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Release Notes Published
Release 1.5.0
Breaking Changes
- Prebuilt binaries are now built against CUDA 9 and cuDNN 7.
- Starting from 1.6 release, our prebuilt binaries will use AVX instructions. This may break TF on older CPUs.
Major Features And Improvements
- Eager execution preview version is now available.
- TensorFlow Lite dev preview is now available.
- CUDA 9 and cuDNN 7 support.
- Accelerated Linear Algebra (XLA):
- Add
complex64
support to XLA compiler. bfloat
support is now added to XLA infrastructure.- Make
ClusterSpec
propagation work with XLA devices. - Use a determinisitic executor to generate XLA graph.
- Add
tf.contrib
:tf.contrib.distributions
:- Add
tf.contrib.distributions.Autoregressive
. - Make
tf.contrib.distributions
QuadratureCompound classes support batch - Infer
tf.contrib.distributions.RelaxedOneHotCategorical
dtype
from arguments. - Make
tf.contrib.distributions
quadrature family parameterized byquadrature_grid_and_prob
vsquadrature_degree
. auto_correlation
added totf.contrib.distributions
- Add
tf.contrib.bayesflow.layers
, a collection of probabilistic (neural) layers. - Add
tf.contrib.bayesflow.halton_sequence
. - Add
tf.contrib.data.make_saveable_from_iterator.
- Add
tf.contrib.data.shuffle_and_repeat
. - Add new custom transformation:
tf.contrib.data.scan()
. tf.contrib.distributions.bijectors
:- Add
tf.contrib.distributions.bijectors.MaskedAutoregressiveFlow
. - Add
tf.contrib.distributions.bijectors.Permute
. - Add
tf.contrib.distributions.bijectors.Gumbel
. - Add
tf.contrib.distributions.bijectors.Reshape
. - Support shape inference (i.e., shapes containing -1) in the Reshape bijector.
- Add
streaming_precision_recall_at_equal_thresholds,
a method for computing streaming precision and recall withO(num_thresholds + size of predictions)
time and space complexity. - Change
RunConfig
default behavior to not set a random seed, making random behavior independently random on distributed workers. We expect this to generally improve training performance. Models that do rely on determinism should set a random seed explicitly. - Replaced the implementation of
tf.flags
withabsl.flags
. - Add support for
CUBLAS_TENSOR_OP_MATH
in fp16 GEMM - Add support for CUDA on NVIDIA Tegra devices
Bug Fixes and Other Changes
- Documentation updates:
- Clarified that you can only install TensorFlow on 64-bit machines.
- Added a short doc explaining how
Estimator
s save checkpoints. - Add documentation for ops supported by the
tf2xla
bridge. - Fix minor typos in the doc of
SpaceToDepth
andDepthToSpace
. - Updated documentation comments in
mfcc_mel_filterbank.h
andmfcc.h
to clarify that the input domain is squared magnitude spectra and the weighting is done on linear magnitude spectra (sqrt of inputs). - Change
tf.contrib.distributions
docstring examples to usetfd
alias rather thands
,bs
. - Fix docstring typos in
tf.distributions.bijectors.Bijector
. tf.assert_equal
no longer raisesValueError.
It now raisesInvalidArgumentError,
as documented.- Update Getting Started docs and API intro.
- Google Cloud Storage (GCS):
- Add userspace DNS caching for the GCS client.
- Customize request timeouts for the GCS filesystem.
- Improve GCS filesystem caching.
- Bug Fixes:
- Fix bug where partitioned integer variables got their wrong shapes. Before
- Fix correctness bug in CPU and GPU implementations of Adadelta.
- Fix a bug in
import_meta_graph
's handling of partitioned variables when importing into a scope. WARNING: This may break loading checkpoints of graphs with partitioned variables saved after usingimport_meta_graph
with a non-emptyimport_scope
argument. - Fix bug in offline debugger which prevented viewing events.
- Added the
WorkerService.DeleteWorkerSession
method to the gRPC interface, to fix a memory leak. Ensure that your master and worker servers are running the same version of TensorFlow to avoid compatibility issues. - Fix bug in peephole implementation of BlockLSTM cell.
- Fix bug by casting dtype of
log_det_jacobian
to matchlog_prob
inTransformedDistribution
. - Fix a bug in
import_meta_graph
's handling of partitioned variables when - Ensure
tf.distributions.Multinomial
doesn't underflow inlog_prob
. Before this change, all partitions of an integer variable were initialized with the shape of the unpartitioned variable; after this change they are initialized correctly.
- Other:
- Add necessary shape util support for bfloat16.
- Add a way to run ops using a step function to MonitoredSession.
- Add
DenseFlipout
probabilistic layer. - A new flag
ignore_live_threads
is available on train. If set toTrue
, it will ignore threads that remain running when tearing down infrastructure after successfully completing training, instead of throwing a RuntimeError. - Restandardize
DenseVariational
as simpler template for other probabilistic layers. tf.data
now supportstf.SparseTensor
components in dataset elements.- It is now possible to iterate over
Tensor
s. - Allow
SparseSegmentReduction
ops to have missing segment IDs. - Modify custom export strategy to account for multidimensional sparse float splits.
Conv2D
,Conv2DBackpropInput
,Conv2DBackpropFilter
now supports arbitrary dilations with GPU and cuDNNv6 support.Estimator
now supportsDataset
:input_fn
can return aDataset
instead ofTensor
s.- Add
RevBlock
, a memory-efficient implementation of reversible residual layers. - Reduce BFCAllocator internal fragmentation.
- Add
cross_entropy
andkl_divergence
totf.distributions.Distribution
. - Add
tf.nn.softmax_cross_entropy_with_logits_v2
which enables backprop w.r.t. the labels. - GPU back-end now uses
ptxas
to compile generated PTX. BufferAssignment
's protocol buffer dump is now deterministic.- Change embedding op to use parallel version of
DynamicStitch
. - Add support for sparse multidimensional feature columns.
- Speed up the case for sparse float columns that have only 1 value.
- Allow sparse float splits to support multivalent feature columns.
- Add
quantile
totf.distributions.TransformedDistribution
. - Add
NCHW_VECT_C
support fortf.depth_to_space
on GPU. - Add
NCHW_VECT_C
support fortf.space_to_depth
on GPU.
API Changes
- Rename
SqueezeDims
attribute toAxis
in C++ API for Squeeze op. Stream::BlockHostUntilDone
now returns Status rather than bool.- Minor refactor: move stats files from
stochastic
tocommon
and removestochastic
.
Thanks to our Contributors
This release contains contributions from many people at Google, as well as:
Adam Zahran, Ag Ramesh, Alan Lee, Alan Yee, Alex Sergeev, Alexander, Amir H. Jadidinejad, Amy, Anastasios Doumoulakis, Andrei Costinescu, Andrei Nigmatulin, Anthony Platanios, Anush Elangovan, arixlin, Armen Donigian, ArtëM Sobolev, Atlas7, Ben Barsdell, Bill Prin, Bo Wang, Brett Koonce, Cameron Thomas, Carl Thomé, Cem Eteke, cglewis, Changming Sun, Charles Shenton, Chi-Hung, Chris Donahue, Chris Filo Gorgolewski, Chris Hoyean Song, Chris Tava, Christian Grail, Christoph Boeddeker, cinqS, Clayne Robison, codrut3, concerttttt, CQY, Dan Becker, Dan Jarvis, Daniel Zhang, David Norman, dmaclach, Dmitry Trifonov, Donggeon Lim, dongpilYu, Dr. Kashif Rasul, Edd Wilder-James, Eric Lv, fcharras, Felix Abecassis, FirefoxMetzger, formath, FredZhang, Gaojin Cao, Gary Deer, Guenther Schmuelling, Hanchen Li, Hanmin Qin, hannesa2, hyunyoung2, Ilya Edrenkin, Jackson Kontny, Jan, Javier Luraschi, Jay Young, Jayaram Bobba, Jeff, Jeff Carpenter, Jeremy Sharpe, Jeroen BéDorf, Jimmy Jia, Jinze Bai, Jiongyan Zhang, Joe Castagneri, Johan Ju, Josh Varty, Julian Niedermeier, JxKing, Karl Lessard, Kb Sriram, Keven Wang, Koan-Sin Tan, Kyle Mills, lanhin, LevineHuang, Loki Der Quaeler, Loo Rong Jie, Luke Iwanski, LáSzló Csomor, Mahdi Abavisani, Mahmoud Abuzaina, ManHyuk, Marek ŠUppa, MathSquared, Mats Linander, Matt Wytock, Matthew Daley, Maximilian Bachl, mdymczyk, melvyniandrag, Michael Case, Mike Traynor, miqlas, Namrata-Ibm, Nathan Luehr, Nathan Van Doorn, Noa Ezra, Nolan Liu, Oleg Zabluda, opensourcemattress, Ouwen Huang, Paul Van Eck, peisong, Peng Yu, PinkySan, pks, powderluv, Qiao Hai-Jun, Qiao Longfei, Rajendra Arora, Ralph Tang, resec, Robin Richtsfeld, Rohan Varma, Ryohei Kuroki, SaintNazaire, Samuel He, Sandeep Dcunha, sandipmgiri, Sang Han, scott, Scott Mudge, Se-Won Kim, Simon Perkins, Simone Cirillo, Steffen Schmitz, Suvojit Manna, Sylvus, Taehoon Lee, Ted Chang, Thomas Deegan, Till Hoffmann, Tim, Toni Kunic, Toon Verstraelen, Tristan Rice, Urs KöSter, Utkarsh Upadhyay, Vish (Ishaya) Abrams, Winnie Tsang, Yan Chen, Yan Facai (颜发才), Yi Yang, Yong Tang, Youssef Hesham, Yuan (Terry) Tang, Zhengsheng Wei, zxcqwe4906, 张志豪, 田传武
We are also grateful to all who filed issues or helped resolve them, asked and answered questions, and were part of inspiring discussions.