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/*
* Copyright (c) 2022-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ARM_COMPUTE_CLINDIRECTCONVOLUTIONLAYER_H
#define ARM_COMPUTE_CLINDIRECTCONVOLUTIONLAYER_H
#include "arm_compute/core/Types.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
namespace arm_compute
{
class CLCompileContext;
class ICLTensor;
class ITensorInfo;
/** Basic function to run the indirect convolution function
*/
class CLIndirectConvolutionLayer : public IFunction
{
public:
/** Constructor */
CLIndirectConvolutionLayer();
/** Destructor */
~CLIndirectConvolutionLayer();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLIndirectConvolutionLayer(const CLIndirectConvolutionLayer &) = delete;
/** Default move constructor */
CLIndirectConvolutionLayer(CLIndirectConvolutionLayer &&);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLIndirectConvolutionLayer &operator=(const CLIndirectConvolutionLayer &) = delete;
/** Default move assignment operator */
CLIndirectConvolutionLayer &operator=(CLIndirectConvolutionLayer &&);
/** Set the input and output tensors.
*
* Valid data layouts:
* - NHWC
*
* Valid data type configurations:
* |src0 |src1 |src2 |dst |
* |:--------------|:--------------|:------|:--------------|
* |F16 |F16 |F16 |F16 |
* |F32 |F32 |F32 |F32 |
*
* @param[in] input Source tensor. 3 lower dimensions represent a single input,
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor. Data type supported:Same as @p input.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output, while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(ICLTensor *input,
const ICLTensor *weights,
const ICLTensor *biases,
ICLTensor *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Set the input and output tensors.
*
* @param[in] compile_context The compile context to be used.
* @param[in] input Source tensor. 3 lower dimensions represent a single input,
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions. Data type supported:Same as @p input.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output, while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(const CLCompileContext &compile_context,
ICLTensor *input,
const ICLTensor *weights,
const ICLTensor *biases,
ICLTensor *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLIndirectConvolutionLayer
*
* @param[in] input Source tensor. 3 lower dimensions represent a single input,
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions. Data type supported:Same as @p input.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type.
* @param[in] output Destination tensor. 3 lower dimensions represent a single output, while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *biases,
const ITensorInfo *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run() override;
private:
struct Impl;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLINDIRECTCONVOLUTIONLAYER_H */
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