CallableOptionsOrBuilder

パブリック インターフェイスCallableOptionsOrBuilder
既知の間接サブクラス

パブリックメソッド

抽象ブール値
containsFeedDevices (文字列キー)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
抽象ブール値
containsFetchDevices (文字列キー)
map<string, string> fetch_devices = 7;
抽象文字列
getFeed (int インデックス)
 Tensors to be fed in the callable.
抽象的な com.google.protobuf.ByteString
getFeedBytes (int インデックス)
 Tensors to be fed in the callable.
抽象整数
getFeedCount ()
 Tensors to be fed in the callable.
抽象マップ<String, String>
getFeedDevices ()
代わりにgetFeedDevicesMap()を使用してください。
抽象整数
getFeedDevicesCount ()
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
抽象マップ<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.
抽象文字列
getFeedDevicesOrDefault (文字列キー、文字列defaultValue)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
抽象文字列
getFeedDevicesOrThrow (文字列キー)
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
抽象リスト<String>
getFeedList ()
 Tensors to be fed in the callable.
抽象文字列
getFetch (int インデックス)
 Fetches.
抽象的な com.google.protobuf.ByteString
getFetchBytes (int インデックス)
 Fetches.
抽象整数
getFetchCount ()
 Fetches.
抽象マップ<String, String>
getFetchDevices ()
代わりにgetFetchDevicesMap()を使用してください。
抽象整数
getFetchDevicesCount ()
map<string, string> fetch_devices = 7;
抽象マップ<String, String>
getFetchDevicesMap ()
map<string, string> fetch_devices = 7;
抽象文字列
getFetchDevicesOrDefault (文字列キー、文字列defaultValue)
map<string, string> fetch_devices = 7;
抽象文字列
getFetchDevicesOrThrow (文字列キー)
map<string, string> fetch_devices = 7;
抽象リスト<String>
getFetchList ()
 Fetches.
抽象ブール値
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.
抽象的なRunOptions
getRunOptions ()
 Options that will be applied to each run.
抽象的なRunOptionsOrBuilder
getRunOptionsOrBuilder ()
 Options that will be applied to each run.
抽象文字列
getTarget (int インデックス)
 Target Nodes.
抽象的な com.google.protobuf.ByteString
getTargetBytes (int インデックス)
 Target Nodes.
抽象整数
getTargetCount ()
 Target Nodes.
抽象リスト<String>
getTargetList ()
 Target Nodes.
抽象TensorConnection
getTensorConnection (int インデックス)
 Tensors to be connected in the callable.
抽象整数
getTensorConnectionCount ()
 Tensors to be connected in the callable.
抽象リスト< TensorConnection >
getTensorConnectionList ()
 Tensors to be connected in the callable.
抽象TensorConnectionOrBuilder
getTensorConnectionOrBuilder (int インデックス)
 Tensors to be connected in the callable.
抽象リスト<? TensorConnectionOrBuilder を拡張 >
getTensorConnectionOrBuilderList ()
 Tensors to be connected in the callable.
抽象ブール値
hasRunOptions ()
 Options that will be applied to each run.

パブリックメソッド

public abstract boolean containsFeedDevices (文字列キー)

 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 (文字列キー)

map<string, string> fetch_devices = 7;

public abstract String getFeed (int インデックス)

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

パブリック抽象 com.google.protobuf.ByteString getFeedBytes (int インデックス)

 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 Map<String, String> getFeedDevices ()

代わりにgetFeedDevicesMap()を使用してください。

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 (文字列キー、文字列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 (文字列キー)

 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;

パブリック抽象 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 インデックス)

 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 インデックス)

 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 Map<String, String> getFetchDevices ()

代わりにgetFetchDevicesMap()を使用してください。

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 (文字列キー、文字列defaultValue)

map<string, string> fetch_devices = 7;

public abstract String getFetchDevicesOrThrow (文字列キー)

map<string, string> fetch_devices = 7;

パブリック抽象 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;

パブリック抽象RunOptions getRunOptions ()

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

パブリック抽象RunOptionsOrBuilder getRunOptionsOrBuilder ()

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

public abstract String getTarget (int インデックス)

 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 インデックス)

 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;

パブリック抽象TensorConnection getTensorConnection (int インデックス)

 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;

パブリック抽象TensorConnectionOrBuilder getTensorConnectionOrBuilder (int インデックス)

 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;

公開抄録リスト<? 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;