CallableOptionsOrBuilder

ממשק ציבורי CallableOptionsOrBuilder
תת-מחלקות עקיפות ידועות

שיטות ציבוריות

בוליאני מופשט
containsFeedDevices (מפתח מחרוזת) 
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
בוליאני מופשט
containsFetchDevices (מפתח מחרוזת)
map<string, string> fetch_devices = 7;
מחרוזת מופשטת
getFeed (int index) 
 Tensors to be fed in the callable.
תקציר com.google.protobuf.ByteString
getFeedBytes (int index) 
 Tensors to be fed in the callable.
מופשט int
getFeedCount () 
 Tensors to be fed in the callable.
מפה מופשטת<String, String>
getFeedDevices ()
השתמש ב- getFeedDevicesMap() במקום זאת.
מופשט 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.
מפה מופשטת<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.
מחרוזת מופשטת
getFeedDevicesOrDefault (מפתח מחרוזת, מחרוזת defaultValue) 
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
מחרוזת מופשטת
getFeedDevicesOrThrow (מפתח מחרוזת) 
 The Tensor objects fed in the callable and fetched from the callable
 are expected to be backed by host (CPU) memory by default.
רשימה מופשטת<String>
getFeedList () 
 Tensors to be fed in the callable.
מחרוזת מופשטת
getFetch (int index) 
 Fetches.
תקציר com.google.protobuf.ByteString
getFetchBytes (int index) 
 Fetches.
מופשט int
getFetchCount () 
 Fetches.
מפה מופשטת<String, String>
getFetchDevices ()
השתמש ב- getFetchDevicesMap() במקום זאת.
מופשט int
getFetchDevicesCount ()
map<string, string> fetch_devices = 7;
מפה מופשטת<String, String>
getFetchDevicesMap ()
map<string, string> fetch_devices = 7;
מחרוזת מופשטת
getFetchDevicesOrDefault (מפתח מחרוזת, מחרוזת defaultValue)
map<string, string> fetch_devices = 7;
מחרוזת מופשטת
getFetchDevicesOrThrow (מפתח מחרוזת)
map<string, string> fetch_devices = 7;
רשימה מופשטת<String>
getFetchList () 
 Fetches.
בוליאני מופשט
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.
תקציר RunOptions
getRunOptions () 
 Options that will be applied to each run.
תקציר RunOptionsOrBuilder
getRunOptionsOrBuilder () 
 Options that will be applied to each run.
מחרוזת מופשטת
getTarget (אינדקס int) 
 Target Nodes.
תקציר com.google.protobuf.ByteString
getTargetBytes (int index) 
 Target Nodes.
מופשט int
getTargetCount () 
 Target Nodes.
רשימה מופשטת<String>
getTargetList () 
 Target Nodes.
מופשט TensorConnection
getTensorConnection (int index) 
 Tensors to be connected in the callable.
מופשט int
getTensorConnectionCount () 
 Tensors to be connected in the callable.
רשימה מופשטת< TensorConnection >
getTensorConnectionList () 
 Tensors to be connected in the callable.
תקציר TensorConnectionOrBuilder
getTensorConnectionOrBuilder (int index) 
 Tensors to be connected in the callable.
רשימה מופשטת<? מרחיב את TensorConnectionOrBuilder >
getTensorConnectionOrBuilderList () 
 Tensors to be connected in the callable.
בוליאני מופשט
hasRunOptions () 
 Options that will be applied to each run.

שיטות ציבוריות

תקציר ציבורי בוליאני מכילFeedDevices (מפתח מחרוזת) 

 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;

תקציר ציבורי בוליאני מכילFetchDevices (מפתח מחרוזת)

map<string, string> fetch_devices = 7;

מחרוזת תקציר ציבורית getFeed (int index) 

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

תקציר ציבורי com.google.protobuf.ByteString getFeedBytes (int index) 

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

תקציר ציבורי int getFeedCount () 

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

תקציר ציבורי מפה<String, String> getFeedDevices ()

השתמש ב- getFeedDevicesMap() במקום זאת.

תקציר ציבורי 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;

תקציר ציבורי מפה<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;

תקציר ציבורי מחרוזת getFeedDevicesOrDefault (מפתח מחרוזת, מחרוזת 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;

מחרוזת תקציר ציבורית getFeedDevicesOrThrow (מפתח מחרוזת) 

 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;

רשימת תקציר ציבורית<String> getFeedList () 

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

תקציר ציבורי מחרוזת getFetch (אינדקס 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;

תקציר ציבורי com.google.protobuf.ByteString getFetchBytes (int index) 

 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;

תקציר ציבורי 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;

תקציר ציבורי מפה<String, String> getFetchDevices ()

השתמש ב- getFetchDevicesMap() במקום זאת.

תקציר ציבורי int getFetchDevicesCount ()

map<string, string> fetch_devices = 7;

תקציר ציבורי מפה<String, String> getFetchDevicesMap ()

map<string, string> fetch_devices = 7;

תקציר ציבורי מחרוזת getFetchDevicesOrDefault (מפתח מחרוזת, מחרוזת defaultValue)

map<string, string> fetch_devices = 7;

מחרוזת תקציר ציבורי getFetchDevicesOrThrow (מפתח מחרוזת)

map<string, string> fetch_devices = 7;

רשימת תקציר ציבורית<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;

תקציר בוליאני ציבורי 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;

תקציר ציבורי RunOptions getRunOptions () 

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

תקציר ציבורי RunOptionsOrBuilder getRunOptionsOrBuilder () 

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

String public abstract getTarget (int index) 

 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;

תקציר ציבורי com.google.protobuf.ByteString getTargetBytes (int index) 

 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;

תקציר ציבורי 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;

רשימת תקציר ציבורית<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;

תקציר ציבורי TensorConnection getTensorConnection (int index) 

 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;

תקציר ציבורי 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;

רשימת תקציר ציבורית< 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;

תקציר ציבורי TensorConnectionOrBuilder getTensorConnectionOrBuilder (int index) 

 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;

רשימת תקציר ציבורית<? מרחיב את 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;

תקציר ציבורי בוליאני hasRunOptions () 

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