tensorflow::
ops::
Barrier
#include <data_flow_ops.h>
Defines a barrier that persists across different graph executions.
Summary
A barrier represents a key-value map, where each key is a string, and each value is a tuple of tensors.
At runtime, the barrier contains 'complete' and 'incomplete' elements. A complete element has defined tensors for all components of its value tuple, and may be accessed using BarrierTakeMany . An incomplete element has some undefined components in its value tuple, and may be updated using BarrierInsertMany .
Args:
- scope: A Scope object
- component_types: The type of each component in a value.
Optional attributes (see
Attrs
):
- shapes: The shape of each component in a value. Each shape must be 1 in the first dimension. The length of this attr must be the same as the length of component_types.
- capacity: The capacity of the barrier. The default capacity is MAX_INT32, which is the largest capacity of the underlying queue.
- container: If non-empty, this barrier is placed in the given container. Otherwise, a default container is used.
- shared_name: If non-empty, this barrier will be shared under the given name across multiple sessions.
Returns:
-
Output
: The handle to the barrier.
Constructors and Destructors |
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Barrier
(const ::
tensorflow::Scope
& scope, const DataTypeSlice & component_types)
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Barrier
(const ::
tensorflow::Scope
& scope, const DataTypeSlice & component_types, const
Barrier::Attrs
& attrs)
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Public attributes |
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handle
|
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operation
|
Public functions |
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node
() const
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::tensorflow::Node *
|
operator::tensorflow::Input
() const
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operator::tensorflow::Output
() const
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Public static functions |
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Capacity
(int64 x)
|
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Container
(StringPiece x)
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Shapes
(const gtl::ArraySlice< PartialTensorShape > & x)
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SharedName
(StringPiece x)
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Structs |
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tensorflow::
|
Optional attribute setters for Barrier . |
Public attributes
Public functions
Barrier
Barrier( const ::tensorflow::Scope & scope, const DataTypeSlice & component_types, const Barrier::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const