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authorGravatar Gunhan Gulsoy <gunan@google.com>2018-02-15 22:50:04 -0800
committerGravatar Gunhan Gulsoy <gunan@google.com>2018-02-15 22:50:04 -0800
commitb2f064351185eeaf2e8f20181345c195666cf7cd (patch)
tree8cabc281acf5f2acb4f7c3a832f8dfc1addf6885 /RELEASE.md
parent56422034fe039d7e8a57392957ed0c8b4b4efe56 (diff)
parent62b3b9a0d40aacb2c890ed56b831dd2568304f89 (diff)
Merge remote-tracking branch 'gtf/r1.6'
Diffstat (limited to 'RELEASE.md')
-rw-r--r--RELEASE.md27
1 files changed, 3 insertions, 24 deletions
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, ç”°ä¼
* 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.