Merge pull request tensorflow#3572 from gunan/r0.10

gunan · web-flow · commit 0b70bd8d6775 · 2016-07-29T14:04:55.000-07:00
Update documentation for r0.10 release.
diff --git a/tensorflow/g3doc/api_docs/cc/ClassEnv.md b/tensorflow/g3doc/api_docs/cc/ClassEnv.md
@@ -38,7 +38,7 @@ Returns the file system schemes registered for this Env .
 
 
 
-#### `Status tensorflow::Env::NewRandomAccessFile(const string &fname, RandomAccessFile **result)` {#Status_tensorflow_Env_NewRandomAccessFile}
+#### `Status tensorflow::Env::NewRandomAccessFile(const string &fname, std::unique_ptr< RandomAccessFile > *result)` {#Status_tensorflow_Env_NewRandomAccessFile}
 
 Creates a brand new random access read-only file with the specified name.
 
@@ -48,7 +48,7 @@ The returned file may be concurrently accessed by multiple threads.
 
 The ownership of the returned RandomAccessFile is passed to the caller and the object should be deleted when is not used. The file object shouldn&apos;t live longer than the Env object.
 
-#### `Status tensorflow::Env::NewWritableFile(const string &fname, WritableFile **result)` {#Status_tensorflow_Env_NewWritableFile}
+#### `Status tensorflow::Env::NewWritableFile(const string &fname, std::unique_ptr< WritableFile > *result)` {#Status_tensorflow_Env_NewWritableFile}
 
 Creates an object that writes to a new file with the specified name.
 
@@ -58,7 +58,7 @@ The returned file will only be accessed by one thread at a time.
 
 The ownership of the returned WritableFile is passed to the caller and the object should be deleted when is not used. The file object shouldn&apos;t live longer than the Env object.
 
-#### `Status tensorflow::Env::NewAppendableFile(const string &fname, WritableFile **result)` {#Status_tensorflow_Env_NewAppendableFile}
+#### `Status tensorflow::Env::NewAppendableFile(const string &fname, std::unique_ptr< WritableFile > *result)` {#Status_tensorflow_Env_NewAppendableFile}
 
 Creates an object that either appends to an existing file, or writes to a new file (if the file does not exist to begin with).
 
@@ -68,7 +68,7 @@ The returned file will only be accessed by one thread at a time.
 
 The ownership of the returned WritableFile is passed to the caller and the object should be deleted when is not used. The file object shouldn&apos;t live longer than the Env object.
 
-#### `Status tensorflow::Env::NewReadOnlyMemoryRegionFromFile(const string &fname, ReadOnlyMemoryRegion **result)` {#Status_tensorflow_Env_NewReadOnlyMemoryRegionFromFile}
+#### `Status tensorflow::Env::NewReadOnlyMemoryRegionFromFile(const string &fname, std::unique_ptr< ReadOnlyMemoryRegion > *result)` {#Status_tensorflow_Env_NewReadOnlyMemoryRegionFromFile}
 
 Creates a readonly region of memory with the file context.
 
@@ -96,6 +96,20 @@ Deletes the named file.
 
 
 
+#### `Status tensorflow::Env::DeleteRecursively(const string &dirname, int64 *undeleted_files, int64 *undeleted_dirs)` {#Status_tensorflow_Env_DeleteRecursively}
+
+Deletes the specified directory and all subdirectories and files underneath it. undeleted_files and undeleted_dirs stores the number of files and directories that weren&apos;t deleted (unspecified if the return status is not OK). REQUIRES: undeleted_files, undeleted_dirs to be not null. Typical return codes.
+
+
+
+OK - dirname exists and we were able to delete everything underneath.
+
+NOT_FOUND - dirname doesn&apos;t exist
+
+PERMISSION_DENIED - dirname or some descendant is not writable
+
+UNIMPLEMENTED - Some underlying functions (like Delete) are not implemented
+
 #### `Status tensorflow::Env::CreateDir(const string &dirname)` {#Status_tensorflow_Env_CreateDir}
 
 Creates the specified directory.
@@ -108,6 +122,28 @@ Deletes the specified directory.
 
 
 
+#### `Status tensorflow::Env::Stat(const string &fname, FileStatistics *stat)` {#Status_tensorflow_Env_Stat}
+
+Obtains statistics for the given path.
+
+
+
+#### `Status tensorflow::Env::IsDirectory(const string &fname)` {#Status_tensorflow_Env_IsDirectory}
+
+Returns whether the given path is a directory or not. Typical return codes (not guaranteed exhaustive):
+
+
+
+OK - The path exists and is a directory.
+
+FAILED_PRECONDITION - The path exists and is not a directory.
+
+NOT_FOUND - The path entry does not exist.
+
+PERMISSION_DENIED - Insufficient permissions.
+
+UNIMPLEMENTED - The file factory doesn&apos;t support directories.
+
 #### `Status tensorflow::Env::GetFileSize(const string &fname, uint64 *file_size)` {#Status_tensorflow_Env_GetFileSize}
 
 Stores the size of `fname` in `*file_size`.
@@ -126,7 +162,13 @@ Returns the number of micro-seconds since some fixed point in time. Only useful
 
 
 
-#### `virtual void tensorflow::Env::SleepForMicroseconds(int micros)=0` {#virtual_void_tensorflow_Env_SleepForMicroseconds}
+#### `virtual uint64 tensorflow::Env::NowSeconds()` {#virtual_uint64_tensorflow_Env_NowSeconds}
+
+Returns the number of seconds since some fixed point in time. Only useful for computing deltas of time.
+
+
+
+#### `virtual void tensorflow::Env::SleepForMicroseconds(int64 micros)=0` {#virtual_void_tensorflow_Env_SleepForMicroseconds}
 
 Sleeps/delays the thread for the prescribed number of micro-seconds.
 
@@ -144,7 +186,7 @@ Caller takes ownership of the result and must delete it eventually (the deletion
 
 
 
-#### `virtual void tensorflow::Env::SchedClosureAfter(int micros, std::function< void()> closure)=0` {#virtual_void_tensorflow_Env_SchedClosureAfter}
+#### `virtual void tensorflow::Env::SchedClosureAfter(int64 micros, std::function< void()> closure)=0` {#virtual_void_tensorflow_Env_SchedClosureAfter}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/cc/ClassEnvWrapper.md b/tensorflow/g3doc/api_docs/cc/ClassEnvWrapper.md
@@ -48,7 +48,7 @@ Returns the number of micro-seconds since some fixed point in time. Only useful
 
 
 
-#### `void tensorflow::EnvWrapper::SleepForMicroseconds(int micros) override` {#void_tensorflow_EnvWrapper_SleepForMicroseconds}
+#### `void tensorflow::EnvWrapper::SleepForMicroseconds(int64 micros) override` {#void_tensorflow_EnvWrapper_SleepForMicroseconds}
 
 Sleeps/delays the thread for the prescribed number of micro-seconds.
 
@@ -66,7 +66,7 @@ Caller takes ownership of the result and must delete it eventually (the deletion
 
 
 
-#### `void tensorflow::EnvWrapper::SchedClosureAfter(int micros, std::function< void()> closure) override` {#void_tensorflow_EnvWrapper_SchedClosureAfter}
+#### `void tensorflow::EnvWrapper::SchedClosureAfter(int64 micros, std::function< void()> closure) override` {#void_tensorflow_EnvWrapper_SchedClosureAfter}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/cc/ClassTensor.md b/tensorflow/g3doc/api_docs/cc/ClassTensor.md
@@ -8,9 +8,13 @@ Represents an n-dimensional array of values.
 
 #### `tensorflow::Tensor::Tensor()` {#tensorflow_Tensor_Tensor}
 
-Default Tensor constructor. Creates a 1-dimension, 0-element float tensor.
+Creates a 1-dimensional, 0-element float tensor.
 
+The returned Tensor is not a scalar (shape {}), but is instead an empty one-dimensional Tensor (shape {0}, NumElements() == 0). Since it has no elements, it does not need to be assigned a value and is initialized by default ( IsInitialized() is true). If this is undesirable, consider creating a one-element scalar which does require initialization:
 
+```c++ Tensor(DT_FLOAT, TensorShape({}))
+
+```
 
 #### `tensorflow::Tensor::Tensor(DataType type, const TensorShape &shape)` {#tensorflow_Tensor_Tensor}
 
@@ -32,22 +36,28 @@ Creates a tensor with the input `type` and `shape`, using the allocator `a` and
 
 #### `tensorflow::Tensor::Tensor(DataType type)` {#tensorflow_Tensor_Tensor}
 
-Creates an uninitialized Tensor of the given data type.
-
+Creates an empty Tensor of the given data type.
 
+Like Tensor() , returns a 1-dimensional, 0-element Tensor with IsInitialized() returning True. See the Tensor() documentation for details.
 
 #### `tensorflow::Tensor::Tensor(const Tensor &other)` {#tensorflow_Tensor_Tensor}
 
 
 
 
 
-#### `tensorflow::Tensor::~Tensor()` {#tensorflow_Tensor_Tensor}
+#### `tensorflow::Tensor::Tensor(Tensor &&other)` {#tensorflow_Tensor_Tensor}
 
 Copy constructor.
 
 
 
+#### `tensorflow::Tensor::~Tensor()` {#tensorflow_Tensor_Tensor}
+
+
+
+
+
 #### `DataType tensorflow::Tensor::dtype() const` {#DataType_tensorflow_Tensor_dtype}
 
 Returns the data type.
@@ -98,9 +108,9 @@ Convenience accessor for the tensor shape.
 
 #### `bool tensorflow::Tensor::IsInitialized() const` {#bool_tensorflow_Tensor_IsInitialized}
 
-Has this Tensor been initialized?
-
+If necessary, has this Tensor been initialized?
 
+Zero-element Tensors are always considered initialized, even if they have never been assigned to and do not have any memory allocated.
 
 #### `size_t tensorflow::Tensor::TotalBytes() const` {#size_t_tensorflow_Tensor_TotalBytes}
 
@@ -120,6 +130,12 @@ Assign operator. This tensor shares other&apos;s underlying storage.
 
 
 
+#### `Tensor & tensorflow::Tensor::operator=(Tensor &&other)` {#Tensor_tensorflow_Tensor_operator_}
+
+Move operator. See move constructor for details.
+
+
+
 #### `bool tensorflow::Tensor::CopyFrom(const Tensor &other, const TensorShape &shape) TF_MUST_USE_RESULT` {#bool_tensorflow_Tensor_CopyFrom}
 
 Copy the other tensor into this tensor and reshape it.
@@ -190,6 +206,12 @@ auto mat = my_mat.matrix<int32>();// CHECK fails as type mismatch.
 
 
 
+#### `TTypes< T, NDIMS >::Tensor tensorflow::Tensor::bit_casted_tensor()` {#TTypes_T_NDIMS_Tensor_tensorflow_Tensor_bit_casted_tensor}
+
+Return the tensor data to an `Eigen::Tensor` with the same size but a bitwise cast to the specified dtype `T`.
+
+Using a bitcast is useful for move and copy operations. NOTE: this is the same as `tensor()` except a bitcast is allowed.
+
 #### `TTypes<T>::Flat tensorflow::Tensor::flat()` {#TTypes_T_Flat_tensorflow_Tensor_flat}
 
 Return the tensor data as an `Eigen::Tensor` of the data type and a specified shape.
@@ -239,6 +261,12 @@ Returns the data as an Eigen::Tensor with NDIMS dimensions, collapsing all Tenso
 
 
 
+#### `TTypes< T, NDIMS >::Tensor tensorflow::Tensor::bit_casted_shaped(gtl::ArraySlice< int64 > new_sizes)` {#TTypes_T_NDIMS_Tensor_tensorflow_Tensor_bit_casted_shaped}
+
+Return the tensor data to an `Eigen::Tensor` with the new shape specified in `new_sizes` and cast to a new dtype `T`.
+
+Using a bitcast is useful for move and copy operations. The allowed bitcast is the only difference from `shaped()`.
+
 #### `TTypes< T, NDIMS >::UnalignedTensor tensorflow::Tensor::unaligned_shaped(gtl::ArraySlice< int64 > new_sizes)` {#TTypes_T_NDIMS_UnalignedTensor_tensorflow_Tensor_unaligned_shaped}
 
 
@@ -269,6 +297,12 @@ Const versions of all the methods above.
 
 
 
+#### `TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::bit_casted_tensor() const` {#TTypes_T_NDIMS_ConstTensor_tensorflow_Tensor_bit_casted_tensor}
+
+Return the tensor data to an `Eigen::Tensor` with the same size but a bitwise cast to the specified dtype `T`.
+
+Using a bitcast is useful for move and copy operations. NOTE: this is the same as `tensor()` except a bitcast is allowed.
+
 #### `TTypes<T>::ConstFlat tensorflow::Tensor::flat() const` {#TTypes_T_ConstFlat_tensorflow_Tensor_flat}
 
 
@@ -287,6 +321,12 @@ Const versions of all the methods above.
 
 
 
+#### `TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::bit_casted_shaped(gtl::ArraySlice< int64 > new_sizes) const` {#TTypes_T_NDIMS_ConstTensor_tensorflow_Tensor_bit_casted_shaped}
+
+Return the tensor data to an `Eigen::Tensor` with the new shape specified in `new_sizes` and cast to a new dtype `T`.
+
+Using a bitcast is useful for move and copy operations. The allowed bitcast is the only difference from `shaped()`.
+
 #### `TTypes< T, NDIMS >::UnalignedConstTensor tensorflow::Tensor::unaligned_shaped(gtl::ArraySlice< int64 > new_sizes) const` {#TTypes_T_NDIMS_UnalignedConstTensor_tensorflow_Tensor_unaligned_shaped}
 
 
@@ -337,7 +377,7 @@ The returned ` StringPiece ` may point to memory location on devices that the CP
 
 NOTE: The underlying tensor buffer is refcounted, so the lifetime of the contents mapped by the ` StringPiece ` matches the lifetime of the buffer; callers should arrange to make sure the buffer does not get destroyed while the ` StringPiece ` is still used.
 
-REQUIRES: `DataTypeCanUseMemcpy( dtype() )`.
+REQUIRES: `DataTypeCanUseMemcpy(dtype())`.
 
 #### `void tensorflow::Tensor::UnsafeCopyFromInternal(const Tensor &, const TensorShape &)` {#void_tensorflow_Tensor_UnsafeCopyFromInternal}
 
diff --git a/tensorflow/g3doc/api_docs/cc/ClassTensorShape.md b/tensorflow/g3doc/api_docs/cc/ClassTensorShape.md
@@ -60,6 +60,18 @@ Copy the specified shape.
 
 
 
+#### `tensorflow::TensorShape::TensorShape(TensorShape &&b)` {#tensorflow_TensorShape_TensorShape}
+
+Move the specified shape. After moving, is safe for destruction and.
+
+
+
+#### `void tensorflow::TensorShape::operator=(TensorShape &&b)` {#void_tensorflow_TensorShape_operator_}
+
+
+
+
+
 #### `void tensorflow::TensorShape::Clear()` {#void_tensorflow_TensorShape_Clear}
 
 Clear a tensor shape.
diff --git a/tensorflow/g3doc/api_docs/cc/ClassTensorShapeUtils.md b/tensorflow/g3doc/api_docs/cc/ClassTensorShapeUtils.md
@@ -36,13 +36,25 @@ Static helper routines for ` TensorShape `. Includes a few common predicates on
 
 
 
-#### `static Status tensorflow::TensorShapeUtils::MakeShape(const int32 *dims, int n, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
+#### `static Status tensorflow::TensorShapeUtils::MakeShape(const int32 *dims, int64 n, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
 
 Returns a ` TensorShape ` whose dimensions are `dims[0]`, `dims[1]`, ..., `dims[n-1]`.
 
 
 
-#### `static Status tensorflow::TensorShapeUtils::MakeShape(const int64 *dims, int n, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
+#### `static Status tensorflow::TensorShapeUtils::MakeShape(const int64 *dims, int64 n, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
+
+
+
+
+
+#### `static Status tensorflow::TensorShapeUtils::MakeShape(gtl::ArraySlice< int32 > shape, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
+
+
+
+
+
+#### `static Status tensorflow::TensorShapeUtils::MakeShape(gtl::ArraySlice< int64 > shape, TensorShape *out)` {#static_Status_tensorflow_TensorShapeUtils_MakeShape}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/cc/StructTF_Buffer.md b/tensorflow/g3doc/api_docs/cc/StructTF_Buffer.md
@@ -18,7 +18,7 @@
 
 
 
-#### `void(* TF_Buffer::data_deallocator) (void *data, size_t length))(void *data, size_t length)` {#void_TF_Buffer_data_deallocator_void_data_size_t_length_}
+#### `void(* TF_Buffer::data_deallocator)(void *data, size_t length))(void *data, size_t length)` {#void_TF_Buffer_data_deallocator_void_data_size_t_length_}
 
 
 
diff --git a/tensorflow/g3doc/api_docs/python/client.md b/tensorflow/g3doc/api_docs/python/client.md
@@ -350,7 +350,8 @@ the session constructor.
 
 
 *  <b>`target`</b>: (Optional.) The execution engine to connect to.
-    Defaults to using an in-process engine.
+    Defaults to using an in-process engine. At present, no value
+    other than the empty string is supported.
 *  <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).
 *  <b>`config`</b>: (Optional) `ConfigProto` proto used to configure the session.
 
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.nn.rnn.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.nn.rnn.md
@@ -2,15 +2,15 @@
 
 Creates a recurrent neural network specified by RNNCell `cell`.
 
-##### The simplest form of RNN network generated is:
-
+The simplest form of RNN network generated is:
+```py
   state = cell.zero_state(...)
   outputs = []
   for input_ in inputs:
     output, state = cell(input_, state)
     outputs.append(output)
   return (outputs, state)
-
+```
 However, a few other options are available:
 
 An initial state can be provided.
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.InteractiveSession.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard2/tf.InteractiveSession.md
@@ -53,7 +53,8 @@ the session constructor.
 
 
 *  <b>`target`</b>: (Optional.) The execution engine to connect to.
-    Defaults to using an in-process engine.
+    Defaults to using an in-process engine. At present, no value
+    other than the empty string is supported.
 *  <b>`graph`</b>: (Optional.) The `Graph` to be launched (described above).
 *  <b>`config`</b>: (Optional) `ConfigProto` proto used to configure the session.
 
diff --git a/tensorflow/g3doc/api_docs/python/nn.md b/tensorflow/g3doc/api_docs/python/nn.md
@@ -1582,15 +1582,15 @@ automatically performed.
 
 Creates a recurrent neural network specified by RNNCell `cell`.
 
-##### The simplest form of RNN network generated is:
-
+The simplest form of RNN network generated is:
+```py
   state = cell.zero_state(...)
   outputs = []
   for input_ in inputs:
     output, state = cell(input_, state)
     outputs.append(output)
   return (outputs, state)
-
+```
 However, a few other options are available:
 
 An initial state can be provided.

Original file line number	Diff line number	Diff line change
`@@ -18,7 +18,7 @@`
`18`	`18`
`19`	`19`
`20`	`20`
`21`		-#### `void(* TF_Buffer::data_deallocator) (void data, size_t length))(void data, size_t length)` {#void_TF_Buffer_data_deallocator_void_data_size_t_length_}
	`21`	+#### `void(* TF_Buffer::data_deallocator)(void data, size_t length))(void data, size_t length)` {#void_TF_Buffer_data_deallocator_void_data_size_t_length_}
`22`	`22`
`23`	`23`
`24`	`24`