public interface
CallableOptionsOrBuilder
Known Indirect Subclasses |
Public Methods
abstract boolean |
containsFeedDevices(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. |
abstract boolean |
containsFetchDevices(String key)
map<string, string> fetch_devices = 7;
|
abstract String |
getFeed(int index)
Tensors to be fed in the callable. |
abstract com.google.protobuf.ByteString |
getFeedBytes(int index)
Tensors to be fed in the callable. |
abstract int |
getFeedCount()
Tensors to be fed in the callable. |
abstract Map<String, String> |
getFeedDevices()
Use
getFeedDevicesMap() instead. |
abstract 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. |
abstract Map<String, 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. |
abstract String |
getFeedDevicesOrDefault(String key, 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. |
abstract String |
getFeedDevicesOrThrow(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. |
abstract List<String> |
getFeedList()
Tensors to be fed in the callable. |
abstract String |
getFetch(int index)
Fetches. |
abstract com.google.protobuf.ByteString |
getFetchBytes(int index)
Fetches. |
abstract int |
getFetchCount()
Fetches. |
abstract Map<String, String> |
getFetchDevices()
Use
getFetchDevicesMap() instead. |
abstract int |
getFetchDevicesCount()
map<string, string> fetch_devices = 7;
|
abstract Map<String, String> |
getFetchDevicesMap()
map<string, string> fetch_devices = 7;
|
abstract String |
getFetchDevicesOrDefault(String key, String defaultValue)
map<string, string> fetch_devices = 7;
|
abstract String |
getFetchDevicesOrThrow(String key)
map<string, string> fetch_devices = 7;
|
abstract List<String> |
getFetchList()
Fetches. |
abstract 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. |
abstract RunOptions |
getRunOptions()
Options that will be applied to each run. |
abstract RunOptionsOrBuilder |
getRunOptionsOrBuilder()
Options that will be applied to each run. |
abstract String |
getTarget(int index)
Target Nodes. |
abstract com.google.protobuf.ByteString |
getTargetBytes(int index)
Target Nodes. |
abstract int |
getTargetCount()
Target Nodes. |
abstract List<String> |
getTargetList()
Target Nodes. |
abstract TensorConnection |
getTensorConnection(int index)
Tensors to be connected in the callable. |
abstract int |
getTensorConnectionCount()
Tensors to be connected in the callable. |
abstract List<TensorConnection> |
getTensorConnectionList()
Tensors to be connected in the callable. |
abstract TensorConnectionOrBuilder |
getTensorConnectionOrBuilder(int index)
Tensors to be connected in the callable. |
abstract List<? extends TensorConnectionOrBuilder> |
getTensorConnectionOrBuilderList()
Tensors to be connected in the callable. |
abstract boolean |
hasRunOptions()
Options that will be applied to each run. |
Public Methods
public abstract boolean containsFeedDevices (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;
public abstract boolean containsFetchDevices (String key)
map<string, string> fetch_devices = 7;
public abstract String getFeed (int index)
Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;
public abstract 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;
public abstract int getFeedCount ()
Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;
public abstract 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;
public abstract Map<String, 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;
public abstract String getFeedDevicesOrDefault (String key, 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;
public abstract String getFeedDevicesOrThrow (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;
public abstract List<String> getFeedList ()
Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;
public abstract 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;
public abstract 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;
public abstract 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;
public abstract int getFetchDevicesCount ()
map<string, string> fetch_devices = 7;
public abstract Map<String, String> getFetchDevicesMap ()
map<string, string> fetch_devices = 7;
public abstract String getFetchDevicesOrDefault (String key, String defaultValue)
map<string, string> fetch_devices = 7;
public abstract String getFetchDevicesOrThrow (String key)
map<string, string> fetch_devices = 7;
public abstract List<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;
public abstract 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;
public abstract RunOptions getRunOptions ()
Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;
public abstract RunOptionsOrBuilder getRunOptionsOrBuilder ()
Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;
public abstract 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;
public abstract 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;
public abstract 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;
public abstract List<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;
public abstract 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;
public abstract 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;
public abstract 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;
public abstract 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;
public abstract 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;
public abstract boolean hasRunOptions ()
Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;