From dce9a49c19f406ba45919e8c94474e55dc5ccd54 Mon Sep 17 00:00:00 2001 From: Yifei Feng Date: Thu, 22 Feb 2018 14:24:57 -0800 Subject: Merge changes from github. PiperOrigin-RevId: 186674197 --- RELEASE.md | 27 +++------------------------ 1 file changed, 3 insertions(+), 24 deletions(-) (limited to 'RELEASE.md') diff --git a/RELEASE.md b/RELEASE.md index 0720a8c639..6f54dee58f 100644 --- a/RELEASE.md +++ b/RELEASE.md @@ -21,7 +21,7 @@ newcomers. * Other: * Add `tf.contrib.distributions.Kumaraswamy`. * `RetryingFileSystem::FlushCaches()` calls the base FileSystem's `FlushCaches()`. - * Add auto_correlation to distributions. + * Add `auto_correlation` to distributions. * Add `tf.contrib.distributions.Autoregressive`. * Add SeparableConv1D layer. * Add convolutional Flipout layers. @@ -31,12 +31,12 @@ newcomers. * Output variance over trees predictions for classifications tasks. * For `pt` and `eval` commands, allow writing tensor values to filesystem as numpy files. * gRPC: Propagate truncated errors (instead of returning gRPC internal error). - * Augment parallel_interleave to support 2 kinds of prefetching. + * Augment `parallel_interleave` to support 2 kinds of prefetching. * Improved XLA support for C64-related ops log, pow, atan2, tanh. * Add probabilistic convolutional layers. ## API Changes -* Introducing prepare_variance boolean with default setting to False for backward compatibility. +* Introducing `prepare_variance` boolean with default setting to False for backward compatibility. * Move `layers_dense_variational_impl.py` to `layers_dense_variational.py`. ## Known Bugs @@ -96,27 +96,6 @@ Yoni Tsafir, yordun, Yuan (Terry) Tang, Yuxin Wu, zhengdi, Zhengsheng Wei, 田 * Starting from 1.6 release, our prebuilt binaries will use AVX instructions. This may break TF on older CPUs. -## Known Bugs -* Using XLA:GPU with CUDA 9 and CUDA 9.1 results in garbage results and/or - `CUDA_ILLEGAL_ADDRESS` failures. - - Google discovered in mid-December 2017 that the PTX-to-SASS compiler in CUDA 9 - and CUDA 9.1 sometimes does not properly compute the carry bit when - decomposing 64-bit address calculations with large offsets (e.g. `load [x + - large_constant]`) into 32-bit arithmetic in SASS. - - As a result, these versions of `ptxas` miscompile most XLA programs which use - more than 4GB of temp memory. This results in garbage results and/or - `CUDA_ERROR_ILLEGAL_ADDRESS` failures. - - A fix in CUDA 9.1.121 is expected in late February 2018. We do not expect a - fix for CUDA 9.0.x. Until the fix is available, the only workaround is to - [downgrade](https://developer.nvidia.com/cuda-toolkit-archive) to CUDA 8.0.x - or disable XLA:GPU. - - TensorFlow will print a warning if you use XLA:GPU with a known-bad version of - CUDA; see e00ba24c4038e7644da417ddc639169b6ea59122. - ## Major Features And Improvements * [Eager execution](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/eager) preview version is now available. -- cgit v1.2.3