COMPMID-1112: Enabled multithreading transforms in Winograd.

Updated RSH code as well.

Change-Id: I9452ff5c7f0ff0cd60b8c223cdd71077288eb0c1
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/130177
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 34 insertions, 76 deletions

diff --git a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp
index dd67e97035..bc067fd07a 100644
--- a/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp
+++ b/arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp
@@ -31,6 +31,7 @@
 #include "arm_compute/core/NEON/kernels/convolution/common/tensor.hpp"
 #include "arm_compute/core/NEON/kernels/convolution/common/utils.hpp"
 
+
 #include <thread>
 #include <utility>
 #include <vector>
@@ -135,15 +136,21 @@ class WinogradGEMM
 
       /** Apply the transform to a tensor. */
       static void execute(
-          const T *inptr,
-          const Tensor4DShape& input_shape,
-          const PaddingType padding_type,
+          const T* const input,        /** Input tensor data */
+          const int n_batches,         /** Number of batches in input tensor. */
+          const int in_batch_stride,   /** Stride between batches of the input. */
+          const int n_rows,            /** Number of rows in input tensor. */
+          const int in_row_stride,     /** Stride between rows of the input. */
+          const int n_cols,            /** Number of columns in input tensor. */
+          const int in_col_stride,     /** Stride between columns of the input. */
+          const int n_channels,        /** Number of channels in input tensor. */
+          const PaddingType padding,   /** Padding type. */
           const int tile_M,
           const int tile_N,
-          T *outptr_base,
-          const int matrix_stride,
-          const int matrix_batch_stride,
-          const int matrix_row_stride
+          T* const output,             /** Base of output matrices. */
+          const int matrix_stride,     /** Stride between output matrices. */
+          const int matrix_batch_stride,  /** Stride between batches within the matrix. */
+          const int matrix_row_stride  /** Stride within matrices. */
       );
 
       /***********************************************************************/
@@ -159,11 +166,15 @@ class WinogradGEMM
           const PaddingType padding,   /** Padding type. */
           T* const output,             /** Base of output matrices. */
           const int matrix_stride,     /** Stride between output matrices. */
-          const int matrix_row_stride  /** Stride within matrices. */
+          const int matrix_row_stride, /** Stride within matrices. */
+          const int in_batch_stride=0, /** Stride between input batches. */
+          const int in_row_stride=0,   /** Stride between input rows. */
+          const int in_col_stride=0    /** Stride between input columns. */
       );
 
-      /** Get the winodw of work a given operator can perform. */
+      /** Get the window of work a given operator can perform. */
       unsigned int get_window() const;
+      static constexpr unsigned int WINDOW_BLOCK = 16;  // Base size of window
 
       /** Perform work upon a window of the input. */
       void run(const unsigned int start, const unsigned int stop);
@@ -201,6 +212,7 @@ class WinogradGEMM
         T* const _outptr;
         const int _n_batches, _n_rows, _n_cols, _n_channels, _matrix_stride,
                   _matrix_row_stride, _tiles_M, _tiles_N;
+        const int _in_col_stride, _in_row_stride, _in_batch_stride;
         const PaddingType _padding_type;
     };
 
@@ -220,7 +232,13 @@ class WinogradGEMM
 
       /** Apply the transform to create a tensor. */
       static void execute(
-        const Tensor4DShape &output_shape,
+        const int n_batches,
+        const int out_batch_stride,
+        const int n_rows,
+        const int out_row_stride,
+        const int n_cols,
+        const int out_col_stride,
+        const int n_channels,
         const T* const matrix_base,
         const int matrix_stride,
         const int matrix_row_stride,
@@ -241,11 +259,15 @@ class WinogradGEMM
         const int n_batches,          /** Number of batches in output tensor. */
         const int n_rows,             /** Number of rows in output tensor. */
         const int n_cols,             /** Number of columns in output tensor. */
-        const int n_channels          /** Number of channels in output tensor. */
+        const int n_channels,         /** Number of channels in output tensor. */
+        const int out_batch_stride=0, /** Output batch stride. */
+        const int out_row_stride=0,   /** Output row stride. */
+        const int out_col_stride=0    /** Output column stride. */
       );
 
       /** Get the window of work a given operator can perform. */
       unsigned int get_window() const;
+      static constexpr unsigned int WINDOW_BLOCK = 16;  // Base size of window
 
       /** Perform work upon a window of the input. */
       void run(const unsigned int start, const unsigned int stop);
@@ -284,6 +306,7 @@ class WinogradGEMM
         const int _matrix_stride, _matrix_row_stride;
         T* const _outptr;
         const int _n_batches, _n_rows, _n_cols, _n_channels, _tile_M, _tile_N;
+        const int _out_col_stride, _out_row_stride, _out_batch_stride;
     };
 
     /** Perform a convolution.
@@ -296,54 +319,6 @@ class WinogradGEMM
         typedef TOut OutputType;
         typedef TIn InputType;
 
-        /** Create a new Winograd operator. */
-        Convolution(
-          const KernelShape &kernel_shape,
-          const Tensor4DShape &input_shape,
-          const PaddingType padding,
-          void *kernel_storage=NULL
-        );
-
-        Convolution(const Convolution&) = delete;
-        Convolution operator=(const Convolution&) = delete;
-
-        /** Create a new Winograd operator and initialise the weights. */
-        Convolution(
-          const KernelShape &kernel_shape,
-          const Tensor4DShape &input_shape,
-          const PaddingType padding,
-          const TIn* const kernel,
-          void *kernel_storage=NULL,
-          void *transform_working_space=NULL
-        );
-
-        /** Clean up a convolution engine. */
-        ~Convolution();
-
-        /** Transform the weights into the Winograd domain. */
-        template <typename WeightsTransform=WeightsTransform<TIn>>
-        void transform_weights(
-          const TIn* const kernel,
-          void *transform_working_space=NULL
-        );
-
-        /* Apply the Winograd operator to some input. */
-        void execute(
-          TOut* const output,
-          const TIn* const input,
-          const TOut* const biases,
-          void* working_space=NULL,
-          const int n_threads=1
-        );
-
-        /* Apply the Winograd operator to some input. */
-        void execute(
-          TOut* const output,
-          const TIn* const input,
-          const TOut* const biases,
-          const int n_threads
-        );
-
         /** Get the output shape of a convolution. */
         static Tensor4DShape get_output_shape(
           const KernelShape &kernel_shape,
@@ -421,23 +396,6 @@ class WinogradGEMM
 
         static constexpr int M_BLOCK = 4;   /** Size of block used by GEMM. */
         static constexpr int N_BLOCK = 16;  /** Size of block used by GEMM. */
-
-      private:
-        const KernelShape kernel_shape;  /** Shape of the kernel to be applied. */
-        TIn *kernel_matrices[N_GEMMS];   /** Pointers into the kernel matrices. */
-        const int kernel_matrix_row_stride;  /** Stride within the kernel matrices. */
-
-        const bool manage_kernel_storage;  /** Kernel storage is managed by the instance. */
-        void* const _kernel_storage;       /** Base pointer for kernel storage. */
-
-        const Tensor4DShape input_shape;  /** Shape of the input tensor. */
-        const PaddingType padding;        /** Padding applied by the operator. */
-
-        const Tensor4DShape output_shape;  /** Output shape produced by the operator. */
-
-        const int tile_rows;  /** Number of rows of tiles. */
-        const int tile_cols;  /** Number of columns of tiles. */
-        const int M, K, N;    /** Sizes of underlying fundamental matrix multiplications. */
     };
 };