Basic function to run CLDeconvolutionLayerUpsampleKernel.
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#include <CLDeconvolutionLayerUpsample.h>
Prevent instances of this class from being copied (As this class contains pointers)
Allow instances of this class to be moved.
Initialize the function's source, destination, interpolation type and border_mode.
- Parameters
-
[in,out] | input | Source tensor. Data type supported: F32. |
[out] | output | Destination tensor. Data type supported: F32. |
[in] | inner_border | The number of zeros added to right and top edges of the input. |
[in] | info | Contains padding and policies to be used in the deconvolution. |
Prevent instances of this class from being copied (As this class contains pointers)
Allow instances of this class to be moved.
Run the kernels contained in the function.
For NEON kernels:
- Multi-threading is used for the kernels which are parallelisable.
- By default std::thread::hardware_concurrency() threads are used.
- Note
- CPPScheduler::set_num_threads() can be used to manually set the number of threads
For OpenCL kernels:
- All the kernels are enqueued on the queue associated with CLScheduler.
- The queue is then flushed.
- Note
- The function will not block until the kernels are executed. It is the user's responsibility to wait.
-
Will call prepare() on first run if hasn't been done
Implements IFunction.
Static function to check if given info will lead to a valid configuration of CLDeconvolutionLayerUpsample.
- Parameters
-
[in] | input | Source tensor info. Data type supported: F32. |
[in] | output | Destination tensor info. Data type supported: F32. |
[in] | inner_border | The number of zeros added to right and top edges of the input. |
[in] | info | Contains padding and policies to be used in the deconvolution. |
- Returns
- a status
The documentation for this class was generated from the following file: