org.bytedeco.javacpp

Class tensorflow.TensorArrayGrad

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.javacpp.tensorflow.TensorArrayGrad

All Implemented Interfaces:

AutoCloseable

Enclosing class:

tensorflow

@Namespace(value="tensorflow::ops")
 @NoOffset
public static class tensorflow.TensorArrayGrad
extends Pointer

Creates a TensorArray for storing the gradients of values in the given handle. If the given TensorArray gradient already exists, returns a reference to it. Locks the size of the original TensorArray by disabling its dynamic size flag. **A note about the input flow_in:** The handle flow_in forces the execution of the gradient lookup to occur only after certain other operations have occurred. For example, when the forward TensorArray is dynamically sized, writes to this TensorArray may resize the object. The gradient TensorArray is statically sized based on the size of the forward TensorArray when this operation executes. Furthermore, the size of the forward TensorArray is frozen by this call. As a result, the flow is used to ensure that the call to generate the gradient TensorArray only happens after all writes are executed. In the case of dynamically sized TensorArrays, gradient computation should only be performed on read operations that have themselves been chained via flow to occur only after all writes have executed. That way the final size of the forward TensorArray is known when this operation is called. **A note about the source attribute:** TensorArray gradient calls use an accumulator TensorArray object. If multiple gradients are calculated and run in the same session, the multiple gradient nodes may accidentally flow through the same accumulator TensorArray. This double counts and generally breaks the TensorArray gradient flow. The solution is to identify which gradient call this particular TensorArray gradient is being called in. This is performed by identifying a unique string (e.g. "gradients", "gradients_1", ...) from the input gradient Tensor's name. This string is used as a suffix when creating the TensorArray gradient object here (the attribute source). The attribute source is added as a suffix to the forward TensorArray's name when performing the creation / lookup, so that each separate gradient calculation gets its own TensorArray accumulator. Arguments: * scope: A Scope object * handle: The handle to the forward TensorArray. * flow_in: A float scalar that enforces proper chaining of operations. * source: The gradient source string, used to decide which gradient TensorArray to return. Returns: * Output grad_handle * Output flow_out

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
TensorArrayGrad(Pointer p) Pointer cast constructor.
TensorArrayGrad(tensorflow.Scope scope, tensorflow.Input handle, tensorflow.Input flow_in, BytePointer source)
TensorArrayGrad(tensorflow.Scope scope, tensorflow.Input handle, tensorflow.Input flow_in, String source)

Method Summary

Modifier and Type	Method and Description
tensorflow.Output	flow_out()
tensorflow.TensorArrayGrad	flow_out(tensorflow.Output flow_out)
tensorflow.Output	grad_handle()
tensorflow.TensorArrayGrad	grad_handle(tensorflow.Output grad_handle)
tensorflow.Operation	operation()
tensorflow.TensorArrayGrad	operation(tensorflow.Operation operation)

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

TensorArrayGrad

public TensorArrayGrad(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

TensorArrayGrad

public TensorArrayGrad(@Const @ByRef
                       tensorflow.Scope scope,
                       @ByVal
                       tensorflow.Input handle,
                       @ByVal
                       tensorflow.Input flow_in,
                       @tensorflow.StringPiece
                       BytePointer source)

TensorArrayGrad

public TensorArrayGrad(@Const @ByRef
                       tensorflow.Scope scope,
                       @ByVal
                       tensorflow.Input handle,
                       @ByVal
                       tensorflow.Input flow_in,
                       @tensorflow.StringPiece
                       String source)

Method Detail

operation

@ByRef
public tensorflow.Operation operation()

operation

public tensorflow.TensorArrayGrad operation(tensorflow.Operation operation)

grad_handle

@ByRef
public tensorflow.Output grad_handle()

grad_handle

public tensorflow.TensorArrayGrad grad_handle(tensorflow.Output grad_handle)

flow_out

@ByRef
public tensorflow.Output flow_out()

flow_out

public tensorflow.TensorArrayGrad flow_out(tensorflow.Output flow_out)