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Merge remote-tracking branch 'gtf/r1.6'

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Gunhan Gulsoy 2018-02-15 22:50:04 -08:00
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27
RELEASE.md
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@ -21,7 +21,7 @@ newcomers.
* Other: * Other:
* Add `tf.contrib.distributions.Kumaraswamy`. * Add `tf.contrib.distributions.Kumaraswamy`.
* `RetryingFileSystem::FlushCaches()` calls the base FileSystem's `FlushCaches()`. * `RetryingFileSystem::FlushCaches()` calls the base FileSystem's `FlushCaches()`.
* Add auto_correlation to distributions. * Add `auto_correlation` to distributions.
* Add `tf.contrib.distributions.Autoregressive`. * Add `tf.contrib.distributions.Autoregressive`.
* Add SeparableConv1D layer. * Add SeparableConv1D layer.
* Add convolutional Flipout layers. * Add convolutional Flipout layers.
@ -31,12 +31,12 @@ newcomers.
* Output variance over trees predictions for classifications tasks. * Output variance over trees predictions for classifications tasks.
* For `pt` and `eval` commands, allow writing tensor values to filesystem as numpy files. * For `pt` and `eval` commands, allow writing tensor values to filesystem as numpy files.
* gRPC: Propagate truncated errors (instead of returning gRPC internal error). * 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. * Improved XLA support for C64-related ops log, pow, atan2, tanh.
* Add probabilistic convolutional layers. * Add probabilistic convolutional layers.
## API Changes ## 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`. * Move `layers_dense_variational_impl.py` to `layers_dense_variational.py`.
## Known Bugs ## 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. * Starting from 1.6 release, our prebuilt binaries will use AVX instructions.
This may break TF on older CPUs. 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 ## Major Features And Improvements
* [Eager execution](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/eager) * [Eager execution](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/eager)
preview version is now available. preview version is now available.

2
tensorflow/contrib/slim/python/slim/evaluation_test.py
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@ -235,7 +235,7 @@ class SingleEvaluationTest(test.TestCase):
def _prepareCheckpoint(self, checkpoint_path): def _prepareCheckpoint(self, checkpoint_path):
init_op = control_flow_ops.group(variables.global_variables_initializer(), init_op = control_flow_ops.group(variables.global_variables_initializer(),
variables.local_variables_initializer()) variables.local_variables_initializer())
saver = saver_lib.Saver() saver = saver_lib.Saver(write_version=saver_pb2.SaverDef.V1)
with self.test_session() as sess: with self.test_session() as sess:
sess.run(init_op) sess.run(init_op)
saver.save(sess, checkpoint_path) saver.save(sess, checkpoint_path)

2
tensorflow/contrib/tpu/profiler/pip_package/setup.py
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@ -20,7 +20,7 @@ from __future__ import print_function
from setuptools import setup from setuptools import setup
_VERSION = '1.6.0-rc0' _VERSION = '1.6.0-rc1'
CONSOLE_SCRIPTS = [ CONSOLE_SCRIPTS = [
'capture_tpu_profile=cloud_tpu_profiler.main:run_main', 'capture_tpu_profile=cloud_tpu_profiler.main:run_main',

2
tensorflow/core/public/version.h
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@ -24,7 +24,7 @@ limitations under the License.
// TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1", // TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
// "-beta", "-rc", "-rc.1") // "-beta", "-rc", "-rc.1")
#define TF_VERSION_SUFFIX "-rc0" #define TF_VERSION_SUFFIX "-rc1"
#define TF_STR_HELPER(x) #x #define TF_STR_HELPER(x) #x
#define TF_STR(x) TF_STR_HELPER(x) #define TF_STR(x) TF_STR_HELPER(x)

2
tensorflow/docs_src/install/install_c.md
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@ -38,7 +38,7 @@ enable TensorFlow for C:
OS="linux" # Change to "darwin" for macOS OS="linux" # Change to "darwin" for macOS
TARGET_DIRECTORY="/usr/local" TARGET_DIRECTORY="/usr/local"
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.6.0-rc0.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.6.0-rc1.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib` The `tar` command extracts the TensorFlow C library into the `lib`

2
tensorflow/docs_src/install/install_go.md
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@ -38,7 +38,7 @@ steps to install this library and enable TensorFlow for Go:
TF_TYPE="cpu" # Change to "gpu" for GPU support TF_TYPE="cpu" # Change to "gpu" for GPU support
TARGET_DIRECTORY='/usr/local' TARGET_DIRECTORY='/usr/local'
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.6.0-rc0.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.6.0-rc1.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib` The `tar` command extracts the TensorFlow C library into the `lib`

22
tensorflow/docs_src/install/install_java.md
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@ -36,7 +36,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId> <artifactId>tensorflow</artifactId>
<version>1.6.0-rc0</version> <version>1.6.0-rc1</version>
</dependency> </dependency>
``` ```
@ -65,7 +65,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId> <artifactId>tensorflow</artifactId>
<version>1.6.0-rc0</version> <version>1.6.0-rc1</version>
</dependency> </dependency>
</dependencies> </dependencies>
</project> </project>
@ -123,12 +123,12 @@ instead:
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>libtensorflow</artifactId> <artifactId>libtensorflow</artifactId>
<version>1.6.0-rc0</version> <version>1.6.0-rc1</version>
</dependency> </dependency>
<dependency> <dependency>
<groupId>org.tensorflow</groupId> <groupId>org.tensorflow</groupId>
<artifactId>libtensorflow_jni_gpu</artifactId> <artifactId>libtensorflow_jni_gpu</artifactId>
<version>1.6.0-rc0</version> <version>1.6.0-rc1</version>
</dependency> </dependency>
``` ```
@ -147,7 +147,7 @@ refer to the simpler instructions above instead.
Take the following steps to install TensorFlow for Java on Linux or macOS: Take the following steps to install TensorFlow for Java on Linux or macOS:
1. Download 1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.6.0-rc0.jar), [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.6.0-rc1.jar),
which is the TensorFlow Java Archive (JAR). which is the TensorFlow Java Archive (JAR).
2. Decide whether you will run TensorFlow for Java on CPU(s) only or with 2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
@ -166,7 +166,7 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
OS=$(uname -s | tr '[:upper:]' '[:lower:]') OS=$(uname -s | tr '[:upper:]' '[:lower:]')
mkdir -p ./jni mkdir -p ./jni
curl -L \ curl -L \
"https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.6.0-rc0.tar.gz" | "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.6.0-rc1.tar.gz" |
tar -xz -C ./jni tar -xz -C ./jni
### Install on Windows ### Install on Windows
@ -174,10 +174,10 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
Take the following steps to install TensorFlow for Java on Windows: Take the following steps to install TensorFlow for Java on Windows:
1. Download 1. Download
[libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.6.0-rc0.jar), [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.6.0-rc1.jar),
which is the TensorFlow Java Archive (JAR). which is the TensorFlow Java Archive (JAR).
2. Download the following Java Native Interface (JNI) file appropriate for 2. Download the following Java Native Interface (JNI) file appropriate for
[TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.6.0-rc0.zip). [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.6.0-rc1.zip).
3. Extract this .zip file. 3. Extract this .zip file.
@ -225,7 +225,7 @@ must be part of your `classpath`. For example, you can include the
downloaded `.jar` in your `classpath` by using the `-cp` compilation flag downloaded `.jar` in your `classpath` by using the `-cp` compilation flag
as follows: as follows:
<pre><b>javac -cp libtensorflow-1.6.0-rc0.jar HelloTF.java</b></pre> <pre><b>javac -cp libtensorflow-1.6.0-rc1.jar HelloTF.java</b></pre>
### Running ### Running
@ -239,11 +239,11 @@ two files are available to the JVM:
For example, the following command line executes the `HelloTF` program on Linux For example, the following command line executes the `HelloTF` program on Linux
and macOS X: and macOS X:
<pre><b>java -cp libtensorflow-1.6.0-rc0.jar:. -Djava.library.path=./jni HelloTF</b></pre> <pre><b>java -cp libtensorflow-1.6.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>
And the following command line executes the `HelloTF` program on Windows: And the following command line executes the `HelloTF` program on Windows:
<pre><b>java -cp libtensorflow-1.6.0-rc0.jar;. -Djava.library.path=jni HelloTF</b></pre> <pre><b>java -cp libtensorflow-1.6.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>
If the program prints <tt>Hello from <i>version</i></tt>, you've successfully If the program prints <tt>Hello from <i>version</i></tt>, you've successfully
installed TensorFlow for Java and are ready to use the API. If the program installed TensorFlow for Java and are ready to use the API. If the program

22
tensorflow/docs_src/install/install_linux.md
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@ -188,7 +188,7 @@ Take the following steps to install TensorFlow with Virtualenv:
Virtualenv environment: Virtualenv environment:
<pre>(tensorflow)$ <b>pip3 install --upgrade \ <pre>(tensorflow)$ <b>pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
If you encounter installation problems, see If you encounter installation problems, see
[Common Installation Problems](#common_installation_problems). [Common Installation Problems](#common_installation_problems).
@ -293,7 +293,7 @@ take the following steps:
<pre> <pre>
$ <b>sudo pip3 install --upgrade \ $ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp34-cp34m-linux_x86_64.whl</b> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp34-cp34m-linux_x86_64.whl</b>
</pre> </pre>
If this step fails, see If this step fails, see
@ -480,7 +480,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
<pre> <pre>
(tensorflow)$ <b>pip install --ignore-installed --upgrade \ (tensorflow)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre> https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
<a name="ValidateYourInstallation"></a> <a name="ValidateYourInstallation"></a>
@ -648,14 +648,14 @@ This section documents the relevant values for Linux installations.
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp27-none-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp27-none-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc0-cp27-none-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc1-cp27-none-linux_x86_64.whl
</pre> </pre>
Note that GPU support requires the NVIDIA hardware and software described in Note that GPU support requires the NVIDIA hardware and software described in
@ -667,14 +667,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp34-cp34m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp34-cp34m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc0-cp34-cp34m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc1-cp34-cp34m-linux_x86_64.whl
</pre> </pre>
Note that GPU support requires the NVIDIA hardware and software described in Note that GPU support requires the NVIDIA hardware and software described in
@ -686,14 +686,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp35-cp35m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp35-cp35m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc0-cp35-cp35m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc1-cp35-cp35m-linux_x86_64.whl
</pre> </pre>
@ -705,14 +705,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only: CPU only:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc0-cp36-cp36m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.6.0rc1-cp36-cp36m-linux_x86_64.whl
</pre> </pre>
GPU support: GPU support:
<pre> <pre>
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc0-cp36-cp36m-linux_x86_64.whl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0rc1-cp36-cp36m-linux_x86_64.whl
</pre> </pre>

10
tensorflow/docs_src/install/install_mac.md
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@ -115,7 +115,7 @@ Take the following steps to install TensorFlow with Virtualenv:
TensorFlow in the active Virtualenv is as follows: TensorFlow in the active Virtualenv is as follows:
<pre> $ <b>pip3 install --upgrade \ <pre> $ <b>pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py3-none-any.whl</b></pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc1-py3-none-any.whl</b></pre>
If you encounter installation problems, see If you encounter installation problems, see
[Common Installation Problems](#common-installation-problems). [Common Installation Problems](#common-installation-problems).
@ -238,7 +238,7 @@ take the following steps:
issue the following command: issue the following command:
<pre> $ <b>sudo pip3 install --upgrade \ <pre> $ <b>sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py3-none-any.whl</b> </pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc1-py3-none-any.whl</b> </pre>
If the preceding command fails, see If the preceding command fails, see
[installation problems](#common-installation-problems). [installation problems](#common-installation-problems).
@ -347,7 +347,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
TensorFlow for Python 2.7: TensorFlow for Python 2.7:
<pre> (<i>targetDirectory</i>)$ <b>pip install --ignore-installed --upgrade \ <pre> (<i>targetDirectory</i>)$ <b>pip install --ignore-installed --upgrade \
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py2-none-any.whl</b></pre> https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc1-py2-none-any.whl</b></pre>
<a name="ValidateYourInstallation"></a> <a name="ValidateYourInstallation"></a>
@ -520,7 +520,7 @@ This section documents the relevant values for Mac OS installations.
<pre> <pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py2-none-any.whl https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc1-py2-none-any.whl
</pre> </pre>
@ -528,5 +528,5 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py2-none-a
<pre> <pre>
https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc0-py3-none-any.whl https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.6.0rc1-py3-none-any.whl
</pre> </pre>

14
tensorflow/docs_src/install/install_sources.md
View File

@ -359,10 +359,10 @@ Invoke `pip install` to install that pip package.
The filename of the `.whl` file depends on your platform. The filename of the `.whl` file depends on your platform.
For example, the following command will install the pip package For example, the following command will install the pip package
for TensorFlow 1.6.0rc0 on Linux: for TensorFlow 1.6.0rc1 on Linux:
<pre> <pre>
$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.6.0rc0-py2-none-any.whl</b> $ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.6.0rc1-py2-none-any.whl</b>
</pre> </pre>
## Validate your installation ## Validate your installation
@ -460,8 +460,8 @@ Stack Overflow and specify the `tensorflow` tag.
**Linux** **Linux**
<table> <table>
<tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr>
<tr><td>tensorflow-1.6.0rc0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow_gpu-1.6.0rc0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>7</td><td>9</td></tr> <tr><td>tensorflow_gpu-1.6.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.9.0</td><td>7</td><td>9</td></tr>
<tr><td>tensorflow-1.5.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.8.0</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.5.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.8.0</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow_gpu-1.5.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.8.0</td><td>7</td><td>9</td></tr> <tr><td>tensorflow_gpu-1.5.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.8.0</td><td>7</td><td>9</td></tr>
<tr><td>tensorflow-1.4.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.5.4</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.4.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.5.4</td><td>N/A</td><td>N/A</td></tr>
@ -479,7 +479,7 @@ Stack Overflow and specify the `tensorflow` tag.
**Mac** **Mac**
<table> <table>
<tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr>
<tr><td>tensorflow-1.6.0rc0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow-1.5.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.5.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.8.1</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow-1.4.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.5.4</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.4.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.5.4</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow-1.3.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.4.5</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.3.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.4.5</td><td>N/A</td><td>N/A</td></tr>
@ -493,8 +493,8 @@ Stack Overflow and specify the `tensorflow` tag.
**Windows** **Windows**
<table> <table>
<tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr> <tr><th>Version:</th><th>CPU/GPU:</th><th>Python Version:</th><th>Compiler:</th><th>Build Tools:</th><th>cuDNN:</th><th>CUDA:</th></tr>
<tr><td>tensorflow-1.6.0rc0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.6.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow_gpu-1.6.0rc0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr> <tr><td>tensorflow_gpu-1.6.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr>
<tr><td>tensorflow-1.5.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.5.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr>
<tr><td>tensorflow_gpu-1.5.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr> <tr><td>tensorflow_gpu-1.5.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>7</td><td>9</td></tr>
<tr><td>tensorflow-1.4.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr> <tr><td>tensorflow-1.4.0</td><td>CPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr>

2
tensorflow/docs_src/install/install_windows.md
View File

@ -47,7 +47,7 @@ installed on your system:
If you have a different version of one of the preceding packages, please If you have a different version of one of the preceding packages, please
change to the specified versions. In particular, the cuDNN version change to the specified versions. In particular, the cuDNN version
must match exactly: TensorFlow will not load if it cannot find `cudnn64_7.dll`. must match exactly: TensorFlow will not load if it cannot find `cuDNN64_7.dll`.
To use a different version of cuDNN, you must build from source. To use a different version of cuDNN, you must build from source.
## Determine how to install TensorFlow ## Determine how to install TensorFlow

12
tensorflow/python/training/saver.py
View File

@ -1597,9 +1597,9 @@ class Saver(object):
[Stripping Default-Valued Attributes](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md#stripping-default-valued-attributes). [Stripping Default-Valued Attributes](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md#stripping-default-valued-attributes).
Returns: Returns:
A string: path prefix used for the checkpoint files. If checkpoint A string: path prefix used for the checkpoint files. If the saver is
format is V1 and the saver is sharded, this string ends with: sharded, this string ends with: '-?????-of-nnnnn' where 'nnnnn'
'-?????-of-nnnnn' where 'nnnnn' is the number of shards created. is the number of shards created.
If the saver is empty, returns None. If the saver is empty, returns None.
Raises: Raises:
@ -1749,12 +1749,6 @@ class Saver(object):
return return
if save_path is None: if save_path is None:
raise ValueError("Can't load save_path when it is None.") raise ValueError("Can't load save_path when it is None.")
if (os.path.isfile(save_path) and
self._write_version not in (
saver_pb2.SaverDef.V1, saver_pb2.SaverDef.LEGACY)):
raise ValueError("The specified path: %s is a file."
" Please specify only the path prefix"
" to the checkpoint files." % save_path)
logging.info("Restoring parameters from %s", save_path) logging.info("Restoring parameters from %s", save_path)
if context.in_graph_mode(): if context.in_graph_mode():
sess.run(self.saver_def.restore_op_name, sess.run(self.saver_def.restore_op_name,

1
tensorflow/python/util/compat_internal.py
View File

@ -20,6 +20,7 @@ from __future__ import print_function
from tensorflow.python.util.compat import as_str_any from tensorflow.python.util.compat import as_str_any
def path_to_str(path): def path_to_str(path):
"""Returns the file system path representation of a `PathLike` object, """Returns the file system path representation of a `PathLike` object,
else as it is. else as it is.

6
tensorflow/tools/pip_package/setup.py
View File

@ -29,17 +29,17 @@ from setuptools.dist import Distribution
# This version string is semver compatible, but incompatible with pip. # This version string is semver compatible, but incompatible with pip.
# For pip, we will remove all '-' characters from this string, and use the # For pip, we will remove all '-' characters from this string, and use the
# result for pip. # result for pip.
_VERSION = '1.6.0-rc0' _VERSION = '1.6.0-rc1'
REQUIRED_PACKAGES = [ REQUIRED_PACKAGES = [
'absl-py >= 0.1.6', 'absl-py >= 0.1.6',
'astor >= 0.6.0', 'astor >= 0.6.0',
'gast >= 0.2.0', 'gast >= 0.2.0',
'grpcio >= 1.8.6', 'grpcio >= 1.8.6',
'numpy >= 1.12.1', 'numpy >= 1.13.3',
'six >= 1.10.0', 'six >= 1.10.0',
'protobuf >= 3.4.0', 'protobuf >= 3.4.0',
'tensorflow-tensorboard >= 1.5.0, < 1.6.0', 'tensorboard >= 1.6.0, < 1.7.0',
'termcolor >= 1.1.0', 'termcolor >= 1.1.0',
] ]