Merge pull request tensorflow#5097 from yifeif/r0.11

yifeif · web-flow · commit b48f9aec1f33 · 2016-10-20T15:43:55.000-07:00
Update doc and release note for 0.11.0rc1
diff --git a/RELEASE.md b/RELEASE.md
@@ -2,6 +2,7 @@
 
 ## Major Features and Improvements
 
+* CUDA 8 support.
 * cuDNN 5 support.
 * HDFS Support.
 * Adds Fused LSTM support via cuDNN 5 in `tensorflow/contrib/cudnn_rnn`.
diff --git a/tensorflow/g3doc/api_docs/cc/ClassEnv.md b/tensorflow/g3doc/api_docs/cc/ClassEnv.md
@@ -90,6 +90,24 @@ Stores in *result the names of the children of the specified directory. The name
 
 Original contents of *results are dropped.
 
+#### `virtual bool tensorflow::Env::MatchPath(const string &path, const string &pattern)=0` {#virtual_bool_tensorflow_Env_MatchPath}
+
+Returns true if the path matches the given pattern. The wildcards allowed in pattern are described below (GetMatchingPaths).
+
+
+
+#### `Status tensorflow::Env::GetMatchingPaths(const string &pattern, std::vector< string > *results)` {#Status_tensorflow_Env_GetMatchingPaths}
+
+Given a pattern, stores in *results the set of paths that matches that pattern. *results is cleared.
+
+pattern must match all of a name, not just a substring. pattern: { term } term: &apos;*&apos;: matches any sequence of non-&apos;/&apos; characters &apos;?&apos;: matches a single non-&apos;/&apos; character &apos;[&apos; [ &apos;^&apos; ] { match-list } &apos;]&apos;: matches any single character (not) on the list c: matches character c (c != &apos;*&apos;, &apos;?&apos;, &apos;\&apos;, &apos;[&apos;) &apos;\&apos; c: matches character c character-range: c: matches character c (c != &apos;\&apos;, &apos;-&apos;, &apos;]&apos;) &apos;\&apos; c: matches character c lo &apos;-&apos; hi: matches character c for lo <= c <= hi
+
+Typical return codes
+
+OK - no errors
+
+UNIMPLEMENTED - Some underlying functions (like GetChildren) are not implemented The default implementation uses a combination of GetChildren, MatchPath and IsDirectory.
+
 #### `Status tensorflow::Env::DeleteFile(const string &fname)` {#Status_tensorflow_Env_DeleteFile}
 
 Deletes the named file.
@@ -110,11 +128,27 @@ PERMISSION_DENIED - dirname or some descendant is not writable
 
 UNIMPLEMENTED - Some underlying functions (like Delete) are not implemented
 
+#### `Status tensorflow::Env::RecursivelyCreateDir(const string &dirname)` {#Status_tensorflow_Env_RecursivelyCreateDir}
+
+Creates the specified directory and all the necessary subdirectories. Typical return codes.
+
+
+
+OK - successfully created the directory and sub directories, even if they were already created.
+
+PERMISSION_DENIED - dirname or some subdirectory is not writable.
+
 #### `Status tensorflow::Env::CreateDir(const string &dirname)` {#Status_tensorflow_Env_CreateDir}
 
-Creates the specified directory.
+Creates the specified directory. Typical return codes.
+
+
+
+OK - successfully created the directory.
 
+ALREADY_EXISTS - directory already exists.
 
+PERMISSION_DENIED - dirname is not writable.
 
 #### `Status tensorflow::Env::DeleteDir(const string &dirname)` {#Status_tensorflow_Env_DeleteDir}
 
diff --git a/tensorflow/g3doc/api_docs/cc/ClassEnvWrapper.md b/tensorflow/g3doc/api_docs/cc/ClassEnvWrapper.md
@@ -42,6 +42,12 @@ Returns the file system schemes registered for this Env .
 
 
 
+#### `bool tensorflow::EnvWrapper::MatchPath(const string &path, const string &pattern) override` {#bool_tensorflow_EnvWrapper_MatchPath}
+
+Returns true if the path matches the given pattern. The wildcards allowed in pattern are described below (GetMatchingPaths).
+
+
+
 #### `uint64 tensorflow::EnvWrapper::NowMicros() override` {#uint64_tensorflow_EnvWrapper_NowMicros}
 
 Returns the number of micro-seconds since some fixed point in time. Only useful for computing deltas of time.
diff --git a/tensorflow/g3doc/api_docs/cc/ClassTensor.md b/tensorflow/g3doc/api_docs/cc/ClassTensor.md
@@ -100,12 +100,6 @@ Convenience accessor for the tensor shape.
 
 
 
-#### `size_t tensorflow::Tensor::BufferHash() const` {#size_t_tensorflow_Tensor_BufferHash}
-
-
-
-
-
 #### `bool tensorflow::Tensor::IsInitialized() const` {#bool_tensorflow_Tensor_IsInitialized}
 
 If necessary, has this Tensor been initialized?
@@ -379,7 +373,7 @@ NOTE: The underlying tensor buffer is refcounted, so the lifetime of the content
 
 REQUIRES: `DataTypeCanUseMemcpy(dtype())`.
 
-#### `void tensorflow::Tensor::UnsafeCopyFromInternal(const Tensor &, const TensorShape &)` {#void_tensorflow_Tensor_UnsafeCopyFromInternal}
+#### `void tensorflow::Tensor::UnsafeCopyFromInternal(const Tensor &, DataType dtype, const TensorShape &)` {#void_tensorflow_Tensor_UnsafeCopyFromInternal}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.train.Saver.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.train.Saver.md
@@ -72,7 +72,7 @@ protocol buffer file in the call to `save()`.
 
 - - -
 
-#### `tf.train.Saver.__init__(var_list=None, reshape=False, sharded=False, max_to_keep=5, keep_checkpoint_every_n_hours=10000.0, name=None, restore_sequentially=False, saver_def=None, builder=None, defer_build=False, allow_empty=False)` {#Saver.__init__}
+#### `tf.train.Saver.__init__(var_list=None, reshape=False, sharded=False, max_to_keep=5, keep_checkpoint_every_n_hours=10000.0, name=None, restore_sequentially=False, saver_def=None, builder=None, defer_build=False, allow_empty=False, write_version=1)` {#Saver.__init__}
 
 Creates a `Saver`.
 
@@ -140,6 +140,11 @@ checkpoints per device.
 *  <b>`allow_empty`</b>: If `False` (default) raise an error if there are no
     variables in the graph. Otherwise, construct the saver anyway and make
     it a no-op.
+*  <b>`write_version`</b>: controls what format to use when saving checkpoints.  It
+    also affects certain filepath matching logic.  Defaults to V1
+    currently, and will be switched to the more memory-efficient V2 format
+    in the future.  If set to V2, the Saver is still able to restore from
+    old V1 checkpoints.
 
 ##### Raises:
 
diff --git a/tensorflow/g3doc/api_docs/python/state_ops.md b/tensorflow/g3doc/api_docs/python/state_ops.md
@@ -1522,7 +1522,7 @@ protocol buffer file in the call to `save()`.
 
 - - -
 
-#### `tf.train.Saver.__init__(var_list=None, reshape=False, sharded=False, max_to_keep=5, keep_checkpoint_every_n_hours=10000.0, name=None, restore_sequentially=False, saver_def=None, builder=None, defer_build=False, allow_empty=False)` {#Saver.__init__}
+#### `tf.train.Saver.__init__(var_list=None, reshape=False, sharded=False, max_to_keep=5, keep_checkpoint_every_n_hours=10000.0, name=None, restore_sequentially=False, saver_def=None, builder=None, defer_build=False, allow_empty=False, write_version=1)` {#Saver.__init__}
 
 Creates a `Saver`.
 
@@ -1590,6 +1590,11 @@ checkpoints per device.
 *  <b>`allow_empty`</b>: If `False` (default) raise an error if there are no
     variables in the graph. Otherwise, construct the saver anyway and make
     it a no-op.
+*  <b>`write_version`</b>: controls what format to use when saving checkpoints.  It
+    also affects certain filepath matching logic.  Defaults to V1
+    currently, and will be switched to the more memory-efficient V2 format
+    in the future.  If set to V2, the Saver is still able to restore from
+    old V1 checkpoints.
 
 ##### Raises:
 
diff --git a/tensorflow/g3doc/get_started/os_setup.md b/tensorflow/g3doc/get_started/os_setup.md
@@ -7,7 +7,7 @@ github source.
 
 The TensorFlow Python API supports Python 2.7 and Python 3.3+.
 
-The GPU version works best with Cuda Toolkit 7.5 and
+The GPU version works best with Cuda Toolkit 8.0 and
 cuDNN v5.  Other versions are supported (Cuda toolkit >= 7.0 and
 cuDNN >= v3) only when installing from sources.
 Please see [Cuda installation](#optional-install-cuda-gpus-on-linux) for
@@ -66,7 +66,7 @@ Then, select the correct binary to install:
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 2.7:
@@ -79,14 +79,14 @@ $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorf
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, CPU only, Python 3.5
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 3.4 or 3.5:
@@ -162,7 +162,7 @@ Now, install TensorFlow just as you would for a regular Pip installation. First
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 2.7:
@@ -175,14 +175,14 @@ Now, install TensorFlow just as you would for a regular Pip installation. First
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, CPU only, Python 3.5
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 3.4 or 3.5:
@@ -301,7 +301,7 @@ select the correct binary to install:
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp27-none-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 2.7:
@@ -314,14 +314,14 @@ select the correct binary to install:
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp34-cp34m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, CPU only, Python 3.5
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
-# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below.
+# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Install from sources" below.
 (tensorflow)$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc1-cp35-cp35m-linux_x86_64.whl
 
 # Mac OS X, CPU only, Python 3.4 or 3.5:
@@ -454,7 +454,7 @@ the Docker container.
 ### (Optional, Linux) Enable GPU Support
 
 If you installed the GPU version of TensorFlow, you must also install the Cuda
-Toolkit 7.5 and cuDNN v5.  Please see [Cuda
+Toolkit 8.0 and cuDNN v5.  Please see [Cuda
 installation](#optional-install-cuda-gpus-on-linux).
 
 You also need to set the `LD_LIBRARY_PATH` and `CUDA_HOME` environment
@@ -594,7 +594,7 @@ https://developer.nvidia.com/cuda-gpus
 
 https://developer.nvidia.com/cuda-downloads
 
-Install version 7.5 if using our binary releases.
+Install version 8.0 if using our binary releases.
 
 Install the toolkit into e.g. `/usr/local/cuda`
 
@@ -609,7 +609,7 @@ toolkit is installed in `/usr/local/cuda`, run the following commands (edited
 to reflect the cuDNN version you downloaded):
 
 ``` bash
-tar xvzf cudnn-7.5-linux-x64-v5.1-ga.tgz
+tar xvzf cudnn-8.0-linux-x64-v5.1-ga.tgz
 sudo cp cuda/include/cudnn.h /usr/local/cuda/include
 sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
 sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
@@ -686,9 +686,9 @@ Once you have it downloaded locally, you can unzip and move the header and
 libraries to your local CUDA Toolkit folder:
 
 ```bash
-$ sudo mv include/cudnn.h /Developer/NVIDIA/CUDA-7.5/include/
-$ sudo mv lib/libcudnn* /Developer/NVIDIA/CUDA-7.5/lib
-$ sudo ln -s /Developer/NVIDIA/CUDA-7.5/lib/libcudnn* /usr/local/cuda/lib/
+$ sudo mv include/cudnn.h /Developer/NVIDIA/CUDA-8.0/include/
+$ sudo mv lib/libcudnn* /Developer/NVIDIA/CUDA-8.0/lib
+$ sudo ln -s /Developer/NVIDIA/CUDA-8.0/lib/libcudnn* /usr/local/cuda/lib/
 ```
 
 To verify the CUDA installation, you can build and run deviceQuery to make sure
@@ -702,8 +702,9 @@ $ popd
 $ ~/cuda-samples/bin/x86_64/darwin/release/deviceQuery
 ```
 
-If you want to compile tensorflow and have the XCode 7.3 installed, note that
-Xcode 7.3 is not yet compatible with CUDA 7.5. You will need to download Xcode
+If you want to compile tensorflow and have XCode 7.3 and CUDA 7.5 installed, note that
+Xcode 7.3 is not yet compatible with CUDA 7.5. You can either upgrade to CUDA
+8.0, or you will need to download Xcode
 7.2 and select it as your default:
 
 ```bash
@@ -734,8 +735,8 @@ No Google Cloud Platform support will be enabled for TensorFlow
 Do you wish to build TensorFlow with GPU support? [y/N] y
 GPU support will be enabled for TensorFlow
 Please specify which gcc nvcc should use as the host compiler. [Default is /usr/bin/gcc]:
-Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 7.5
-Please specify the location where CUDA 7.5 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
+Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 8.0
+Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
 Please specify the cuDNN version you want to use. [Leave empty to use system default]: 5
 Please specify the location where cuDNN 5 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
 Please specify a list of comma-separated Cuda compute capabilities you want to build with.
