CallableOptionsOrBuilder

общедоступный интерфейс CallableOptionsOrBuilder
Известные косвенные подклассы

Публичные методы

абстрактное логическое значение
содержитFeedDevices (строковый ключ)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
абстрактное логическое значение
содержитFetchDevices (строковый ключ)
map<string, string> fetch_devices = 7;
абстрактная строка
getFeed (целевой индекс)
 Tensors to be fed in the callable.
абстрактный com.google.protobuf.ByteString
getFeedBytes (целевой индекс)
 Tensors to be fed in the callable.
абстрактный int
getFeedCount ()
 Tensors to be fed in the callable.
абстрактная карта<String, String>
getFeedDevices ()
Вместо этого используйте getFeedDevicesMap() .
абстрактный 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.
абстрактная карта<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.
абстрактная строка
getFeedDevicesOrDefault (строковый ключ, строковое значение по умолчанию)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
абстрактная строка
getFeedDevicesOrThrow (строковый ключ)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
абстрактный список<String>
получитьфидлист ()
 Tensors to be fed in the callable.
абстрактная строка
getFetch (целочисленный индекс)
 Fetches.
абстрактный com.google.protobuf.ByteString
getFetchBytes (целочисленный индекс)
 Fetches.
абстрактный int
getFetchCount ()
 Fetches.
абстрактная карта<String, String>
getFetchDevices ()
Вместо этого используйте getFetchDevicesMap() .
абстрактный int
getFetchDevicesCount ()
map<string, string> fetch_devices = 7;
абстрактная карта<String, String>
getFetchDevicesMap ()
map<string, string> fetch_devices = 7;
абстрактная строка
getFetchDevicesOrDefault (строковый ключ, строковое значение по умолчанию)
map<string, string> fetch_devices = 7;
абстрактная строка
getFetchDevicesOrThrow (строковый ключ)
map<string, string> fetch_devices = 7;
абстрактный список<String>
getFetchList ()
 Fetches.
абстрактное логическое значение
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.
абстрактные параметры запуска
getRunOptions ()
 Options that will be applied to each run.
абстрактный RunOptionsOrBuilder
getRunOptionsOrBuilder ()
 Options that will be applied to each run.
абстрактная строка
getTarget (целевой индекс)
 Target Nodes.
абстрактный com.google.protobuf.ByteString
getTargetBytes (индекс целого числа)
 Target Nodes.
абстрактный int
getTargetCount ()
 Target Nodes.
абстрактный список<String>
getTargetList ()
 Target Nodes.
абстрактное TensorConnection
getTensorConnection (индекс целого числа)
 Tensors to be connected in the callable.
абстрактный int
getTensorConnectionCount ()
 Tensors to be connected in the callable.
абстрактный список <TensorConnection>
getTensorConnectionList ()
 Tensors to be connected in the callable.
абстрактный TensorConnectionOrBuilder
getTensorConnectionOrBuilder (индекс int)
 Tensors to be connected in the callable.
абстрактный список<? расширяет TensorConnectionOrBuilder >
getTensorConnectionOrBuilderList ()
 Tensors to be connected in the callable.
абстрактное логическое значение
имеетRunOptions ()
 Options that will be applied to each run.

Публичные методы

общедоступное абстрактное логическое значение containsFeedDevices (строковый ключ) 

 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;

общедоступное абстрактное логическое значение containsFetchDevices (строковый ключ)

map<string, string> fetch_devices = 7;

общедоступная абстрактная строка getFeed (индекс int) 

 Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;

общедоступный абстрактный com.google.protobuf.ByteString getFeedBytes (индекс int) 

 Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;

публичный абстрактный int getFeedCount () 

 Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;

общедоступная абстрактная Map<String, String> getFeedDevices ()

Вместо этого используйте getFeedDevicesMap() .

общедоступный абстрактный 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;

общедоступная абстрактная 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;

общедоступная абстрактная строка getFeedDevicesOrDefault (ключ 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;

общедоступная абстрактная строка getFeedDevicesOrThrow (строковый ключ) 

 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;

общедоступный абстрактный список <String> getFeedList () 

 Tensors to be fed in the callable. Each feed is the name of a tensor.
repeated string feed = 1;

общедоступная абстрактная строка getFetch (индекс 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;

общедоступный абстрактный com.google.protobuf.ByteString getFetchBytes (индекс 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;

публичный абстрактный 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;

публичная абстрактная Map<String, String> getFetchDevices ()

Вместо этого используйте getFetchDevicesMap() .

общедоступный абстрактный int getFetchDevicesCount ()

map<string, string> fetch_devices = 7;

публичная абстрактная Map<String, String> getFetchDevicesMap ()

map<string, string> fetch_devices = 7;

общедоступная абстрактная строка getFetchDevicesOrDefault (строковый ключ, строковое значение по умолчанию)

map<string, string> fetch_devices = 7;

общедоступная абстрактная строка getFetchDevicesOrThrow (строковый ключ)

map<string, string> fetch_devices = 7;

общедоступный абстрактный список <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;

общедоступное абстрактное логическое значение 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;

публичный абстрактный RunOptions getRunOptions () 

 Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;

публичный абстрактный RunOptionsOrBuilder getRunOptionsOrBuilder () 

 Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;

общедоступная абстрактная строка getTarget (индекс 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;

общедоступный абстрактный com.google.protobuf.ByteString getTargetBytes (индекс 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;

публичный абстрактный 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;

общедоступный абстрактный список <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;

общедоступный абстрактный TensorConnection getTensorConnection (индекс 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;

публичный абстрактный 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;

общедоступный абстрактный список < 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;

общедоступный абстрактный TensorConnectionOrBuilder getTensorConnectionOrBuilder (индекс 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;

публичный абстрактный список<? расширяет 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;

общедоступное абстрактное логическое значение hasRunOptions () 

 Options that will be applied to each run.
.tensorflow.RunOptions run_options = 4;