org.tensorflow.framework

Interface CallableOptionsOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

CallableOptions, CallableOptions.Builder

public interface CallableOptionsOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
boolean	containsFeedDevices(java.lang.String key) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
boolean	containsFetchDevices(java.lang.String key) map<string, string> fetch_devices = 7;
java.lang.String	getFeed(int index) Tensors to be fed in the callable.
com.google.protobuf.ByteString	getFeedBytes(int index) Tensors to be fed in the callable.
int	getFeedCount() Tensors to be fed in the callable.
java.util.Map<java.lang.String,java.lang.String>	getFeedDevices() Deprecated.
int	getFeedDevicesCount() The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
java.util.Map<java.lang.String,java.lang.String>	getFeedDevicesMap() The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
java.lang.String	getFeedDevicesOrDefault(java.lang.String key, java.lang.String defaultValue) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
java.lang.String	getFeedDevicesOrThrow(java.lang.String key) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
java.util.List<java.lang.String>	getFeedList() Tensors to be fed in the callable.
java.lang.String	getFetch(int index) Fetches.
com.google.protobuf.ByteString	getFetchBytes(int index) Fetches.
int	getFetchCount() Fetches.
java.util.Map<java.lang.String,java.lang.String>	getFetchDevices() Deprecated.
int	getFetchDevicesCount() map<string, string> fetch_devices = 7;
java.util.Map<java.lang.String,java.lang.String>	getFetchDevicesMap() map<string, string> fetch_devices = 7;
java.lang.String	getFetchDevicesOrDefault(java.lang.String key, java.lang.String defaultValue) map<string, string> fetch_devices = 7;
java.lang.String	getFetchDevicesOrThrow(java.lang.String key) map<string, string> fetch_devices = 7;
java.util.List<java.lang.String>	getFetchList() Fetches.
boolean	getFetchSkipSync() By default, RunCallable() will synchronize the GPU stream before returning fetched tensors on a GPU device, to ensure that the values in those tensors have been produced.
RunOptions	getRunOptions() Options that will be applied to each run.
RunOptionsOrBuilder	getRunOptionsOrBuilder() Options that will be applied to each run.
java.lang.String	getTarget(int index) Target Nodes.
com.google.protobuf.ByteString	getTargetBytes(int index) Target Nodes.
int	getTargetCount() Target Nodes.
java.util.List<java.lang.String>	getTargetList() Target Nodes.
TensorConnection	getTensorConnection(int index) Tensors to be connected in the callable.
int	getTensorConnectionCount() Tensors to be connected in the callable.
java.util.List<TensorConnection>	getTensorConnectionList() Tensors to be connected in the callable.
TensorConnectionOrBuilder	getTensorConnectionOrBuilder(int index) Tensors to be connected in the callable.
java.util.List<? extends TensorConnectionOrBuilder>	getTensorConnectionOrBuilderList() Tensors to be connected in the callable.
boolean	hasRunOptions() Options that will be applied to each run.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getFeedList

java.util.List<java.lang.String> getFeedList()

 Tensors to be fed in the callable. Each feed is the name of a tensor.
 

repeated string feed = 1;

Returns:

A list containing the feed.

getFeedCount

int getFeedCount()

 Tensors to be fed in the callable. Each feed is the name of a tensor.
 

repeated string feed = 1;

Returns:

The count of feed.

getFeed

java.lang.String getFeed(int index)

 Tensors to be fed in the callable. Each feed is the name of a tensor.
 

repeated string feed = 1;

Parameters:

index - The index of the element to return.

Returns:

The feed at the given index.

getFeedBytes

com.google.protobuf.ByteString getFeedBytes(int index)

 Tensors to be fed in the callable. Each feed is the name of a tensor.
 

repeated string feed = 1;

Parameters:

index - The index of the value to return.

Returns:

The bytes of the feed at the given index.

getFetchList

java.util.List<java.lang.String> getFetchList()

 Fetches. A list of tensor names. The caller of the callable expects a
 tensor to be returned for each fetch[i] (see RunStepResponse.tensor). The
 order of specified fetches does not change the execution order.
 

repeated string fetch = 2;

Returns:

A list containing the fetch.

getFetchCount

int getFetchCount()

 Fetches. A list of tensor names. The caller of the callable expects a
 tensor to be returned for each fetch[i] (see RunStepResponse.tensor). The
 order of specified fetches does not change the execution order.
 

repeated string fetch = 2;

Returns:

The count of fetch.

getFetch

java.lang.String getFetch(int index)

 Fetches. A list of tensor names. The caller of the callable expects a
 tensor to be returned for each fetch[i] (see RunStepResponse.tensor). The
 order of specified fetches does not change the execution order.
 

repeated string fetch = 2;

Parameters:

index - The index of the element to return.

Returns:

The fetch at the given index.

getFetchBytes

com.google.protobuf.ByteString getFetchBytes(int index)

 Fetches. A list of tensor names. The caller of the callable expects a
 tensor to be returned for each fetch[i] (see RunStepResponse.tensor). The
 order of specified fetches does not change the execution order.
 

repeated string fetch = 2;

Parameters:

index - The index of the value to return.

Returns:

The bytes of the fetch at the given index.

getTargetList

java.util.List<java.lang.String> getTargetList()

 Target Nodes. A list of node names. The named nodes will be run by the
 callable but their outputs will not be returned.
 

repeated string target = 3;

Returns:

A list containing the target.

getTargetCount

int getTargetCount()

 Target Nodes. A list of node names. The named nodes will be run by the
 callable but their outputs will not be returned.
 

repeated string target = 3;

Returns:

The count of target.

getTarget

java.lang.String getTarget(int index)

 Target Nodes. A list of node names. The named nodes will be run by the
 callable but their outputs will not be returned.
 

repeated string target = 3;

Parameters:

index - The index of the element to return.

Returns:

The target at the given index.

getTargetBytes

com.google.protobuf.ByteString getTargetBytes(int index)

 Target Nodes. A list of node names. The named nodes will be run by the
 callable but their outputs will not be returned.
 

repeated string target = 3;

Parameters:

index - The index of the value to return.

Returns:

The bytes of the target at the given index.

hasRunOptions

boolean hasRunOptions()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

Returns:

Whether the runOptions field is set.

getRunOptions

RunOptions getRunOptions()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

Returns:

The runOptions.

getRunOptionsOrBuilder

RunOptionsOrBuilder getRunOptionsOrBuilder()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

getTensorConnectionList

java.util.List<TensorConnection> getTensorConnectionList()

 Tensors to be connected in the callable. Each TensorConnection denotes
 a pair of tensors in the graph, between which an edge will be created
 in the callable.
 

repeated .tensorflow.TensorConnection tensor_connection = 5;

getTensorConnection

TensorConnection getTensorConnection(int index)

 Tensors to be connected in the callable. Each TensorConnection denotes
 a pair of tensors in the graph, between which an edge will be created
 in the callable.
 

repeated .tensorflow.TensorConnection tensor_connection = 5;

getTensorConnectionCount

int getTensorConnectionCount()

 Tensors to be connected in the callable. Each TensorConnection denotes
 a pair of tensors in the graph, between which an edge will be created
 in the callable.
 

repeated .tensorflow.TensorConnection tensor_connection = 5;

getTensorConnectionOrBuilderList

java.util.List<? extends TensorConnectionOrBuilder> getTensorConnectionOrBuilderList()

 Tensors to be connected in the callable. Each TensorConnection denotes
 a pair of tensors in the graph, between which an edge will be created
 in the callable.
 

repeated .tensorflow.TensorConnection tensor_connection = 5;

getTensorConnectionOrBuilder

TensorConnectionOrBuilder getTensorConnectionOrBuilder(int index)

 Tensors to be connected in the callable. Each TensorConnection denotes
 a pair of tensors in the graph, between which an edge will be created
 in the callable.
 

repeated .tensorflow.TensorConnection tensor_connection = 5;

getFeedDevicesCount

int getFeedDevicesCount()

 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
 The options below allow changing that - feeding tensors backed by
 device memory, or returning tensors that are backed by device memory.
 The maps below map the name of a feed/fetch tensor (which appears in
 'feed' or 'fetch' fields above), to the fully qualified name of the device
 owning the memory backing the contents of the tensor.
 For example, creating a callable with the following options:
 CallableOptions {
   feed: "a:0"
   feed: "b:0"
   fetch: "x:0"
   fetch: "y:0"
   feed_devices: {
     "a:0": "/job:localhost/replica:0/task:0/device:GPU:0"
   }
   fetch_devices: {
     "y:0": "/job:localhost/replica:0/task:0/device:GPU:0"
  }
 }
 means that the Callable expects:
 - The first argument ("a:0") is a Tensor backed by GPU memory.
 - The second argument ("b:0") is a Tensor backed by host memory.
 and of its return values:
 - The first output ("x:0") will be backed by host memory.
 - The second output ("y:0") will be backed by GPU memory.
 FEEDS:
 It is the responsibility of the caller to ensure that the memory of the fed
 tensors will be correctly initialized and synchronized before it is
 accessed by operations executed during the call to Session::RunCallable().
 This is typically ensured by using the TensorFlow memory allocators
 (Device::GetAllocator()) to create the Tensor to be fed.
 Alternatively, for CUDA-enabled GPU devices, this typically means that the
 operation that produced the contents of the tensor has completed, i.e., the
 CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or
 cuStreamSynchronize()).
 

map<string, string> feed_devices = 6;

containsFeedDevices

boolean containsFeedDevices(java.lang.String key)

 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
 The options below allow changing that - feeding tensors backed by
 device memory, or returning tensors that are backed by device memory.
 The maps below map the name of a feed/fetch tensor (which appears in
 'feed' or 'fetch' fields above), to the fully qualified name of the device
 owning the memory backing the contents of the tensor.
 For example, creating a callable with the following options:
 CallableOptions {
   feed: "a:0"
   feed: "b:0"
   fetch: "x:0"
   fetch: "y:0"
   feed_devices: {
     "a:0": "/job:localhost/replica:0/task:0/device:GPU:0"
   }
   fetch_devices: {
     "y:0": "/job:localhost/replica:0/task:0/device:GPU:0"
  }
 }
 means that the Callable expects:
 - The first argument ("a:0") is a Tensor backed by GPU memory.
 - The second argument ("b:0") is a Tensor backed by host memory.
 and of its return values:
 - The first output ("x:0") will be backed by host memory.
 - The second output ("y:0") will be backed by GPU memory.
 FEEDS:
 It is the responsibility of the caller to ensure that the memory of the fed
 tensors will be correctly initialized and synchronized before it is
 accessed by operations executed during the call to Session::RunCallable().
 This is typically ensured by using the TensorFlow memory allocators
 (Device::GetAllocator()) to create the Tensor to be fed.
 Alternatively, for CUDA-enabled GPU devices, this typically means that the
 operation that produced the contents of the tensor has completed, i.e., the
 CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or
 cuStreamSynchronize()).
 

map<string, string> feed_devices = 6;

getFeedDevices

@Deprecated
java.util.Map<java.lang.String,java.lang.String> getFeedDevices()

Deprecated.

Use getFeedDevicesMap() instead.

getFeedDevicesMap

java.util.Map<java.lang.String,java.lang.String> getFeedDevicesMap()

 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
 The options below allow changing that - feeding tensors backed by
 device memory, or returning tensors that are backed by device memory.
 The maps below map the name of a feed/fetch tensor (which appears in
 'feed' or 'fetch' fields above), to the fully qualified name of the device
 owning the memory backing the contents of the tensor.
 For example, creating a callable with the following options:
 CallableOptions {
   feed: "a:0"
   feed: "b:0"
   fetch: "x:0"
   fetch: "y:0"
   feed_devices: {
     "a:0": "/job:localhost/replica:0/task:0/device:GPU:0"
   }
   fetch_devices: {
     "y:0": "/job:localhost/replica:0/task:0/device:GPU:0"
  }
 }
 means that the Callable expects:
 - The first argument ("a:0") is a Tensor backed by GPU memory.
 - The second argument ("b:0") is a Tensor backed by host memory.
 and of its return values:
 - The first output ("x:0") will be backed by host memory.
 - The second output ("y:0") will be backed by GPU memory.
 FEEDS:
 It is the responsibility of the caller to ensure that the memory of the fed
 tensors will be correctly initialized and synchronized before it is
 accessed by operations executed during the call to Session::RunCallable().
 This is typically ensured by using the TensorFlow memory allocators
 (Device::GetAllocator()) to create the Tensor to be fed.
 Alternatively, for CUDA-enabled GPU devices, this typically means that the
 operation that produced the contents of the tensor has completed, i.e., the
 CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or
 cuStreamSynchronize()).
 

map<string, string> feed_devices = 6;

getFeedDevicesOrDefault

java.lang.String getFeedDevicesOrDefault(java.lang.String key,
                                         java.lang.String defaultValue)

 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
 The options below allow changing that - feeding tensors backed by
 device memory, or returning tensors that are backed by device memory.
 The maps below map the name of a feed/fetch tensor (which appears in
 'feed' or 'fetch' fields above), to the fully qualified name of the device
 owning the memory backing the contents of the tensor.
 For example, creating a callable with the following options:
 CallableOptions {
   feed: "a:0"
   feed: "b:0"
   fetch: "x:0"
   fetch: "y:0"
   feed_devices: {
     "a:0": "/job:localhost/replica:0/task:0/device:GPU:0"
   }
   fetch_devices: {
     "y:0": "/job:localhost/replica:0/task:0/device:GPU:0"
  }
 }
 means that the Callable expects:
 - The first argument ("a:0") is a Tensor backed by GPU memory.
 - The second argument ("b:0") is a Tensor backed by host memory.
 and of its return values:
 - The first output ("x:0") will be backed by host memory.
 - The second output ("y:0") will be backed by GPU memory.
 FEEDS:
 It is the responsibility of the caller to ensure that the memory of the fed
 tensors will be correctly initialized and synchronized before it is
 accessed by operations executed during the call to Session::RunCallable().
 This is typically ensured by using the TensorFlow memory allocators
 (Device::GetAllocator()) to create the Tensor to be fed.
 Alternatively, for CUDA-enabled GPU devices, this typically means that the
 operation that produced the contents of the tensor has completed, i.e., the
 CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or
 cuStreamSynchronize()).
 

map<string, string> feed_devices = 6;

getFeedDevicesOrThrow

java.lang.String getFeedDevicesOrThrow(java.lang.String key)

 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
 The options below allow changing that - feeding tensors backed by
 device memory, or returning tensors that are backed by device memory.
 The maps below map the name of a feed/fetch tensor (which appears in
 'feed' or 'fetch' fields above), to the fully qualified name of the device
 owning the memory backing the contents of the tensor.
 For example, creating a callable with the following options:
 CallableOptions {
   feed: "a:0"
   feed: "b:0"
   fetch: "x:0"
   fetch: "y:0"
   feed_devices: {
     "a:0": "/job:localhost/replica:0/task:0/device:GPU:0"
   }
   fetch_devices: {
     "y:0": "/job:localhost/replica:0/task:0/device:GPU:0"
  }
 }
 means that the Callable expects:
 - The first argument ("a:0") is a Tensor backed by GPU memory.
 - The second argument ("b:0") is a Tensor backed by host memory.
 and of its return values:
 - The first output ("x:0") will be backed by host memory.
 - The second output ("y:0") will be backed by GPU memory.
 FEEDS:
 It is the responsibility of the caller to ensure that the memory of the fed
 tensors will be correctly initialized and synchronized before it is
 accessed by operations executed during the call to Session::RunCallable().
 This is typically ensured by using the TensorFlow memory allocators
 (Device::GetAllocator()) to create the Tensor to be fed.
 Alternatively, for CUDA-enabled GPU devices, this typically means that the
 operation that produced the contents of the tensor has completed, i.e., the
 CUDA stream has been synchronized (e.g., via cuCtxSynchronize() or
 cuStreamSynchronize()).
 

map<string, string> feed_devices = 6;

getFetchDevicesCount

int getFetchDevicesCount()

map<string, string> fetch_devices = 7;

containsFetchDevices

boolean containsFetchDevices(java.lang.String key)

map<string, string> fetch_devices = 7;

getFetchDevices

@Deprecated
java.util.Map<java.lang.String,java.lang.String> getFetchDevices()

Deprecated.

Use getFetchDevicesMap() instead.

getFetchDevicesMap

java.util.Map<java.lang.String,java.lang.String> getFetchDevicesMap()

map<string, string> fetch_devices = 7;

getFetchDevicesOrDefault

java.lang.String getFetchDevicesOrDefault(java.lang.String key,
                                          java.lang.String defaultValue)

map<string, string> fetch_devices = 7;

getFetchDevicesOrThrow

java.lang.String getFetchDevicesOrThrow(java.lang.String key)

map<string, string> fetch_devices = 7;

getFetchSkipSync

boolean getFetchSkipSync()

 By default, RunCallable() will synchronize the GPU stream before returning
 fetched tensors on a GPU device, to ensure that the values in those tensors
 have been produced. This simplifies interacting with the tensors, but
 potentially incurs a performance hit.
 If this options is set to true, the caller is responsible for ensuring
 that the values in the fetched tensors have been produced before they are
 used. The caller can do this by invoking `Device::Sync()` on the underlying
 device(s), or by feeding the tensors back to the same Session using
 `feed_devices` with the same corresponding device name.
 

bool fetch_skip_sync = 8;

Returns:

The fetchSkipSync.