@Namespace(value="tensorflow::ops") @NoOffset public static class tensorflow.QueueDequeueUpTo extends Pointer
n tuples of one or more tensors from the given queue.
This operation is not supported by all queues. If a queue does not support
DequeueUpTo, then an Unimplemented error is returned.
If the queue is closed and there are more than 0 but less than n
elements remaining, then instead of returning an OutOfRange error like
QueueDequeueMany, less than n elements are returned immediately. If
the queue is closed and there are 0 elements left in the queue, then
an OutOfRange error is returned just like in QueueDequeueMany.
Otherwise the behavior is identical to QueueDequeueMany:
This operation concatenates queue-element component tensors along the
0th dimension to make a single component tensor. All of the components
in the dequeued tuple will have size n in the 0th dimension.
This operation has k outputs, where k is the number of components in
the tuples stored in the given queue, and output i is the ith
component of the dequeued tuple.
Arguments:
* scope: A Scope object
* handle: The handle to a queue.
* n: The number of tuples to dequeue.
* component_types: The type of each component in a tuple.
Optional attributes (see Attrs):
* timeout_ms: If the queue has fewer than n elements, this operation
will block for up to timeout_ms milliseconds.
Note: This option is not supported yet.
Returns:
* OutputList: One or more tensors that were dequeued as a tuple.| Modifier and Type | Class and Description |
|---|---|
static class |
tensorflow.QueueDequeueUpTo.Attrs
Optional attribute setters for QueueDequeueUpTo
|
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator| Constructor and Description |
|---|
QueueDequeueUpTo(Pointer p)
Pointer cast constructor.
|
QueueDequeueUpTo(tensorflow.Scope scope,
tensorflow.Input handle,
tensorflow.Input n,
tensorflow.DataTypeVector component_types) |
QueueDequeueUpTo(tensorflow.Scope scope,
tensorflow.Input handle,
tensorflow.Input n,
tensorflow.DataTypeVector component_types,
tensorflow.QueueDequeueUpTo.Attrs attrs) |
| Modifier and Type | Method and Description |
|---|---|
tensorflow.OutputVector |
components() |
tensorflow.QueueDequeueUpTo |
components(tensorflow.OutputVector components) |
tensorflow.Output |
get(long index) |
tensorflow.Operation |
operation() |
tensorflow.QueueDequeueUpTo |
operation(tensorflow.Operation operation) |
static tensorflow.QueueDequeueUpTo.Attrs |
TimeoutMs(long x) |
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, zeropublic QueueDequeueUpTo(Pointer p)
Pointer.Pointer(Pointer).public QueueDequeueUpTo(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input handle, @ByVal tensorflow.Input n, @Cast(value="const tensorflow::DataTypeSlice*") @ByRef tensorflow.DataTypeVector component_types)
public QueueDequeueUpTo(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input handle, @ByVal tensorflow.Input n, @Cast(value="const tensorflow::DataTypeSlice*") @ByRef tensorflow.DataTypeVector component_types, @Const @ByRef tensorflow.QueueDequeueUpTo.Attrs attrs)
@ByVal @Name(value="operator []") public tensorflow.Output get(@Cast(value="size_t") long index)
@ByVal public static tensorflow.QueueDequeueUpTo.Attrs TimeoutMs(@Cast(value="tensorflow::int64") long x)
@ByRef public tensorflow.Operation operation()
public tensorflow.QueueDequeueUpTo operation(tensorflow.Operation operation)
@ByRef @Cast(value="tensorflow::OutputList*") public tensorflow.OutputVector components()
public tensorflow.QueueDequeueUpTo components(tensorflow.OutputVector components)
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