CallableOptionsOrBuilder

interfaz pública CallableOptionsOrBuilder

Subclases indirectas conocidas CallableOptions , CallableOptions.Builder CallableOptions Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed.  CallableOptions.Builder Defines a subgraph in another `GraphDef` as a set of feed points and nodes to be fetched or executed.

Métodos públicos

booleano abstracto	containsFeedDevices (clave de cadena) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
booleano abstracto	containsFetchDevices (clave de cadena) map<string, string> fetch_devices = 7;
cadena abstracta	getFeed (índice int) Tensors to be fed in the callable.
resumen com.google.protobuf.ByteString	getFeedBytes (índice int) Tensors to be fed in the callable.
int abstracto	getFeedCount () Tensors to be fed in the callable.
Mapa abstracto <Cadena, Cadena>	getFeedDevices () Utilice getFeedDevicesMap() lugar.
int abstracto	getFeedDevicesCount () The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
Mapa abstracto <Cadena, Cadena>	getFeedDevicesMap () The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
cadena abstracta	getFeedDevicesOrDefault (clave de cadena, valor predeterminado de cadena) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
cadena abstracta	getFeedDevicesOrThrow (clave de cadena) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
Lista abstracta <String>	getFeedList () Tensors to be fed in the callable.
cadena abstracta	getFetch (índice int) Fetches.
resumen com.google.protobuf.ByteString	getFetchBytes (índice int) Fetches.
int abstracto	getFetchCount () Fetches.
Mapa abstracto <Cadena, Cadena>	getFetchDevices () Utilice getFetchDevicesMap() lugar.
int abstracto	getFetchDevicesCount () map<string, string> fetch_devices = 7;
Mapa abstracto <Cadena, Cadena>	getFetchDevicesMap () map<string, string> fetch_devices = 7;
cadena abstracta	getFetchDevicesOrDefault (clave de cadena, valor predeterminado de cadena) map<string, string> fetch_devices = 7;
cadena abstracta	getFetchDevicesOrThrow (clave de cadena) map<string, string> fetch_devices = 7;
Lista abstracta <String>	getFetchList () Fetches.
booleano abstracto	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 abstractas	getRunOptions () Options that will be applied to each run.
resumen RunOptionsOrBuilder	getRunOptionsOrBuilder () Options that will be applied to each run.
cadena abstracta	getTarget (índice int) Target Nodes.
resumen com.google.protobuf.ByteString	getTargetBytes (índice int) Target Nodes.
int abstracto	getTargetCount () Target Nodes.
Lista abstracta <String>	getTargetList () Target Nodes.
TensorConnection abstracto	getTensorConnection (índice int) Tensors to be connected in the callable.
int abstracto	getTensorConnectionCount () Tensors to be connected in the callable.
Lista abstracta < TensorConnection >	getTensorConnectionList () Tensors to be connected in the callable.
TensorConnectionOrBuilder abstracto	getTensorConnectionOrBuilder (índice int) Tensors to be connected in the callable.
Resumen Lista <? extiende TensorConnectionOrBuilder >	getTensorConnectionOrBuilderList () Tensors to be connected in the callable.
booleano abstracto	hasRunOptions () Options that will be applied to each run.

Métodos públicos

public abstract boolean containsFeedDevices (clave de cadena)

 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 (clave de cadena)

map<string, string> fetch_devices = 7;

getFeed de cadena abstracta pública (índice int)

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

repeated string feed = 1;

resumen público com.google.protobuf.ByteString getFeedBytes (índice int)

 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;

Mapa abstracto público <String, String> getFeedDevices ()

Utilice getFeedDevicesMap() lugar.

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;

Mapa abstracto público <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 (clave de cadena, valor predeterminado de cadena)

 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 (clave de cadena)

 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;

Lista pública abstracta <String> getFeedList ()

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

repeated string feed = 1;

getFetch de cadena abstracta pública (índice int)

 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;

resumen público com.google.protobuf.ByteString getFetchBytes (índice int)

 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;

Mapa abstracto público <String, String> getFetchDevices ()

Utilice getFetchDevicesMap() lugar.

public abstract int getFetchDevicesCount ()

map<string, string> fetch_devices = 7;

Mapa abstracto público <String, String> getFetchDevicesMap ()

map<string, string> fetch_devices = 7;

public abstract String getFetchDevicesOrDefault (clave de cadena, valor predeterminado de cadena)

map<string, string> fetch_devices = 7;

público abstracto String getFetchDevicesOrThrow (clave de cadena)

map<string, string> fetch_devices = 7;

Lista pública abstracta <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;

getFetchSkipSync () booleano abstracto público

 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;

RunOptions abstractas públicas getRunOptions ()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

resumen público RunOptionsOrBuilder getRunOptionsOrBuilder ()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

getTarget de cadena abstracta pública (índice int)

 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;

resumen público com.google.protobuf.ByteString getTargetBytes (índice int)

 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;

Lista pública abstracta <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;

TensorConnection abstracto público getTensorConnection (índice int)

 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;

Lista pública abstracta < 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;

resumen público TensorConnectionOrBuilder getTensorConnectionOrBuilder (índice int)

 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;

Lista de resumen público <? extiende 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;

hasRunOptions () booleano abstracto público

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;