Created a FAQ for TF 2.0. #78
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
I think this doc should live with either the TF 2.0 release itself, or on the https://www.tensorflow.org/alpha page |
|
(And, I've been filled in on reasons this might not be able to happen.) |
|
tesnorflow/doc maybe another choice. |
ewilderj
approved these changes
Apr 3, 2019
|
Awesome! Thanks, @ewilderj. 😄 🎉 |
broken
pushed a commit
to broken/community
that referenced
this pull request
Apr 30, 2019
Adding 2.0 related FAQ to the Testing group.
karllessard
added a commit
to karllessard/tensorflow-community
that referenced
this pull request
May 10, 2019
* Adding a doc to deprecate collections * Responding to Karmels comments * Minor fix to VariableTracker sample code * RFC for random numbers in TensorFlow 2.0 * Changes after some feedback * Removed 'global_seed' in the main code and showed the design with 'global_seed' in the Questions section. * Some changes after feedback * A tweak * Change after feedback * A tweak * changes * changes * fix link * new-rfc * changes * Update rfcs/20181225-tf-backend.md Co-Authored-By: alextp <apassos@google.com> * Added some considerations about tf.function * Renamed the internal name "op_generator" to "global_generator" * Changed seed size from 256 to 1024 bits * Initial signpost for community meetings Adding this so there is basic information about how to find the community calendar and get invited to meetings. * Add iCal link too * changes * Initial version of embedding and partitioned variable RFC. * Fix one formatting issue. * Fix another formatting issue. * Use markdown language for the table instead of HTML. * Add tensorflow/io R Package CRAN release instructions (tensorflow#53) * Added Design Review Notes * Make clear distinction between embedding variables and loadbalancing variables. * Added decisions below each question, and "how to use generators with distribution strategies". * Adopted Dong Lin's suggestions * Add a paragraph pointing out the problem with the `partition_strategy` argument. * RFC: Move from tf.contrib to addons (tensorflow#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 * Update alternatives since `DynamicPartition` and `DynamicStitch` do have GPU kernels. * Add a section for saving and restore `PartitionedVariable`. * Mention that variable types can be nested, attention needs to be paid to their saving and restoring mechanism. * Create README.md (tensorflow#57) * Splitted `_state_var` into `_state_var` and `_alg_var` (because of concerns from implementation), and changed status to "Accepted" * Updated timestamp * Moved the auto-selection of algorithm from `create_rng_state` to `Generator.__init__` * Update according to the discussion * Move performance heuristics in Distribution Strategy level. We will not expose knobs for users to control; * Emphasize that embedding support in v2 will all be via `Embedding` layer. Users can use `tf.compat.v1` to handle embedding by themselves; * Mention that default `partition_strategy` in v1 `embedding_lookup` is "mod", which will possibly break users's model when they update to TF 2.0; * We want to prioritize shuffling embedding after 2.0 release; * We have plans to serialize and deserialize `Embedding` layer and Distribution Strategies to allow loading a saved model to a different number of partitions. * Update relese binary build command for sig-io (tensorflow#58) This PR updates relese binary build command for sig-io Signed-off-by: Yong Tang <yong.tang.github@outlook.com> * Add Bryan to SIG IO release team (tensorflow#59) * Change to accepted * Add link to TensorFlow IO R package * Updated link for the friction log. (tensorflow#64) * Switch DistStrat revised API examples to TensorFlow 2 style. (tensorflow#63) * RFC: Attention for Dense Networks on Keras (tensorflow#54) * Design review for "Attention for Dense Networks" * RFC: Stateful Containers with tf.Module (tensorflow#56) * Create 20190117-tf-module.md * Update 20190117-tf-module.md * Loosen return type for variable properties. * Use Dense consistently. Thanks brilee@ for spotting! * Remove convert_to_tensor from examples. This wasn't ever required and including it might cause confusion. h/t pluskid@ gehring@ and awav@ * Remove owned_* methods. * Document `_flatten` See tensorflow/tensorflow@5076adf6 for more context. * Fix typo in module name. Thanks k-w-w@! * Update 20190117-tf-module.md * RFC: New tf.print (tensorflow#14) * New tf.print proposal * Attempt to fix table of contents * Removed not-working TOC label * Minor updates to the doc. * Update tf.print to be accepted * Added design review notes * Marking doc as accepted * Update cond_v2 design doc (tensorflow#70) * Update to bring in line with implementation * Added the symbol map to the RFC. * Updated testing section of the Community site. * Removed the 100%, formatting tweaks. * Update CHARTER.md * Change contact email address I will leave my current company soon, so update my email. * Create README.md * Logos for SIGs * Update README.md * Update addons owners (tensorflow#85) Add Yan Facai as another project lead. * Created a FAQ for TF 2.0. (tensorflow#78) Adding 2.0 related FAQ to the Testing group. * Request and charter for SIG JVM (tensorflow#86) Chartering docs for SIG JVM * Update CODEOWNERS Add @karllessard, @sjamesr and @tzolov as code owners for sigs/jvm. * Update CODEOWNERS Add missing / * Update CODEOWNERS Add @dynamicwebpaige as owner for sigs/testing/ * Update RFC with current information (tensorflow#89) Make current to SIG Addons * RFC: TF on Demand Project (tensorflow#69) * Adding an RFC for TF on Demand Project. * modified one line in tf-on-demand md file. * Changing RFC status from PROPOSED to ACCEPTED. * RFC: SavedModel Save/Load in 2.x (tensorflow#34) * RFC for SavedModel Save/Load in 2.x * Minor edits and a discussion topic for load() with multiple MetaGraphs * Tweak to the "Imported representations of signatures" section * Update "Importing existing SavedModels" with the .signatures change * Update RFC and add review notes * Status -> accepted * Update CHARTER.md New leads. * Update 20180920-unify-rnn-interface.md (tensorflow#81) Typo fix. * Update yyyymmdd-rfc-template.md Adding "user benefit" section into the RFC template, to encourage articulating the benefit to users in a clear way. * Update while_v2 design doc (tensorflow#71) * Update while_v2 design doc, include link to implementation * Update TF 2.0 FAQ to link to TensorBoard TF 2.0 tutorial (tensorflow#94) * CLN: update sig addons logo png (tensorflow#99) * Add SIG Keras Add a reference link to Keras' governance repository for SIG Keras. * RFC: String Tensor Unification (tensorflow#91) * RFC: String Tensor Unification * Updated rfcs/20190411-string-unification.md Updated TFLite sections to address feedback from @jdduke. Marked as Accepted. * Start RFC for tensor buffers
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.