapper | MultitaskOptimizerWrapper | No OSS uses found / Needs refactored as Wrapper subclass |
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| opt.multitask_optimizer_wrapper | clip_gradients_by_global_norm | No OSS uses found / Specific to MultitaskOptimizers / At least partly covered in Keras optimizer |
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| opt.powersign | PowerSignOptimizer | No OSS uses found / Needs refactored as OptimizerV2 subclass |
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| opt.sign_decay | get_linear_decay_fn | No OSS usage / Used in AddSign & PowerSign |
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| opt.sign_decay | get_cosine_decay_fn | No OSS usage / Not an optimizer |
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| opt.sign_decay | get_restart_decay_fn | No OSS usage / Not an optimizer |
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| opt.reg_adagrad_optimizer | RegAdagradOptimizer | No OSS uses found / Needs refactored as keraas Adagrad subclass |
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| opt.variable_clipping_optimizer | VariableClippingOptimizer | No OSS uses found / Needs refactored as Wrapper subclass / partial covered by keras norm clip |
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| opt.weight_decay_optimizers | ShampooWOptimizer | No OSS uses found |
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| opt.weight_decay_optimizers | extend_with_decoupled_weight_decay | No OSS uses found / Functional paradigm - factory function |
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| layers.embedding_ops | scattered_embedding_lookup_sparse | No OSS uses found |
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| layers.embedding_ops | embedding_lookup_unique | No OSS uses found |
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| layers.encoders | bow_encoder | Creates variables, but does not subclass Layer |
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| layers.encoders | embed_sequence | Creates variables, but does not subclass Layer |
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| layers.layers | convolution2d_in_plane | No OSS uses found |
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| layers.layers | GDN | No OSS uses found |
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| layers.layers | scale_gradient | No OSS uses found |
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| layers.layers | sequence_to_images | No OSS uses found |
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| layers.layers | spatial_softmax | One OSS project found / Needs refactored as base Layer subclass / Uses get_variable_collections |
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| layers.optimizers | optimize_loss | Concience wrapper to build a training op / Would need refactor to stick to TF2.0 APIs |
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| layers.optimizers | adaptive_clipping_fn | No OSS uses found |
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| layers.rev_block_lib | RevBlock | No OSS uses found |
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| layers.rev_block_lib | recompute_grad | No OSS uses found |
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| layers.summaries | summarize_tensor | One OSS project found / Very simple wrapper |
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| layers.utils | constant_value | Simple wrapper... need a good reason to support |
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| nn.alpha_dropout | alpha_dropout | No OSS uses found / Needs refactored as base Layer subclass |
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| nn.fwd_gradients | fwd_gradients | No OSS uses found |
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| nn.sampling_ops | rank_sampled_softmax_loss | One OSS use found / Needs to utilize sampled_softmax_loss_v2 |
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| nn.sampling_ops | sampled_sparse_softmax_loss | No OSS uses found / Needs to utilize sampled_softmax_loss_v2 |
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| nn.scaled_softplus | scaled_softplus | No OSS uses found |
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| losses.metric_loss_ops | update_1d_tensor | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | get_cluster_assignment | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | compute_facility_energy | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | compute_clustering_score | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | compute_augmented_facility_locations | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | update_medoid_per_cluster | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | update_all_medoids | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | compute_augmented_facility_locations_pam | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | compute_gt_cluster_score | No OSS uses found / Large amount of code related to cluster_loss |
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| losses.metric_loss_ops | cluster_loss | No OSS uses found / Large amount of code related to cluster_loss |
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| image.image_ops | bipartite_match | No OSS uses found / Should live in linalg or somewhere else? |
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| image.interpolate_spline | interpolate_spline | One OSS uses found / Should live in tf.signal? |
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| image.single_image_random_dot_stereograms | single_image_random_dot_stereograms | No OSS uses found |
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| image.parse_image_wrap | sparse_image_warp | No OSS uses found |
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| resampler.resampler_ops | ALL | Pending community interest |
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| solvers | ALL | Pending community interest to maintain |
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| integrate | ALL | Pending community interest to maintain |
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### Code that will not be copied from tf.contrib to addons and hence would not be available in either of tf.contrib or addons
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| Module (tf.contrib) | Class/Function | Rationale |
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|:----------------------- |:----------- |:------------------------------------ |
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| opt.adamax | AdaMaxOptimizer | Available in tf.keras.optimizers |
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| opt.matrix_functions | matrix_square_root | Available as linalg_ops.matrix_square_root |
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| opt.nadam_optimizer | NadamOptimizer | Available in tf.keras.optimizers |
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| layers.embedding_ops | safe_embedding_lookup_sparse | Exists as tf.nn.safe_embedding_lookup_sparse |
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| layers.embedding_ops | embedding_lookup_sparse_with_distributed_aggregation | Replaced by emedding_lookup_sparse_v2 |
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| layers.feature_column | ALL | Better version available in tf.feature_column |
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| layers.initizalizers | xavier_initializer | tf.keras has a glorot_normal and glorot_uniform |
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| layers.initizalizers | variance_scaling_initializer | Exists in tf.keras.initializers |
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| layers.layers | avg_pool2d | Exists in tf.keras.layers |
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| layers.layers | avg_pool3d | Exists in tf.keras.layers |
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| layers.layers | batch_norm | Exists in tf.keras.layers |
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| layers.layers | bias_add | Exists in tf.keras.layers |
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| layers.layers | conv1d | Exists in tf.keras.layers |
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| layers.layers | conv2d | Exists in tf.keras.layers |
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| layers.layers | conv3d | Exists in tf.keras.layers |
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| layers.layers | conv2d_in_plane | Functional Alias |
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| layers.layers | conv2d_transpose | Exists in tf.keras.layers |
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| layers.layers | conv3d_transpose | Exists in tf.keras.layers |
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| layers.layers | convolution | Exists in tf.keras.layers |
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| layers.layers | convolution1d | Exists in tf.keras.layers |
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| layers.layers | convolution2d | Exists in tf.keras.layers |
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| layers.layers | convolution2d_transpose | Exists in tf.keras.layers |
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| layers.layers | convolution3d | Exists in tf.keras.layers |
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| layers.layers | convolution3d_transpose | Exists in tf.keras.layers |
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| layers.layers | dropout | Exists in tf.keras.layers |
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| layers.layers | elu | Exists in tf.keras.layers |
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| layers.layers | flatten | Exists in tf.keras.layers |
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| layers.layers | fully_connected | Exists in tf.keras.layers |
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| layers.layers | gdn | Functional interface of GDN |
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| layers.layers | images_to_sequence | No OSS uses found / Functional paradigm |
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| layers.layers | linear | Exists in tf.keras.layers |
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| layers.layers | pool | Exists in tf.keras.layers |
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| layers.layers | max_pool2d| Exists in tf.keras.layers |
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| layers.layers | max_pool3d | Exists in tf.keras.layers |
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| layers.layers | one_hot_encoding | Exists in tf.keras / Uses collections |
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| layers.layers | relu | Exists in tf.keras.layers |
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| layers.layers | relu6 | Exists in tf.keras.layers |
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| layers.layers | repeat | Exists as sequential model |
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| layers.layers | separable_conv2d | Exists in tf.keras.layers |
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| layers.layers | separable_convolution2d | Exists in tf.keras.layers |
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| layers.layers | softmax | Exists in tf.keras.layers |
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| layers.layers | stack | Exists as sequential model / Uses variable scoping |
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| layers.layers | unit_norm | Exists in linalg |
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| layers.layers | legacy_fully_connected | Legacy layer |
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| layers.layers | legacy_linear | Legacy layer |
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| layers.layers | legacy_relu | Legacy layer |
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| layers.regularizers | l1_regularizer | Available in tf.keras.regularizers |
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| layers.regularizers | l2_regularizer | Available in tf.keras.regularizers |
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| layers.regularizers | l1_l2_regularizer | Available in tf.keras.regularizers |
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| layers.regularizers | sum_regularizer | Trivial convience wrapper |
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| layers.regularizers | apply_regularization | Uses collections |
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| layers.rev_block_lib | rev_block | Functional paradigm for RevBlock |
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| layers.summaries | summarize_tensors | Trivial list comprehension |
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| layers.summaries | summarize_collection | Uses collections |
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| layers.summaries | summarize_activations | Uses collecftions |
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| layers.target_column | ALL | Deprecated since Estimators |
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| layers.utils | collect_named_output | Unsupported tensor alias API |
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| layers.utils | append_tensor_alias | Unsupported tensor alias API |
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| layers.utils | gather_tensors_aliases | Unsupported tensor alias API |
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| layers.utils | get_tensor_aliases | Unsupported tensor alias API |
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| layers.utils | convert_collection_to_dict | Uses collections |
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| layers.utils | static_cond | Simple wrapper / No OSS use |
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| layers.utils | smart_cond | Simple wrapper / Little OSS use |
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| layers.utils | get_variable_collections | Uses collections |
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| layers.utils | channel_dimension | Simple wrapper / No OSS use |
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| layers.utils | last_dimension | Simple wrapper / No OSS use |
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| layers.utils | two_element_tuple | No OSS use |
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| layers.utils | n_positive_integers | No OSS use |
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| nn.cross_entropy | ALL | Deprecated Losses |
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| losses.loss_ops | ALL | Available in core tf.losses |
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**Notes:**
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* More details of our code review can be found in [this spreadsheet](https://docs.google.com/spreadsheets/d/1hYJchHp1y1t2U6htq5UXxMxWlGxxtOyyNHDF8_qhtQQ/edit#gid=185512613)
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* We used [this analysis tool](https://tf-contrib-analyzer.herokuapp.com/) to detect OSS usage.
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## Questions and Discussion Topics
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* Are there any modules being excluded from the move that you feel have substantial value to the community?
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* Are there any new modules that you feel should be added to addons from somewhere else apart from tf.contrib
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* We're actively collecting volunteers to help move, refactor and/or maintain in Addons (Please reachout to our [mailing list](https://groups.google.com/a/tensorflow.org/forum/#!forum/addons)
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or [gitter channel](https://gitter.im/tensorflow/sig-addons) if you have interest in helping our community.
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## After Request Notes
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* Now that the review period has ended, please post all suggested
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additions/removals directly to the tensorflow/addons [issues page](https://github.com/tensorflow/addons/issues)

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