Merge v1.4-rc1 back into master branch. (#13960)

* Update RELEASE NOTES for TensorFlow 1.4 * Update the version strings for TF 1.4-rc0. * Update version strings in POM files missed by update script. * Pin TensorBoard 0.4 to TensorFlow 1.4 * Fixing the name of the disabled test. (#13592) * Revert "Implementing ghost batch norm as defined in https://arxiv.org/pdf/1705.08741." This reverts commit 125f7afa4a. * Disable iterator_ops_test on Windows for 1.4 release (#13609) * Disable failing Windows tests for r1.4 release. testRemoteIteratorUsingRemoteCallOpDirectSessionGPUCPU test is failing with "TypeError: only integer scalar arrays can be converted to a scalar index" on the Windows GPU Release bot. Disabling test. * Fix typo. * Also disalbe iterator_ops_test from contrib/. * Add contributing authors to 1.4 Release notes. Thanks! * Fixes to authors. Removed duplicate and removed googler from contributing author list. * Fixes and additions to release notes. Added line about Keras moving into core. Added line about CUDA/cuDNN versions. Added line about custom ops. * Fixing a master regression (#13562) * Update version strings for 1.4.0rc1 * Remaining cherry-picks for 1.4.0rc1 (#13700) * Java: Tweak to address some Javadoc errors. PiperOrigin-RevId: 171987329 * Fix S3 BUILD not including files explicitly. This causes remote builds to fail since they AWS headers were missing. PiperOrigin-RevId: 171718021 * Add missing default config setting in aws.BUILD (#13662) * Remove setting AWS logging for S3 file system. Was causing issues with tests. Can repro test failures on Macs by running... bazel test --config=s3 --cache_test_results=no --test_output=streamed //tensorflow/core/kernels:control_flow_ops_test Possible reason for error is symbol collision with AWS logging code. One possible solution would be to split out another shared object for the S3 filesystem op which does not link in libtensorflow_framework.so. This is done, for example, by libforestprotos.so in tensorflow/contrib/tensor_forest/BUILD PiperOrigin-RevId: 171246381 * Relanding change to add config to enable S3 file system support. Pass --config=s3 argument to Bazel to build with S3 file system support. Change was originally rolled back due to a failure it caused in //tensorflow/core/kernels:control_flow_ops_test on Macs which is now fixed. PiperOrigin-RevId: 171579378 * Update release notes about Amazon S3 file system support being default. * Add documentation to sloppy_interleave function PiperOrigin-RevId: 171303413 * Add `cudnn_rnn_ops` to the Windows build Fixes #13696. * Creating a patch for the wrong links that still point to dev. (#13753) * tfdbg release notes in r1.4 * Fix ambiguous type comparison in s3_crypto.cc (#13758) tensorflow/contrib/s3/s3_crypto.cc(74): error C2666: 'std::fpos<_Mbstatet>::operator ==': 3 overloads have similar conversions could be 'bool std::fpos<_Mbstatet>::operator ==(std::streamoff) const' or 'bool std::fpos<_Mbstatet>::operator ==(const std::fpos<_Mbstatet> &) We were seeing this compilation error on Windows builds. * Set estimator run_config default random seed to None. This will make it aligned with other parts of the TF. Many users are not aware of impact of non-random seed. For example it may lead to train only on a small fraction of training data due to preemptions. We're changing default behavior since we consider it as a bug fix. PiperOrigin-RevId: 172519268 * Move global_step_read dependency to model_fn instead of input_fn. PiperOrigin-RevId: 172366972 * [tf.data] Fix broken implementation of `Dataset.from_generator()` on Windows. Due to a mix-up between NumPy's default array element type for a Python `int` on Windows and Linux, a tf.py_func() in `Dataset.from_generator()` would appear to return the wrong type on Windows (np.int32 instead of np.int64). All code using `Dataset.from_generator()` on Windows was previously broken. This change fixes both `tf.data.Dataset.from_generator()` and `tf.contrib.data.Dataset.from_generator()`. It also enables test coverage for this method on Windows, which should prevent future breakage. PiperOrigin-RevId: 172346533 * Update RELEASE notes for change to run_config random seed. * Disable probable timeout flake on Ubuntu machines. PiperOrigin-RevId: 172408922 * Disabling failing contrib tests. * Disable S3 on Windows due to build issues. * Update serving_input_fn argument name to serving_input_receiver_fn PiperOrigin-RevId: 172787460 * Update the C++ API guide (#13858) - Adds the standard warning at the top that people may want the master branch - Includes a documentation fix for 1.4 (cc_binary -> tf_cc_binary to avoid undefined symbols). * Add known Dataset issue to RELEASE.md. (#13870) Adding info about issue using Unicode strings with Datasets. * Fixes to merge. * Fix spelling of tensorflow in install_sources.md
2026-01-15 12:15:41 +00:00 · 2017-10-31 11:05:14 -07:00
parent 9a2b0983a9
commit e6faa845c5
12 changed files with 72 additions and 42 deletions
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -19,6 +19,14 @@
  (with GPU and gradient support).
 * Add a self-check on `import tensorflow` for Windows DLL issues.
 * Add NCHW support to `tf.depth_to_space` on GPU.
+* TensorFlow Debugger (tfdbg):
+  * Add `eval` command to allow evaluation of arbitrary Python/numpy expressions
+    in tfdbg command-line interface. See
+    [Debugging TensorFlow Programs](https://www.tensorflow.org/programmers_guide/debugger)
+    for more details.
+  * Usability improvement: The frequently used tensor filter `has_inf_or_nan` is
+    now added to `Session` wrappers and hooks by default. So there is no need
+    for clients to call `.add_tensor_filter(tf_debug.has_inf_or_nan)` anymore.
 * SinhArcsinh (scalar) distribution added to `contrib.distributions`.
 * Make `GANEstimator` opensource.
 * `Estimator.export_savedmodel()` now includes all valid serving signatures
@@ -60,10 +68,14 @@
 * Fix `tf.contrib.distributions.Affine` incorrectly computing log-det-jacobian.
 * Fix `tf.random_gamma` incorrectly handling non-batch, scalar draws.
 * Resolved a race condition in TensorForest TreePredictionsV4Op.
-* Google Cloud Storage file system and Hadoop file system support are now
-  default build options.
+* Google Cloud Storage file system, Amazon S3 file system, and Hadoop file
+  system support are now default build options.
 * Custom op libraries must link against libtensorflow_framework.so
  (installed at `tf.sysconfig.get_lib()`).
+* 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.

 ## Breaking Changes to the API
 * The signature of the `tf.contrib.data.rejection_resample()` function has been
@@ -74,6 +86,11 @@
 * Remove seldom used and unnecessary `tf.contrib.data.Iterator.dispose_op()`.
 * Reorder some TFGAN loss functions in a non-backwards compatible way.

+## Known Issues
+* In Python 3, `Dataset.from_generator()` does not support Unicode strings.
+  You must convert any strings to bytes objects before yielding them from
+  the generator.
+
 ## Thanks to our Contributors

 This release contains contributions from many people at Google, as well as:
--- a/configure.py
+++ b/configure.py
@@ -994,6 +994,7 @@ def main():
    environ_cp['TF_NEED_HDFS'] = '0'
    environ_cp['TF_NEED_JEMALLOC'] = '0'
    environ_cp['TF_NEED_OPENCL'] = '0'
+    environ_cp['TF_NEED_S3'] = '0'
    environ_cp['TF_CUDA_CLANG'] = '0'

  if is_macos():
--- a/tensorflow/core/public/version.h
+++ b/tensorflow/core/public/version.h
@@ -24,7 +24,7 @@ limitations under the License.

 // TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
 // "-beta", "-rc", "-rc.1")
-#define TF_VERSION_SUFFIX "-rc0"
+#define TF_VERSION_SUFFIX "-rc1"

 #define TF_STR_HELPER(x) #x
 #define TF_STR(x) TF_STR_HELPER(x)
--- a/tensorflow/docs_src/api_guides/cc/guide.md
+++ b/tensorflow/docs_src/api_guides/cc/guide.md
@@ -1,4 +1,12 @@
 # C++ API
+
+Note: By default [tensorflow.org](http://tensorflow.org) shows docs for the
+most recent stable version. The instructions in this doc require building from
+source. You will probably want to build from the `master` version of tensorflow.
+You should, as a result, be sure you are following the
+[`master` version of this doc](https://www.tensorflow.org/versions/master/api_guides/cc/guide),
+in case there have been any changes.
+
 [TOC]

 TensorFlow's C++ API provides mechanisms for constructing and executing a data
@@ -48,7 +56,9 @@ TensorFlow
 `BUILD` file in the same directory with the following contents:

 ```python
-cc_binary(
+load("//tensorflow:tensorflow.bzl", "tf_cc_binary")
+
+tf_cc_binary(
    name = "example",
    srcs = ["example.cc"],
    deps = [
@@ -59,8 +69,10 @@ cc_binary(
 )
 ```

-You should be able to build and run the example using the following command
-(be sure to run `./configure` in your build sandbox first):
+Use `tf_cc_binary` rather than Bazel's native `cc_binary` to link in necessary
+symbols from `libtensorflow_framework.so`. You should be able to build and run
+the example using the following command (be sure to run `./configure` in your
+build sandbox first):

 ```shell
 bazel run -c opt //tensorflow/cc/example:example
--- a/tensorflow/docs_src/install/install_c.md
+++ b/tensorflow/docs_src/install/install_c.md
@@ -38,7 +38,7 @@ enable TensorFlow for C:
         OS="linux" # Change to "darwin" for macOS
         TARGET_DIRECTORY="/usr/local"
         curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.4.0-rc0.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.4.0-rc1.tar.gz" |
           sudo tar -C $TARGET_DIRECTORY -xz

     The `tar` command extracts the TensorFlow C library into the `lib`
--- a/tensorflow/docs_src/install/install_go.md
+++ b/tensorflow/docs_src/install/install_go.md
@@ -38,7 +38,7 @@ steps to install this library and enable TensorFlow for Go:
         TF_TYPE="cpu" # Change to "gpu" for GPU support
         TARGET_DIRECTORY='/usr/local'
         curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.4.0-rc0.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.4.0-rc1.tar.gz" |
         sudo tar -C $TARGET_DIRECTORY -xz

     The `tar` command extracts the TensorFlow C library into the `lib`
--- a/tensorflow/docs_src/install/install_java.md
+++ b/tensorflow/docs_src/install/install_java.md
@@ -36,7 +36,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
 <dependency>
  <groupId>org.tensorflow</groupId>
  <artifactId>tensorflow</artifactId>
-  <version>1.4.0-rc0</version>
+  <version>1.4.0-rc1</version>
 </dependency>
 ```

@@ -65,7 +65,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
               <dependency>
                 <groupId>org.tensorflow</groupId>
                 <artifactId>tensorflow</artifactId>
-                 <version>1.4.0-rc0</version>
+                 <version>1.4.0-rc1</version>
               </dependency>
             </dependencies>
         </project>
@@ -124,7 +124,7 @@ refer to the simpler instructions above instead.
 Take the following steps to install TensorFlow for Java on Linux or macOS:

  1. Download
-     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.4.0-rc0.jar),
+     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.4.0-rc1.jar),
     which is the TensorFlow Java Archive (JAR).

  2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
@@ -143,7 +143,7 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
         OS=$(uname -s | tr '[:upper:]' '[:lower:]')
         mkdir -p ./jni
         curl -L \
-           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.4.0-rc0.tar.gz" |
+           "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.4.0-rc1.tar.gz" |
           tar -xz -C ./jni

 ### Install on Windows
@@ -151,10 +151,10 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
 Take the following steps to install TensorFlow for Java on Windows:

  1. Download
-     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.4.0-rc0.jar),
+     [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.4.0-rc1.jar),
     which is the TensorFlow Java Archive (JAR).
  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_64-1.4.0-rc0.zip).
+     [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.4.0-rc1.zip).
  3. Extract this .zip file.


@@ -202,7 +202,7 @@ must be part of your `classpath`. For example, you can include the
 downloaded `.jar` in your `classpath` by using the `-cp` compilation flag
 as follows:

-<pre><b>javac -cp libtensorflow-1.4.0-rc0.jar HelloTF.java</b></pre>
+<pre><b>javac -cp libtensorflow-1.4.0-rc1.jar HelloTF.java</b></pre>


 ### Running
@@ -216,11 +216,11 @@ two files are available to the JVM:
 For example, the following command line executes the `HelloTF` program on Linux
 and macOS X:

-<pre><b>java -cp libtensorflow-1.4.0-rc0.jar:. -Djava.library.path=./jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.4.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>

 And the following command line executes the `HelloTF` program on Windows:

-<pre><b>java -cp libtensorflow-1.4.0-rc0.jar;. -Djava.library.path=jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.4.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>

 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
--- a/tensorflow/docs_src/install/install_linux.md
+++ b/tensorflow/docs_src/install/install_linux.md
@@ -188,7 +188,7 @@ Take the following steps to install TensorFlow with Virtualenv:
     Virtualenv environment:

     <pre>(tensorflow)$ <b>pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>

 If you encounter installation problems, see
 [Common Installation Problems](#common_installation_problems).
@@ -293,7 +293,7 @@ take the following steps:

     <pre>
     $ <b>sudo pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp34-cp34m-linux_x86_64.whl</b>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp34-cp34m-linux_x86_64.whl</b>
     </pre>

     If this step fails, see
@@ -480,7 +480,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:

     <pre>
     (tensorflow)$ <b>pip install --ignore-installed --upgrade \
-     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp34-cp34m-linux_x86_64.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>


 <a name="ValidateYourInstallation"></a>
@@ -648,14 +648,14 @@ This section documents the relevant values for Linux installations.
 CPU only:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp27-none-linux_x86_64.whl
 </pre>


 GPU support:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc0-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc1-cp27-none-linux_x86_64.whl
 </pre>

 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:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp34-cp34m-linux_x86_64.whl
 </pre>


 GPU support:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc0-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc1-cp34-cp34m-linux_x86_64.whl
 </pre>

 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:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp35-cp35m-linux_x86_64.whl
 </pre>


 GPU support:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc0-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc1-cp35-cp35m-linux_x86_64.whl
 </pre>


@@ -705,14 +705,14 @@ Note that GPU support requires the NVIDIA hardware and software described in
 CPU only:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc0-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.4.0rc1-cp36-cp36m-linux_x86_64.whl
 </pre>


 GPU support:

 <pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc0-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.4.0rc1-cp36-cp36m-linux_x86_64.whl
 </pre>


--- a/tensorflow/docs_src/install/install_mac.md
+++ b/tensorflow/docs_src/install/install_mac.md
@@ -114,7 +114,7 @@ Take the following steps to install TensorFlow with Virtualenv:
     TensorFlow in the active Virtualenv is as follows:

     <pre> $ <b>pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py2-none-any.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc1-py2-none-any.whl</b></pre>

 If you encounter installation problems, see
 [Common Installation Problems](#common-installation-problems).
@@ -235,7 +235,7 @@ take the following steps:
     issue the following command:

     <pre> $ <b>sudo pip3 install --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py2-none-any.whl</b> </pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc1-py2-none-any.whl</b> </pre>

     If the preceding command fails, see
     [installation problems](#common-installation-problems).
@@ -344,7 +344,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
     TensorFlow for Python 2.7:

     <pre> (tensorflow)$ <b>pip install --ignore-installed --upgrade \
-     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py2-none-any.whl</b></pre>
+     https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc1-py2-none-any.whl</b></pre>


 <a name="ValidateYourInstallation"></a>
@@ -517,7 +517,7 @@ This section documents the relevant values for Mac OS installations.


 <pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py2-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc1-py2-none-any.whl
 </pre>


@@ -525,7 +525,7 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py2-none-a


 <pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc0-py3-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.4.0rc1-py3-none-any.whl
 </pre>


--- a/tensorflow/docs_src/install/install_sources.md
+++ b/tensorflow/docs_src/install/install_sources.md
@@ -355,10 +355,10 @@ Invoke `pip install` to install that pip package.
 The filename of the `.whl` file depends on your platform.
 For example, the following command will install the pip package

-for TensorFlow 1.4.0rc0 on Linux:
+for TensorFlow 1.4.0rc1 on Linux:

 <pre>
-$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.4.0rc0-py2-none-any.whl</b>
+$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.4.0rc1-py2-none-any.whl</b>
 </pre>

 ## Validate your installation
@@ -447,8 +447,8 @@ Stack Overflow and specify the `tensorflow` tag.
 **Linux**
 <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><td>tensorflow-1.4.0rc0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>N/A</td><td>N/A</td></tr>
-<tr><td>tensorflow_gpu-1.4.0rc0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>6</td><td>8</td></tr>
+<tr><td>tensorflow-1.4.0rc1</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>N/A</td><td>N/A</td></tr>
+<tr><td>tensorflow_gpu-1.4.0rc1</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>6</td><td>8</td></tr>
 <tr><td>tensorflow-1.2.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>N/A</td><td>N/A</td></tr>
 <tr><td>tensorflow_gpu-1.2.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.5</td><td>5.1</td><td>8</td></tr>
 <tr><td>tensorflow-1.1.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>GCC 4.8</td><td>Bazel 0.4.2</td><td>N/A</td><td>N/A</td></tr>
@@ -460,7 +460,7 @@ Stack Overflow and specify the `tensorflow` tag.
 **Mac**
 <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><td>tensorflow-1.4.0rc0</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-1.4.0rc1</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-1.2.0</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-1.1.0</td><td>CPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.4.2</td><td>N/A</td><td>N/A</td></tr>
 <tr><td>tensorflow_gpu-1.1.0</td><td>GPU</td><td>2.7, 3.3-3.6</td><td>Clang from xcode</td><td>Bazel 0.4.2</td><td>5.1</td><td>8</td></tr>
@@ -471,8 +471,8 @@ Stack Overflow and specify the `tensorflow` tag.
 **Windows**
 <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><td>tensorflow-1.4.0rc0</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_gpu-1.4.0rc0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>6</td><td>8</td></tr>
+<tr><td>tensorflow-1.4.0rc1</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-1.4.0rc1</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>6</td><td>8</td></tr>
 <tr><td>tensorflow-1.2.0</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-1.2.0</td><td>GPU</td><td>3.5-3.6</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>5.1</td><td>8</td></tr>
 <tr><td>tensorflow-1.1.0</td><td>CPU</td><td>3.5</td><td>MSVC 2015 update 3</td><td>Cmake v3.6.3</td><td>N/A</td><td>N/A</td></tr>
--- a/tensorflow/tools/ci_build/update_version.py
+++ b/tensorflow/tools/ci_build/update_version.py
@@ -17,7 +17,7 @@
 # Automatically update TensorFlow version in source files
 #
 # Usage:
-#           ./tensorflow/tools/ci_build/update_version.py --version 1.4.0-rc0
+#           ./tensorflow/tools/ci_build/update_version.py --version 1.4.0-rc1
 #           ./tensorflow/tools/ci_build/update_version.py --nightly
 #
 """Update version of TensorFlow script."""
--- a/tensorflow/tools/pip_package/setup.py
+++ b/tensorflow/tools/pip_package/setup.py
@@ -29,7 +29,7 @@ from setuptools.dist import Distribution
 # This version string is semver compatible, but incompatible with pip.
 # For pip, we will remove all '-' characters from this string, and use the
 # result for pip.
-_VERSION = '1.4.0-rc0'
+_VERSION = '1.4.0-rc1'

 REQUIRED_PACKAGES = [
    'enum34 >= 1.1.6',