COMPMID-845: Create a ConvolutionLayer for CL
Change-Id: Ifcc406d2d0a99c911d6b6c875657b0e0028255d5
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119148
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
index f6672ce..53d59c3 100644
--- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
@@ -26,71 +26,18 @@
#include "arm_compute/runtime/IFunction.h"
-#include "arm_compute/core/CL/kernels/CLCol2ImKernel.h"
-#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
-#include "arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h"
-#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
-#include "arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h"
-#include "arm_compute/core/CL/kernels/CLIm2ColKernel.h"
-#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLMemoryGroup.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/functions/CLGEMM.h"
-#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
-#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
+#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include <memory>
namespace arm_compute
{
-class ICLTensor;
-
-/** Function to reshape and transpose the weights. This function calls the following kernels:
- * -# @ref CLWeightsReshapeKernel
- * -# @ref CLGEMMTranspose1xWKernel
- */
-class CLConvolutionLayerReshapeWeights : public IFunction
-{
-public:
- /** Constructor */
- CLConvolutionLayerReshapeWeights(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
- /** Set the input and output tensors.
- *
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
- * Data type supported: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
- * @param[out] output Destination tensor. Data types supported: Same as @p weights.
- * @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise.
- * Data types supported: Same as @p weights.
- */
- void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose1xW);
- // Inherited methods overridden:
- void run() override;
-
-private:
- CLMemoryGroup _memory_group;
- CLWeightsReshapeKernel _weights_reshape_kernel;
- CLGEMMTranspose1xWKernel _weights_transposed_kernel;
- CLTensor _weights_reshaped;
- bool _transpose1xW;
-};
-
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
- * Note: weights already reshaped for quantized asymmetric is not supported
- *
- * -# @ref CLIm2ColKernel
- * -# @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
- * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale (if quantized asymmetric)
- * -# @ref CLCol2ImKernel
- *
- * if the weights are already reshaped:
- * -# @ref CLGEMMInterleave4x4Kernel
- * -# @ref CLGEMMMatrixMultiplyKernel
- * else
- * -# @ref CLGEMM
+ * -# @ref CLGEMMConvolutionLayer
+ * -# @ref CLDirectConvolutionLayer
*/
class CLConvolutionLayer : public IFunction
{
@@ -108,46 +55,49 @@
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], 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] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
- * tensor has also been transposed with CLGEMMTranspose1xWKernel. Data type supported: Same as @p input.
+ * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
*/
- void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo());
+ void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo());
+ /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayer
+ *
+ * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
+ * while every optional dimension from 4 and above represent a batch of inputs.
+ * Data types supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. 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:Same as @p input.
+ * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], 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] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info = WeightsInfo());
+ /** Static function to check if given info will return the convolution called by @ref CLConvolutionLayer
+ *
+ * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
+ * while every optional dimension from 4 and above represent a batch of inputs.
+ * Data types supported: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. 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:Same as @p input.
+ * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], 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] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
+ * @param[in] gpu_target Specifies the @p GPUTarget.
+ *
+ * @return a status
+ */
+ static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info, const GPUTarget gpu_target);
// Inherited methods overridden:
void run() override;
private:
- /** Configures the appropriate matrix multiply routine
- *
- * @param input Input tensor. Data types supported: QS8/QASYMM8/QS16/F16/F32.
- * @param weights Weights tensor. Data type supported: Same as @p input.
- * @param output Output tensor. Data types supported: Same as @p input,
- * except for input of QASYMM8 type where output should be of S32 type.
- * @param is_interleaved_transposed Flag that signals if matrix is interleaved transposed
- */
- void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool is_interleaved_transposed, bool are_weights_reshaped);
-
-private:
- CLMemoryGroup _memory_group;
- CLConvolutionLayerReshapeWeights _reshape_weights;
- CLIm2ColKernel _im2col_kernel;
- CLGEMMInterleave4x4Kernel _interleave_kernel;
- CLGEMMMatrixMultiplyKernel _mm_kernel;
- CLGEMM _mm_gemm;
- CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
- CLCol2ImKernel _col2im_kernel;
-
- CLTensor _im2col_output;
- CLTensor _interleave_output;
- CLTensor _weights_reshaped;
- CLTensor _weights_transposed;
- CLTensor _gemm_output;
- CLTensor _tmp_output;
-
- bool _are_weights_reshaped;
- bool _is_quantized;
- bool _is_interleaved_transposed;
+ std::shared_ptr<IMemoryManager> _memory_manager;
+ std::unique_ptr<IFunction> _function; /**< Function to run */
};
}
#endif /* __ARM_COMPUTE_CLCONVOLUTIONLAYER_H__ */