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-rw-r--r--tensorflow/docs_src/install/install_c.md2
-rw-r--r--tensorflow/docs_src/install/install_go.md2
-rw-r--r--tensorflow/docs_src/install/install_java.md22
-rw-r--r--tensorflow/docs_src/install/install_linux.md18
-rw-r--r--tensorflow/docs_src/install/install_mac.md10
-rw-r--r--tensorflow/docs_src/install/install_raspbian.md6
-rw-r--r--tensorflow/docs_src/install/install_sources.md9
-rw-r--r--tensorflow/docs_src/performance/xla/operation_semantics.md24
8 files changed, 49 insertions, 44 deletions
diff --git a/tensorflow/docs_src/install/install_c.md b/tensorflow/docs_src/install/install_c.md
index 5e26facaba..4a63f11fca 100644
--- 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_64-1.10.0-rc1.tar.gz" |
+ "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-${OS}-x86_64-1.10.0.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib`
diff --git a/tensorflow/docs_src/install/install_go.md b/tensorflow/docs_src/install/install_go.md
index 83d16bc4b7..f0f8436777 100644
--- a/tensorflow/docs_src/install/install_go.md
+++ b/tensorflow/docs_src/install/install_go.md
@@ -38,7 +38,7 @@ steps to install this library and enable TensorFlow for Go:
TF_TYPE="cpu" # Change to "gpu" for GPU support
TARGET_DIRECTORY='/usr/local'
curl -L \
- "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.10.0-rc1.tar.gz" |
+ "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-${TF_TYPE}-$(go env GOOS)-x86_64-1.10.0.tar.gz" |
sudo tar -C $TARGET_DIRECTORY -xz
The `tar` command extracts the TensorFlow C library into the `lib`
diff --git a/tensorflow/docs_src/install/install_java.md b/tensorflow/docs_src/install/install_java.md
index e9c6650c92..c131a2ea76 100644
--- a/tensorflow/docs_src/install/install_java.md
+++ b/tensorflow/docs_src/install/install_java.md
@@ -36,7 +36,7 @@ following to the project's `pom.xml` to use the TensorFlow Java APIs:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
- <version>1.10.0-rc1</version>
+ <version>1.10.0</version>
</dependency>
```
@@ -65,7 +65,7 @@ As an example, these steps will create a Maven project that uses TensorFlow:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>tensorflow</artifactId>
- <version>1.10.0-rc1</version>
+ <version>1.10.0</version>
</dependency>
</dependencies>
</project>
@@ -124,12 +124,12 @@ instead:
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>libtensorflow</artifactId>
- <version>1.10.0-rc1</version>
+ <version>1.10.0</version>
</dependency>
<dependency>
<groupId>org.tensorflow</groupId>
<artifactId>libtensorflow_jni_gpu</artifactId>
- <version>1.10.0-rc1</version>
+ <version>1.10.0</version>
</dependency>
```
@@ -148,7 +148,7 @@ refer to the simpler instructions above instead.
Take the following steps to install TensorFlow for Java on Linux or macOS:
1. Download
- [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.10.0-rc1.jar),
+ [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.10.0.jar),
which is the TensorFlow Java Archive (JAR).
2. Decide whether you will run TensorFlow for Java on CPU(s) only or with
@@ -167,7 +167,7 @@ Take the following steps to install TensorFlow for Java on Linux or macOS:
OS=$(uname -s | tr '[:upper:]' '[:lower:]')
mkdir -p ./jni
curl -L \
- "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.10.0-rc1.tar.gz" |
+ "https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-${TF_TYPE}-${OS}-x86_64-1.10.0.tar.gz" |
tar -xz -C ./jni
### Install on Windows
@@ -175,10 +175,10 @@ 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-1.10.0-rc1.jar),
+ [libtensorflow.jar](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-1.10.0.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_64-1.10.0-rc1.zip).
+ [TensorFlow for Java on Windows](https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow_jni-cpu-windows-x86_64-1.10.0.zip).
3. Extract this .zip file.
__Note__: The native library (`tensorflow_jni.dll`) requires `msvcp140.dll` at runtime, which is included in the [Visual C++ 2015 Redistributable](https://www.microsoft.com/en-us/download/details.aspx?id=48145) package.
@@ -227,7 +227,7 @@ 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-1.10.0-rc1.jar HelloTF.java</b></pre>
+<pre><b>javac -cp libtensorflow-1.10.0.jar HelloTF.java</b></pre>
### Running
@@ -241,11 +241,11 @@ 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-1.10.0-rc1.jar:. -Djava.library.path=./jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.10.0.jar:. -Djava.library.path=./jni HelloTF</b></pre>
And the following command line executes the `HelloTF` program on Windows:
-<pre><b>java -cp libtensorflow-1.10.0-rc1.jar;. -Djava.library.path=jni HelloTF</b></pre>
+<pre><b>java -cp libtensorflow-1.10.0.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
diff --git a/tensorflow/docs_src/install/install_linux.md b/tensorflow/docs_src/install/install_linux.md
index 005ad437bc..0febdee99f 100644
--- a/tensorflow/docs_src/install/install_linux.md
+++ b/tensorflow/docs_src/install/install_linux.md
@@ -436,7 +436,7 @@ 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-1.10.0rc1-cp34-cp34m-linux_x86_64.whl</b></pre>
+ https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0-cp34-cp34m-linux_x86_64.whl</b></pre>
<a name="ValidateYourInstallation"></a>
@@ -650,13 +650,13 @@ This section documents the relevant values for Linux installations.
CPU only:
<pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0rc1-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0-cp27-none-linux_x86_64.whl
</pre>
GPU support:
<pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0rc1-cp27-none-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0-cp27-none-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
@@ -667,13 +667,13 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0rc1-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0-cp34-cp34m-linux_x86_64.whl
</pre>
GPU support:
<pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0rc1-cp34-cp34m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0-cp34-cp34m-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
@@ -684,13 +684,13 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0rc1-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0-cp35-cp35m-linux_x86_64.whl
</pre>
GPU support:
<pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0rc1-cp35-cp35m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0-cp35-cp35m-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
@@ -701,13 +701,13 @@ Note that GPU support requires the NVIDIA hardware and software described in
CPU only:
<pre>
-https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0rc1-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl
</pre>
GPU support:
<pre>
-https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0rc1-cp36-cp36m-linux_x86_64.whl
+https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.0-cp36-cp36m-linux_x86_64.whl
</pre>
Note that GPU support requires the NVIDIA hardware and software described in
diff --git a/tensorflow/docs_src/install/install_mac.md b/tensorflow/docs_src/install/install_mac.md
index 3a8637bfb1..c4d63cc107 100644
--- a/tensorflow/docs_src/install/install_mac.md
+++ b/tensorflow/docs_src/install/install_mac.md
@@ -119,7 +119,7 @@ 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-1.10.0rc1-py3-none-any.whl</b></pre>
+ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0-py3-none-any.whl</b></pre>
If you encounter installation problems, see
[Common Installation Problems](#common-installation-problems).
@@ -242,7 +242,7 @@ take the following steps:
issue the following command:
<pre> $ <b>sudo pip3 install --upgrade \
- https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0rc1-py3-none-any.whl</b> </pre>
+ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0-py3-none-any.whl</b> </pre>
If the preceding command fails, see
[installation problems](#common-installation-problems).
@@ -350,7 +350,7 @@ Take the following steps to install TensorFlow in an Anaconda environment:
TensorFlow for Python 2.7:
<pre> (<i>targetDirectory</i>)$ <b>pip install --ignore-installed --upgrade \
- https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0rc1-py2-none-any.whl</b></pre>
+ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0-py2-none-any.whl</b></pre>
<a name="ValidateYourInstallation"></a>
@@ -517,7 +517,7 @@ The value you specify depends on your Python version.
<pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0rc1-py2-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0-py2-none-any.whl
</pre>
@@ -525,5 +525,5 @@ https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0rc1-py2-none-
<pre>
-https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0rc1-py3-none-any.whl
+https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.10.0-py3-none-any.whl
</pre>
diff --git a/tensorflow/docs_src/install/install_raspbian.md b/tensorflow/docs_src/install/install_raspbian.md
index 58a5285c78..cf6b6b4f79 100644
--- a/tensorflow/docs_src/install/install_raspbian.md
+++ b/tensorflow/docs_src/install/install_raspbian.md
@@ -60,7 +60,7 @@ If it gives the error "Command not found", then the package has not been
installed yet. To install if for the first time, run:
<pre>$ sudo apt-get install python3-pip # for Python 3.n
-sudo apt-get install python-pip # for Python 2.7</pre>
+$ sudo apt-get install python-pip # for Python 2.7</pre>
You can find more help on installing and upgrading pip in
[the Raspberry Pi documentation](https://www.raspberrypi.org/documentation/linux/software/python.md).
@@ -78,8 +78,8 @@ your system, run the following command:
Assuming the prerequisite software is installed on your Pi, install TensorFlow
by invoking **one** of the following commands:
- <pre> $ <b>pip3 install tensorflow</b> # Python 3.n
- $ <b>pip install tensorflow</b> # Python 2.7</pre>
+<pre>$ <b>pip3 install tensorflow</b> # Python 3.n
+$ <b>pip install tensorflow</b> # Python 2.7</pre>
This can take some time on certain platforms like the Pi Zero, where some Python
packages like scipy that TensorFlow depends on need to be compiled before the
diff --git a/tensorflow/docs_src/install/install_sources.md b/tensorflow/docs_src/install/install_sources.md
index 8bb09f4021..dfd9fbce4b 100644
--- a/tensorflow/docs_src/install/install_sources.md
+++ b/tensorflow/docs_src/install/install_sources.md
@@ -180,7 +180,10 @@ If you follow these instructions, you will not need to disable SIP.
After installing pip, invoke the following commands:
-<pre> $ <b>sudo pip install six numpy wheel mock</b> </pre>
+<pre> $ <b>sudo pip install six numpy wheel mock h5py</b>
+ $ <b>sudo pip install keras_applications==1.0.4 --no-deps</b>
+ $ <b>sudo pip install keras_preprocessing==1.0.2 --no-deps</b>
+</pre>
Note: These are just the minimum requirements to _build_ tensorflow. Installing
the pip package will download additional packages required to _run_ it. If you
@@ -375,10 +378,10 @@ 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 1.10.0rc1 on Linux:
+for TensorFlow 1.10.0 on Linux:
<pre>
-$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.10.0rc1-py2-none-any.whl</b>
+$ <b>sudo pip install /tmp/tensorflow_pkg/tensorflow-1.10.0-py2-none-any.whl</b>
</pre>
## Validate your installation
diff --git a/tensorflow/docs_src/performance/xla/operation_semantics.md b/tensorflow/docs_src/performance/xla/operation_semantics.md
index 76d2bb4606..bd7b0f7048 100644
--- a/tensorflow/docs_src/performance/xla/operation_semantics.md
+++ b/tensorflow/docs_src/performance/xla/operation_semantics.md
@@ -1877,19 +1877,19 @@ See also
[`XlaBuilder::RngNormal`](https://www.tensorflow.org/code/tensorflow/compiler/xla/client/xla_builder.h).
Constructs an output of a given shape with random numbers generated following
-the $$N(\mu, \sigma)$$ normal distribution. The parameters `mu` and `sigma`, and
-output shape have to have elemental type F32. The parameters furthermore have to
-be scalar valued.
+the $$N(\mu, \sigma)$$ normal distribution. The parameters $$\mu$$ and
+$$\sigma$$, and output shape have to have a floating point elemental type. The
+parameters furthermore have to be scalar valued.
-<b>`RngNormal(mean, sigma, shape)`</b>
+<b>`RngNormal(mu, sigma, shape)`</b>
| Arguments | Type | Semantics |
| --------- | ------- | --------------------------------------------------- |
-| `mu` | `XlaOp` | Scalar of type F32 specifying mean of generated |
-: : : numbers :
-| `sigma` | `XlaOp` | Scalar of type F32 specifying standard deviation of |
+| `mu` | `XlaOp` | Scalar of type T specifying mean of generated |
+: : : numbers :
+| `sigma` | `XlaOp` | Scalar of type T specifying standard deviation of |
: : : generated numbers :
-| `shape` | `Shape` | Output shape of type F32 |
+| `shape` | `Shape` | Output shape of type T |
## RngUniform
@@ -1898,9 +1898,11 @@ See also
Constructs an output of a given shape with random numbers generated following
the uniform distribution over the interval $$[a,b)$$. The parameters and output
-shape may be either F32, S32 or U32, but the types have to be consistent.
-Furthermore, the parameters need to be scalar valued. If $$b <= a$$ the result
-is implementation-defined.
+element type have to be a boolean type, an integral type or a floating point
+types, and the types have to be consistent. The CPU and GPU backends currently
+only support F64, F32, F16, BF16, S64, U64, S32 and U32. Furthermore, the
+parameters need to be scalar valued. If $$b <= a$$ the result is
+implementation-defined.
<b>`RngUniform(a, b, shape)`</b>
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-15 10:57:33 +0000