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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
namespace armnn
{
class TensorShape;
class ITensorHandle
{
public:
enum Type
{
Cpu,
CL,
Neon
};
virtual ~ITensorHandle(){}
/// Indicate to the memory manager that this resource is active.
/// This is used to compute overlapping lifetimes of resources.
virtual void Manage() = 0;
/// Indicate to the memory manager that this resource is no longer active.
/// This is used to compute overlapping lifetimes of resources.
virtual void Allocate() = 0;
/// Get the type backend associated with the tensor handle.
/// \return Type enum
virtual ITensorHandle::Type GetType() const = 0;
/// Get the parent tensor if this is a subtensor.
/// \return a pointer to the parent tensor. Otherwise nullptr if not a subtensor.
virtual ITensorHandle* GetParent() const = 0;
/// Map the tensor data for access.
/// \param blocking hint to block the calling thread until all other accesses are complete. (backend dependent)
/// \return pointer to the first element of the mapped data.
virtual const void* Map(bool blocking=true) const = 0;
/// Unmap the tensor data
virtual void Unmap() const = 0;
/// Map the tensor data for access. Must be paired with call to Unmap().
/// \param blocking hint to block the calling thread until all other accesses are complete. (backend dependent)
/// \return pointer to the first element of the mapped data.
void* Map(bool blocking=true)
{
return const_cast<void*>(static_cast<const ITensorHandle*>(this)->Map(blocking));
}
/// Unmap the tensor data that was previously mapped with call to Map().
void Unmap()
{
return static_cast<const ITensorHandle*>(this)->Unmap();
}
/// Get the strides for each dimension ordered from largest to smallest where
/// the smallest value is the same as the size of a single element in the tensor.
/// \return a TensorShape filled with the strides for each dimension
virtual TensorShape GetStrides() const = 0;
/// Get the number of elements for each dimension orderd from slowest iterating dimension
/// to fastest iterating dimension.
/// \return a TensorShape filled with the number of elements for each dimension.
virtual TensorShape GetShape() const = 0;
};
}
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