Port CLGEMMConvolutionLayer

Details:
port CLWeightsReshapeKernel to ClWeightsReshapeKernel
port CLGEMMConvolutionLayer to ClGemmConvolution

Resolves: COMPMID-4515

Change-Id: I7d5b4ec72db2742f6eb9f3ffc88f717c35b4f2a3
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5983
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 8 insertions, 201 deletions

diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
index e262409ee7..3075465ef7 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
@@ -24,160 +24,24 @@
 #ifndef ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H
 #define ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H
 
-#include "arm_compute/runtime/IFunction.h"
-
-#include "arm_compute/core/CL/CLKernelLibrary.h"
-#include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
-#include "arm_compute/runtime/CL/functions/CLGEMM.h"
-#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
+#include "arm_compute/runtime/CL/CLTypes.h"
+#include "arm_compute/runtime/IFunction.h"
 #include "arm_compute/runtime/IMemoryManager.h"
-#include "arm_compute/runtime/ITransformWeights.h"
 #include "arm_compute/runtime/IWeightsManager.h"
-#include "arm_compute/runtime/MemoryGroup.h"
 
 #include <memory>
 
 namespace arm_compute
 {
-class CLWeightsReshapeKernel;
+// Forward declarations
+class CLCompileContext;
 class ICLTensor;
-namespace opencl
-{
-namespace kernels
-{
-class ClIm2ColKernel;
-class ClCol2ImKernel;
-} // namespace kernels
-} // namespace opencl
-
-/** Function to reshape and transpose the weights. This function calls the following kernels:
- * -# @ref CLWeightsReshapeKernel
- */
-class CLConvolutionLayerReshapeWeights : public IFunction
-{
-public:
-    /** Constructor */
-    CLConvolutionLayerReshapeWeights();
-    /** Prevent instances of this class from being copied */
-    CLConvolutionLayerReshapeWeights(const CLConvolutionLayerReshapeWeights &) = delete;
-    /** Prevent instances of this class from being copied */
-    CLConvolutionLayerReshapeWeights &operator=(const CLConvolutionLayerReshapeWeights &) = delete;
-    /** Default move constructor */
-    CLConvolutionLayerReshapeWeights(CLConvolutionLayerReshapeWeights &&) = default;
-    /** Default move assignment operator */
-    CLConvolutionLayerReshapeWeights &operator=(CLConvolutionLayerReshapeWeights &&) = default;
-    /** Default destructor */
-    ~CLConvolutionLayerReshapeWeights();
-    /** 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: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/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]  num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
-     */
-    void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
-    /** Set the input and output tensors.
-     *
-     * @param[in]  compile_context The compile context to be used.
-     * @param[in]  weights         Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
-     *                             Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/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]  num_groups      (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
-     */
-    void configure(const CLCompileContext &compile_context, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
-    /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayerReshapeWeights
-     *
-     * @param[in] weights    Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
-     *                       Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/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[in] output     Destination tensor. Data types supported: Same as @p weights.
-     * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
-     *
-     * @return a status
-     */
-    static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups = 1);
-    // Inherited methods overridden:
-    void run() override;
-
-private:
-    std::unique_ptr<CLWeightsReshapeKernel> _weights_reshape_kernel;
-};
-
-namespace weights_transformations
-{
-/** Basic function to manage the reshape weights generated from @ref CLConvolutionLayerReshapeWeights */
-class CLConvolutionLayerReshapeWeightsTransform : public ITransformWeights
-{
-public:
-    /** Configures the @ref CLConvolutionLayerReshapeWeights function
-     *
-     * @param[in] input      Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32.
-     * @param[in] biases     Biases tensor. Data type supported: same as @p input, S32 if @p input is quantized.
-     * @param[in] num_groups Number of groups when performing a grouped convolution.
-     */
-    void configure(const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups)
-    {
-        configure(CLKernelLibrary::get().get_compile_context(), input, biases, num_groups);
-    }
-    /** Configures the @ref CLConvolutionLayerReshapeWeights function
-     *
-     * @param[in] compile_context The compile context to be used.
-     * @param[in] input           Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32.
-     * @param[in] biases          Biases tensor. Data type supported: same as @p input, S32 if @p input is quantized.
-     * @param[in] num_groups      Number of groups when performing a grouped convolution.
-     */
-    void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups)
-    {
-        _bias_bit   = (biases != nullptr) ? 1 : 0;
-        _num_groups = num_groups;
-        _func.configure(compile_context, input, biases, &_output, num_groups);
-    }
-
-    //Inherited method override
-    void run() override
-    {
-        _output.allocator()->allocate();
-        _func.run();
-        _reshape_run = true;
-    }
-
-    //Inherited method override
-    ICLTensor *get_weights() override
-    {
-        return &_output;
-    }
-
-    //Inherited method override
-    void release() override
-    {
-        _output.allocator()->free();
-    }
-
-    //Inherited method override
-    uint32_t uid() override
-    {
-        return ((0x9) | (_bias_bit << 7) | (_num_groups << 8));
-    }
-
-private:
-    CLTensor                         _output{};
-    CLConvolutionLayerReshapeWeights _func{};
-    int32_t                          _bias_bit{ 0 };
-    unsigned int                     _num_groups{ 0 };
-};
-} // namespace weights_transformations
+class ITensorInfo;
 
 /** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
  *
- * -# @ref opencl::kernels::ClIm2ColKernel
- * -# @ref CLGEMM (if the data type is FP32 or FP16)
- * -# @ref CLGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED)
- * -# @ref CLGEMMLowpOutputStage with QUANTIZE_DOWN_FIXEDPOINT type of quantization (if the data type is QASYMM8/QASYMM8_SIGNED)
- * -# @ref opencl::kernels::ClCol2ImKernel (if NCHW data layout)
+ * -# @ref opencl::ClGemmConvolution
  */
 class CLGEMMConvolutionLayer : public IFunction
 {
@@ -282,65 +146,8 @@ public:
     void prepare() override;
 
 private:
-    /** Configures the appropriate matrix multiply routine
-     *
-     * @param[in]      compile_context       The compile context to be used.
-     * @param[in]      input                 Input tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
-     * @param[in]      weights               Weights tensor. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or
-     *                                       QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
-     * @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 quantized type where biases should be of S32 type.
-     * @param[in, out] output                Output tensor. Data types supported: same as @p input.
-     * @param[in]      gemmlowp_output_stage GEMMLowp output stage info
-     * @param[in]      gemm_3d_depth         Depth of GEMM 3D
-     * @param[in]      act_info              Activation to apply after the matrix multiplication
-     */
-    void configure_mm(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
-                      const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
-                      int gemm_3d_depth, const ActivationLayerInfo &act_info);
-    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines
-     *
-     * @param[in] input                 Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
-     * @param[in] weights               Weights tensor info. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or
-     *                                  QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED.
-     * @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 quantized type where biases should be of S32 type.
-     * @param[in] output                Output tensor info. Data types supported: same as @p input.
-     * @param[in] gemmlowp_output_stage GEMMLowp output stage info
-     * @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.
-     * @param[in] act_info              Activation to apply after the matrix multiplication
-     *
-     * @return a status
-     */
-    static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage,
-                              int gemm_3d_depth, bool skip_im2col, const ActivationLayerInfo &act_info);
-
-private:
-    MemoryGroup                                                        _memory_group;
-    IWeightsManager                                                   *_weights_manager;
-    CLConvolutionLayerReshapeWeights                                   _reshape_weights;
-    weights_transformations::CLConvolutionLayerReshapeWeightsTransform _reshape_weights_managed;
-    std::unique_ptr<opencl::kernels::ClIm2ColKernel>                   _im2col_kernel;
-    CLGEMM                                                             _mm_gemm;
-    CLGEMMLowpMatrixMultiplyCore                                       _mm_gemmlowp;
-    std::unique_ptr<opencl::kernels::ClCol2ImKernel>                   _col2im_kernel;
-    CLActivationLayer                                                  _activationlayer_function;
-
-    const ICLTensor *_original_weights;
-    const ICLTensor *_input;
-    const ICLTensor *_gemm_output_to_use;
-    ICLTensor       *_output;
-
-    CLTensor _im2col_output;
-    CLTensor _weights_reshaped;
-    CLTensor _gemm_output;
-
-    bool _skip_im2col;
-    bool _skip_col2im;
-    bool _is_quantized;
-    bool _fuse_activation;
-    bool _is_prepared;
+    struct Impl;
+    std::unique_ptr<Impl> _impl;
 };
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H */