Major Features and Improvements
* TensorFlow now builds and runs on Microsoft Windows (tested on Windows 10,
Windows 7, and Windows Server 2016). Supported languages include Python (via
a pip package) and C++. CUDA 8.0 and cuDNN 5.1 are supported for GPU
acceleration. Known limitations include: It is not currently possible to
load a custom op library. The GCS and HDFS file systems are not currently
supported. The following ops are not currently implemented: Dequantize,
QuantizeAndDequantize, QuantizedAvgPool,
QuantizedBatchNomWithGlobalNormalization, QuantizedBiasAdd, QuantizedConcat,
QuantizedConv2D, QuantizedMatmul, QuantizedMaxPool,
QuantizeDownAndShrinkRange, QuantizedRelu, QuantizedRelu6, QuantizedReshape,
QuantizeV2, RequantizationRange, and Requantize.
* Go: Experimental API in Go to create and execute graphs
(https://godoc.org/github.com/tensorflow/tensorflow/tensorflow/go)
* New checkpoint format becomes the default in `tf.train.Saver`. Old V1
checkpoints continue to be readable; controlled by the `write_version`
argument, `tf.train.Saver` now by default writes out in the new V2 format.
It significantly reduces the peak memory required and latency incurred
during restore.
* Added a new library for library of matrix-free (iterative) solvers for
linear equations, linear least-squares, eigenvalues and singular values in
tensorflow/contrib/solvers. Initial version has lanczos bidiagonalization,
conjugate gradients and CGLS.
* Added gradients for `matrix_solve_ls` and `self_adjoint_eig`.
* Large cleanup to add second order gradient for ops with C++ gradients and
improve existing gradients such that most ops can now be differentiated
multiple times.
* Added a solver for ordinary differential equations,
`tf.contrib.integrate.odeint`.
* New contrib module for tensors with named axes, `tf.contrib.labeled_tensor`.
* Visualization of embeddings in TensorBoard.
Breaking Changes to the API
* `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
previously `BUS_ANY` was used.
* `Env::FileExists` and `FileSystem::FileExists` now return a
tensorflow::Status instead of a bool. Any callers to this function can be
converted to a bool by adding .ok() to the call.
* The C API type `TF_SessionWithGraph` has been renamed to `TF_Session`,
indicating its preferred use in language bindings for TensorFlow. What was
previously `TF_Session` has been renamed to `TF_DeprecatedSession`.
* Renamed `TF_Port` to `TF_Output` in the C API.
* 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 previously `BUS_ANY` was used.
* Most RNN cells and RNN functions now use different variable scopes to be
consistent with layers (`tf.contrib.layers`). This means old checkpoints
written using this code will not load after this change without providing
`Saver` a list of variable renames. Examples of variable scope changes
include `RNN` -> `rnn` in `tf.nn.rnn`, `tf.nn.dynamic_rnn` and moving from
`Linear/Matrix` -> `weights` and `Linear/Bias` -> `biases` in most RNN
cells.
* Deprecated tf.select op. tf.where should be used instead.
* `SparseTensor.shape` has been renamed to `SparseTensor.dense_shape`. Same
for `SparseTensorValue.shape`.
* `Env::FileExists` and `FileSystem::FileExists` now return a
`tensorflow::Status` instead of a bool. Any callers to this function can be
converted to a bool by adding `.ok()` to the call.
* C API: Type `TF_SessionWithGraph` has been renamed to `TF_Session`,
indicating its preferred use in language bindings for TensorFlow. What was
previously `TF_Session` has been renamed to `TF_DeprecatedSession`.
* C API: Renamed `TF_Port` to `TF_Output`.
* C API: The caller retains ownership of `TF_Tensor` objects provided to
`TF_Run`, `TF_SessionRun`, `TF_SetAttrTensor` etc.
* Renamed `tf.image.per_image_whitening()` to
`tf.image.per_image_standardization()`
* Move Summary protobuf constructors to `tf.summary` submodule.
* Deprecate `histogram_summary`, `audio_summary`, `scalar_summary`,
`image_summary`, `merge_summary`, and `merge_all_summaries`.
* Combined `batch_*` and regular version of linear algebra and FFT ops. The
regular op now handles batches as well. All `batch_*` Python interfaces were
removed.
* `tf.all_variables`, `tf.VARIABLES` and `tf.initialize_all_variables` renamed
to `tf.global_variables`, `tf.GLOBAL_VARIABLES` and
`tf.global_variables_initializer` respectively.
* `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()`
Bug Fixes and Other Changes
* Use threadsafe version of `lgamma` function.
* Fix `tf.sqrt` handling of negative arguments.
* Fixed bug causing incorrect number of threads to be used for multi-threaded
benchmarks.
* Performance optimizations for `batch_matmul` on multi-core CPUs.
* Improve trace, `matrix_set_diag`, `matrix_diag_part` and their gradients to
work for rectangular matrices.
* Support for SVD of complex valued matrices.
Thanks to our Contributors
This release contains contributions from many people at Google, as well as:
a7744hsc, Abhi Agg, admcrae, Adriano Carmezim, Aki Sukegawa, Alex Kendall,
Alexander Rosenberg Johansen, amcrae, Amlan Kar, Andre Simpelo, Andreas Eberle,
Andrew Hundt, Arnaud Lenglet, b0noI, Balachander Ramachandran, Ben Barsdell,
Ben Guidarelli, Benjamin Mularczyk, Burness Duan, c0g, Changming Sun, chanis,
Corey Wharton, Dan J, Daniel Trebbien, Darren Garvey, David Brailovsky, David
Jones, Di Zeng, DjangoPeng, Dr. Kashif Rasul, drag0, Fabrizio (Misto) Milo,
FabríCio Ceschin, fp, Ghedeon, guschmue, Gökçen Eraslan, Haosdent Huang,
Haroen Viaene, Harold Cooper, Henrik Holst, hoangmit, Ivan Ukhov, Javier
Dehesa, Jingtian Peng, Jithin Odattu, Joan Pastor, Johan Mathe, Johannes Mayer,
Jongwook Choi, Justus Schwabedal, Kai Wolf, Kamil Hryniewicz, Kamran Amini,
Karen Brems, Karl Lattimer, kborer, Ken Shirriff, Kevin Rose, Larissa Laich,
Laurent Mazare, Leonard Lee, Liang-Chi Hsieh, Liangliang He, Luke Iwanski, Marek
Kolodziej, Moustafa Alzantot, MrQianjinsi, nagachika, Neil Han, Nick Meehan,
Niels Ole Salscheider, Nikhil Mishra, nschuc, Ondrej Skopek, OndřEj Filip,
OscarDPan, Pablo Moyano, Przemyslaw Tredak, qitaishui, Quarazy, raix852,
Philipp Helo, Sam Abrahams, SriramRamesh, Till Hoffmann, Tushar Soni, tvn,
tyfkda, Uwe Schmidt, Victor Villas, Vit Stepanovs, Vladislav Gubarev,
wujingyue, Xuesong Yang, Yi Liu, Yilei Yang, youyou3, Yuan (Terry) Tang,
Yuming Wang, Zafar Takhirov, zhongyuk, Ziming Dong, guotong1988
We are also grateful to all who filed issues or helped resolve them, asked and
answered questions, and were part of inspiring discussions.