提交 9937f8c6 编写于 作者: G gunan 提交者: GitHub

Update release notes for 1.0.0-alpha. (#6747)

* Update release notes for 1.0.0-alpha.

* Add numpy compatibility to release notes.
上级 e9c76254
# Changes since the last release # Release 1.0.0-alpha
## Major Features and Improvements
* TensorFlow Debugger (tfdbg): command-line interface and API.
* New python 3 docker images added.
* Made pip packages pypi compliant. TensorFlow can now be installed by `pip
install tensorflow` command.
* Several python API calls have been changed to resemble NumPy more closely.
* Android: person detection + tracking demo implementing Scalable Object
Detection using Deep Neural Networks.
* Android: pre-built libs are now built nightly.
* New (experimental) [Java API](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/java).
## Breaking Changes to the API ## Breaking Changes to the API
* TensorFlow/models have been moved to a separate github repository.
* Division and modulus operators (/, //, %) now match Python (flooring) * Division and modulus operators (/, //, %) now match Python (flooring)
semantics. This applies to `tf.div` and `tf.mod` as well. To obtain forced semantics. This applies to `tf.div` and `tf.mod` as well. To obtain forced
integer truncation based behaviors you can use `tf.truncatediv` integer truncation based behaviors you can use `tf.truncatediv`
...@@ -53,12 +65,80 @@ ...@@ -53,12 +65,80 @@
made `tf.sparse_split` require keyword arguments. made `tf.sparse_split` require keyword arguments.
* Deprecated `tf.concat` operator. Please switch to use `tf.concat_v2` for now. * Deprecated `tf.concat` operator. Please switch to use `tf.concat_v2` for now.
In the Beta release, we will update `tf.concat` to match argument order of In the Beta release, we will update `tf.concat` to match argument order of
`tf.concat_v2. `tf.concat_v2`.
* tf.image.decode_jpeg by default uses the faster DCT method, sacrificing * `tf.image.decode_jpeg` by default uses the faster DCT method, sacrificing
a little fidelity for improved speed. One can revert to the old a little fidelity for improved speed. One can revert to the old
behavior by specifying the attribute dct_method='INTEGER_ACCURATE'. behavior by specifying the attribute `dct_method='INTEGER_ACCURATE'`.
* `tf.complex_abs` has been removed from the Python interface. `tf.abs` * `tf.complex_abs` has been removed from the Python interface. `tf.abs`
supports complex tensors and should be used instead. supports complex tensors and should be used instead.
* Template.`var_scope` property renamed to `.variable_scope`
* SyncReplicasOptimizer is removed and SyncReplicasOptimizerV2 renamed to SyncReplicasOptimizer.
* `tf.zeros_initializer()` and `tf.ones_initializer()` now return a callable
that must be called with initializer arguments, in your code replace
`tf.zeros_initializer` with `tf.zeros_initializer()`.
* `SparseTensor.shape` has been renamed to `SparseTensor.dense_shape`. Same for
`SparseTensorValue.shape`.
* Remove old tf summary ops, like `tf.scalar_summary` and `tf.histogram_summary`.
Use `tf.summary.scalar` and `tf.summary.histogram` instead.
* Remove tf.train.SummaryWriter and tf.train.SummaryWriterCache.
* Removes RegisterShape from public API. Use C++ shape function registration
instead.
* Deprecated `_ref` dtypes from the python API.
## Bug Fixes and Other Changes
* New op: `parallel_stack`.
* Introducing common tf io compression options constants for
RecordReader/RecordWriter.
* Add `sparse_column_with_vocabulary_file`, to specify a feature column that
transform string features to IDs, where the mapping is defined by a vocabulary
file.
* Added `index_to_string_table` which returns a lookup table that maps indices to
strings.
* Add `string_to_index_table`, which returns a lookup table that matches strings
to indices.
* Add a `ParallelForWithWorkerId` function.
* Add `string_to_index_table`, which returns a lookup table that matches strings
to indices.
* Support restore session from checkpoint files in v2 in `contrib/session_bundle`.
* Added a tf.contrib.image.rotate function for arbitrary angles.
* Added `tf.contrib.framework.filter_variables` as a convenience function to
filter lists of variables based on regular expressions.
* Remove old tf summary ops, like `tf.scalar_summary` and `tf.histogram_summary`.
Use `tf.summary.scalar` and `tf.summary.histogram` instead.
* `make_template()` takes an optional `custom_getter_ param`.
* Added comment about how existing directories are handled by
`recursive_create_dir`.
* Added an op for QR factorizations.
* Divides and mods in Python API now use flooring (Python) semantics.
* Android: cmake/gradle build for TensorFlow Inference library under
`contrib/android/cmake`
* Android: Much more robust Session initialization code.
* Android: TF stats now exposed directly in demo and log when debug mode is
active
* Android: new/better README.md documentation
## Thanks to our Contributors
This release contains contributions from many people at Google, as well as:
Aaron Hu, Abhishek Aggarwal, Adam Michael, Adriano Carmezim, @AfirSraftGarrier,
Alexander Novikov, Alexander Rosenberg Johansen, Andrew Gibiansky, Andrew Hundt,
Anish Shah, Anton Loss, @b0noI, @BoyuanJiang, Carl Thomé, Chad Kennedy, Comic
Chang, Connor Braa, Daniel N. Lang, Daniel Trebbien,
@danielgordon10, Darcy Liu, Darren Garvey, Dmitri Lapin, Eron Wright, Evan
Cofer, Fabrizio Milo, Finbarr Timbers, Franck Dernoncourt, Garrett Smith,
@guschmue, Hao Wei, Henrik Holst, Huazuo Gao, @Ian, @Issac, Jacob Israel,
Jangsoo Park, Jin Kim, Jingtian Peng, John Pope, Kye Bostelmann, Liangliang He,
Ling Zhang, Luheng He, Luke Iwanski, @lvli, Michael Basilyan, Mihir Patel,
Mikalai Drabovich, Morten Just, @newge, Nick Butlin, Nishant Shukla,
Pengfei Ni, Przemyslaw Tredak, @rasbt, @Ronny, Rudolf Rosa, @RustingSword,
Sam Abrahams, Sam Putnam, @SeongAhJo, Shi Jiaxin, @skavulya, Steffen MüLler,
@TheUSER123, @tiriplicamihai, @vhasanov, Victor Costan, Vit Stepanovs,
Wangda Tan, Wenjian Huang, Xingdong Zuo, Yaroslav Bulatov, Yota Toyama,
Yuan (Terry) Tang, Yuxin Wu
We are also grateful to all who filed issues or helped resolve them, asked and
answered questions, and were part of inspiring discussions.
# Release 0.12.0 # Release 0.12.0
...@@ -98,15 +178,15 @@ ...@@ -98,15 +178,15 @@
## Breaking Changes to the API ## Breaking Changes to the API
* `BusAdjacency` enum replaced with a protocol buffer `DeviceLocality`. PCI bus * `BusAdjacency` enum replaced with a protocol buffer `DeviceLocality`. PCI bus
indexing now starts from 1 instead of 0, and bus_id==0 is used where indexing now starts from 1 instead of 0, and `bus_id==0` is used where
previously BUS_ANY was used. previously `BUS_ANY` was used.
* `Env::FileExists` and `FileSystem::FileExists` now return a tensorflow::Status * `Env::FileExists` and `FileSystem::FileExists` now return a tensorflow::Status
intead of a bool. Any callers to this function can be converted to a bool intead of a bool. Any callers to this function can be converted to a bool
by adding .ok() to the call. by adding .ok() to the call.
* The C API type `TF_SessionWithGraph` has been renamed to `TF_Session`, * The C API type `TF_SessionWithGraph` has been renamed to `TF_Session`,
indicating its preferred use in language bindings for TensorFlow. indicating its preferred use in language bindings for TensorFlow.
What was previously `TF_Session` has been renamed to `TF_DeprecatedSession`. What was previously `TF_Session` has been renamed to `TF_DeprecatedSession`.
* Renamed TF_Port to TF_Output in the C API. * Renamed `TF_Port` to `TF_Output` in the C API.
* Removes RegisterShape from public API. Use C++ shape function registration instead. * Removes RegisterShape from public API. Use C++ shape function registration instead.
indexing now starts from 1 instead of 0, and `bus_id==0` is used where indexing now starts from 1 instead of 0, and `bus_id==0` is used where
previously `BUS_ANY` was used. previously `BUS_ANY` was used.
...@@ -141,7 +221,7 @@ ...@@ -141,7 +221,7 @@
`tf.global_variables_initializer` respectively. `tf.global_variables_initializer` respectively.
* `tf.zeros_initializer()` and `tf.ones_initializer()` now return a callable * `tf.zeros_initializer()` and `tf.ones_initializer()` now return a callable
that must be called with initializer arguments, in your code replace that must be called with initializer arguments, in your code replace
tf.zeros_initializer with tf.zeros_initializer() `tf.zeros_initializer` with `tf.zeros_initializer()`
## Bug Fixes and Other Changes ## Bug Fixes and Other Changes
......
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