Port NEGEMMConvolutionLayer
Details:
port NEWeightsReshapeKernel to CpuWeightsReshapeKernel
port NEGEMMConvolutionLayer to CpuGEMMConvolutionLayer
Resolves: COMPMID-4509
Change-Id: I3c7051e2c3f6d808a7ccb898aad70e5b221b9dc3
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5938
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
index e3b7d91..2ebb80b 100644
--- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
@@ -27,143 +27,21 @@
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/IFunction.h"
+#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/IWeightsManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
-#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
-#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h"
-#include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h"
-#include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h"
-#include "arm_compute/runtime/Tensor.h"
#include <memory>
namespace arm_compute
{
class ITensor;
-class NEWeightsReshapeKernel;
-namespace cpu
-{
-namespace kernels
-{
-class CpuIm2ColKernel;
-class CpuCol2ImKernel;
-} // namespace kernels
-} // namespace cpu
-
-/** Function to reshape the weights. This function calls the following kernel:
- * -# @ref NEWeightsReshapeKernel
- */
-class NEConvolutionLayerReshapeWeights : public IFunction
-{
-public:
- /** Constructor */
- NEConvolutionLayerReshapeWeights() noexcept;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEConvolutionLayerReshapeWeights(const NEConvolutionLayerReshapeWeights &) = delete;
- /** Prevent instances of this class from being moved (As this class contains non movable objects) */
- NEConvolutionLayerReshapeWeights(NEConvolutionLayerReshapeWeights &&) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEConvolutionLayerReshapeWeights &operator=(const NEConvolutionLayerReshapeWeights &) = delete;
- /** Prevent instances of this class from being moved (As this class contains non movable objects) */
- NEConvolutionLayerReshapeWeights &operator=(NEConvolutionLayerReshapeWeights &&) = delete;
- /** Default destructor */
- ~NEConvolutionLayerReshapeWeights();
- /** 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: All.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
- * Data type supported: same as @p weights.
- * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
- * @param[out] output Destination tensor. Data types supported: same as @p weights.
- */
- void configure(const ITensor *weights, const ITensor *biases, ITensor *output);
- /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights
- *
- * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
- * Data type supported: All.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
- * Data type supported: same as @p weights.
- * @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
- * @param[in] output Destination tensor. Data types supported: same as @p weights.
- *
- * @return an error status
- */
- static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output);
-
- // Inherited methods overridden:
- void run() override;
-
-private:
- std::unique_ptr<NEWeightsReshapeKernel> _weights_reshape_kernel;
-};
-
-namespace weights_transformations
-{
-/** Basic function to manage the reshape weights generated from @ref NEConvolutionLayerReshapeWeights */
-class NEConvolutionLayerReshapeWeightsTransform : public ITransformWeights
-{
-public:
- /** Constructor */
- NEConvolutionLayerReshapeWeightsTransform() = default;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEConvolutionLayerReshapeWeightsTransform(const NEConvolutionLayerReshapeWeightsTransform &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEConvolutionLayerReshapeWeightsTransform &operator=(const NEConvolutionLayerReshapeWeightsTransform &) = delete;
- /** Prevent instances of this class from being moved (As this class contains non movable objects) */
- NEConvolutionLayerReshapeWeightsTransform(NEConvolutionLayerReshapeWeightsTransform &&) = delete;
- /** Prevent instances of this class from being moved (As this class contains non movable objects) */
- NEConvolutionLayerReshapeWeightsTransform &operator=(NEConvolutionLayerReshapeWeightsTransform &&) = delete;
- /** Default destructor */
- ~NEConvolutionLayerReshapeWeightsTransform() = default;
- void configure(const ITensor *input, const ITensor *biases)
- {
- _bias_bit = (biases != nullptr) ? 1 : 0;
- _func.configure(input, biases, &_output);
- }
-
- void run() override
- {
- _output.allocator()->allocate();
- _func.run();
- _reshape_run = true;
- }
-
- ITensor *get_weights() override
- {
- return &_output;
- }
-
- void release() override
- {
- _output.allocator()->free();
- }
-
- uint32_t uid() override
- {
- return ((0x8) | (_bias_bit << 7));
- }
-
- bool is_reshape_run()
- {
- return _reshape_run;
- }
-
-private:
- Tensor _output{};
- NEConvolutionLayerReshapeWeights _func{};
- int32_t _bias_bit{ 0 };
-};
-} // namespace weights_transformations
+class ITensorInfo;
/** Basic function to compute the convolution layer. This function calls the following kernels/functions:
*
- * -# @ref cpu::kernels::CpuIm2ColKernel
- * -# @ref NEGEMM (if the data type is BFLOAT16/FP16/FP32)
- * -# @ref NEGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED)
- * -# @ref NEGEMMLowpOutputStage (if the data type is QASYMM8/QASYMM8_SIGNED)
- * -# @ref NEArithmeticAddition (if biases != nullptr and we have a 1x1 convolution with the NHWC data layout)
- * -# @ref cpu::kernels::CpuCol2ImKernel (if NCHW data layout)
+ * -# @ref cpu::CpuGemmConvolution
*
*/
class NEGEMMConvolutionLayer : public IFunction
@@ -244,73 +122,8 @@
void prepare() override;
private:
- /** Configures the appropriate matrix multiply routine
- *
- * @param[in] input Input tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
- * @param[in] weights Weights tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/BFLOAT16/F16/F32.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
- * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type.
- * @param[out] output Output tensor. Data types supported: Same as @p input,
- * except for input of QASYMM8/QASYMM8_SIGNED type where output should be of S32 type.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
- * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1)
- */
- void configure_mm(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo(), int gemm_3d_depth = 1);
- /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer matrix multiply routines
- *
- * @param[in] input Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
- * @param[in] weights Weights tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/BFLOAT16/F16/F32.
- * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
- * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type.
- * @param[in] output Output tensor info. Data types supported: Same as @p input,
- * except for input of QASYMM8/QASYMM8_SIGNED type where output should be of S32 type.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
- * @param[in] gemm_3d_depth (Optional) Depth of GEMM 3D (Defaults to 1)
- * @param[in] skip_im2col (Optional) Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. (Default to false)
- *
- * @return a status
- */
- static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const ActivationLayerInfo &act_info = ActivationLayerInfo(),
- int gemm_3d_depth = 1, bool skip_im2col = false);
- /** Static function to check if GEMM3D is supported in @ref NEGEMM or in @ref NEGEMMLowpMatrixMultiplyCore
- *
- * @param[in] input_info Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
- * @param[in] weights_info Weights tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/BFLOAT16/F16/F32.
- * @param[in] act_info Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
- * @param[in] gemm_3d_depth Depth of GEMM 3D
- * @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout
- *
- * @return a status
- */
- static Status validate_gemm3d(const ITensorInfo *input_info, const ITensorInfo *weights_info, const ActivationLayerInfo &act_info, int gemm_3d_depth, bool skip_im2col);
-
-private:
- MemoryGroup _memory_group;
- IWeightsManager *_weights_manager;
- NEConvolutionLayerReshapeWeights _reshape_weights;
- weights_transformations::NEConvolutionLayerReshapeWeightsTransform _reshape_weights_managed;
- std::unique_ptr<cpu::kernels::CpuIm2ColKernel> _im2col_kernel;
- NEGEMM _mm_gemm;
- NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- std::unique_ptr<cpu::kernels::CpuCol2ImKernel> _col2im_kernel;
- NEReshapeLayer _reshape_layer;
-
- const ITensor *_input;
- const ITensor *_original_weights;
- ITensor *_original_output;
-
- Tensor _im2col_output;
- Tensor _weights_reshaped;
- Tensor _gemm_output;
- Tensor _gemm_output_3d;
- Tensor _tmp_output;
-
- DataLayout _data_layout;
-
- bool _skip_im2col;
- bool _skip_col2im;
- bool _is_quantized;
- bool _is_prepared;
+ struct Impl;
+ std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
-#endif /* ARM_COMPUTE_NECONVOLUTIONGEMMLAYER_H */
+#endif /* ARM_COMPUTE_NEGEMMCONVOLUTIONLAYER_H */