CallableOptionsOrBuilder

antarmuka publik CallableOptionsOrBuilder

Subkelas Tidak Langsung yang Diketahui CallableOptions , CallableOptions.Builder Opsi yang Dapat Dipanggil 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.

Metode Publik

boolean abstrak	berisiFeedDevices (kunci string) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
boolean abstrak	berisiFetchDevices (kunci string) map<string, string> fetch_devices = 7;
Tali abstrak	getFeed (indeks int) Tensors to be fed in the callable.
abstrak com.google.protobuf.ByteString	getFeedBytes (indeks int) Tensors to be fed in the callable.
abstrak ke dalam	dapatkan Jumlah Umpan () Tensors to be fed in the callable.
peta abstrak<String, String>	dapatkan Perangkat Umpan () Gunakan getFeedDevicesMap() sebagai gantinya.
abstrak ke dalam	dapatkanFeedDevicesCount () The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
peta abstrak<String, String>	dapatkan FeedDevicesMap () The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
Tali abstrak	getFeedDevicesOrDefault (kunci string, 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.
Tali abstrak	getFeedDevicesOrThrow (kunci string) The Tensor objects fed in the callable and fetched from the callable are expected to be backed by host (CPU) memory by default.
Daftar abstrak<String>	dapatkanDaftar Umpan () Tensors to be fed in the callable.
Tali abstrak	getFetch (indeks int) Fetches.
abstrak com.google.protobuf.ByteString	getFetchBytes (indeks int) Fetches.
abstrak ke dalam	dapatkanFetchCount () Fetches.
peta abstrak<String, String>	dapatkanFetchDevices () Gunakan getFetchDevicesMap() sebagai gantinya.
abstrak ke dalam	dapatkanFetchDevicesCount () map<string, string> fetch_devices = 7;
peta abstrak<String, String>	dapatkanFetchDevicesMap () map<string, string> fetch_devices = 7;
Tali abstrak	getFetchDevicesOrDefault (kunci string, String defaultValue) map<string, string> fetch_devices = 7;
Tali abstrak	getFetchDevicesOrThrow (kunci string) map<string, string> fetch_devices = 7;
Daftar abstrak<String>	dapatkanFetchList () Fetches.
boolean abstrak	dapatkanFetchSkipSync () 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 abstrak	dapatkan Opsi Jalankan () Options that will be applied to each run.
abstrak RunOptionsOrBuilder	dapatkanRunOptionsOrBuilder () Options that will be applied to each run.
Tali abstrak	getTarget (indeks int) Target Nodes.
abstrak com.google.protobuf.ByteString	getTargetBytes (indeks int) Target Nodes.
abstrak ke dalam	dapatkanTargetCount () Target Nodes.
Daftar abstrak<String>	dapatkanDaftar Target () Target Nodes.
TensorConnection abstrak	getTensorConnection (indeks int) Tensors to be connected in the callable.
abstrak ke dalam	dapatkanTensorConnectionCount () Tensors to be connected in the callable.
Daftar abstrak< TensorConnection >	dapatkanTensorConnectionList () Tensors to be connected in the callable.
abstrak TensorConnectionOrBuilder	getTensorConnectionOrBuilder (indeks int) Tensors to be connected in the callable.
Daftar abstrak<? memperluas TensorConnectionOrBuilder >	dapatkanTensorConnectionOrBuilderList () Tensors to be connected in the callable.
boolean abstrak	hasRunOptions () Options that will be applied to each run.

Metode Publik

boolean abstrak publik berisiFeedDevices (kunci String)

 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;

boolean abstrak publik berisiFetchDevices (kunci string)

map<string, string> fetch_devices = 7;

abstrak publik String getFeed (indeks int)

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

repeated string feed = 1;

abstrak publik com.google.protobuf.ByteString getFeedBytes (indeks int)

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

repeated string feed = 1;

abstrak publik int getFeedCount ()

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

repeated string feed = 1;

peta abstrak publik<String, String> getFeedDevices ()

Gunakan getFeedDevicesMap() sebagai gantinya.

abstrak publik 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;

Peta abstrak publik<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;

abstrak publik String getFeedDevicesOrDefault (kunci string, 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;

abstrak publik String getFeedDevicesOrThrow (kunci String)

 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;

Daftar abstrak publik<String> getFeedList ()

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

repeated string feed = 1;

abstrak publik String getFetch (int indeks)

 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;

abstrak publik com.google.protobuf.ByteString getFetchBytes (indeks 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;

abstrak publik 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;

peta abstrak publik<String, String> getFetchDevices ()

Gunakan getFetchDevicesMap() sebagai gantinya.

abstrak publik int getFetchDevicesCount ()

map<string, string> fetch_devices = 7;

peta abstrak publik<String, String> getFetchDevicesMap ()

map<string, string> fetch_devices = 7;

abstrak publik String getFetchDevicesOrDefault (kunci string, String defaultValue)

map<string, string> fetch_devices = 7;

abstrak publik String getFetchDevicesOrThrow (kunci String)

map<string, string> fetch_devices = 7;

Daftar abstrak publik<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;

boolean abstrak publik 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;

abstrak publik RunOptions getRunOptions ()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

abstrak publik RunOptionsOrBuilder getRunOptionsOrBuilder ()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;

abstrak publik String getTarget (int indeks)

 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;

abstrak publik com.google.protobuf.ByteString getTargetBytes (indeks 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;

abstrak publik 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;

Daftar abstrak publik<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;

abstrak publik TensorConnection getTensorConnection (indeks 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;

abstrak publik 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;

Daftar abstrak publik< 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;

abstrak publik TensorConnectionOrBuilder getTensorConnectionOrBuilder (int indeks)

 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;

Daftar abstrak publik<? memperluas 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;

boolean abstrak publik hasRunOptions ()

 Options that will be applied to each run.
 

.tensorflow.RunOptions run_options = 4;