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;
общедоступная абстрактная Map<String, String> getFetchDevices ()
Вместо этого используйте getFetchDevicesMap()
.
общедоступный абстрактный int getFetchDevicesCount ()
map<string, string> fetch_devices = 7;
общедоступная 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;