COMPMID-1357: Stop passing around raw pointers in NEWinogradConvolution
First step to allow us to enable the memory manager in this function
Change-Id: Ic42fdac4c74cd21973c71130b59883e4a87d3dca
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/140167
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-by: Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h b/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
index 68c133e..9cdd69a 100644
--- a/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
@@ -74,7 +74,7 @@
* @param[in] matrix_stride Stride between output matrices.
*/
virtual void configure(const ITensor *input_nhwc, const int num_batches, const int num_rows, const int num_cols, const int num_channels,
- const PaddingType padding, T *const output, const int matrix_stride) = 0;
+ const PaddingType padding, ITensor *output, const int matrix_stride) = 0;
/** Destructor */
virtual ~INEWinogradLayerTransformInputKernel()
@@ -152,7 +152,7 @@
const int num_cols,
const int num_channels,
const PaddingType padding,
- T *const output,
+ ITensor *output,
const int matrix_stride) override;
// Inherited methods overridden:
@@ -181,7 +181,7 @@
int _num_cols; /**< Number of columns in input tensor. */
int _num_channels; /**< Number of channels in input tensor. */
PaddingType _padding; /**< Padding type. */
- T *_output; /**< Base of output matrices. */
+ ITensor *_output; /**< Base of output matrices. */
int _matrix_stride; /**< Stride between output matrices. */
};
@@ -236,9 +236,9 @@
*/
virtual void configure(
const ITensor *biases,
- const T *const output_workingspace,
+ const ITensor *output_workingspace,
const int matrix_stride,
- ITensor *const output_nhwc,
+ ITensor *output_nhwc,
const int num_batches,
const int num_rows,
const int num_cols,
@@ -318,9 +318,9 @@
*/
void configure(
const ITensor *biases,
- const T *const output_workingspace,
+ const ITensor *output_workingspace,
const int matrix_stride,
- ITensor *const output_nhwc,
+ ITensor *output_nhwc,
const int num_batches,
const int num_rows,
const int num_cols,
@@ -345,7 +345,7 @@
using OutputTransform = typename WinogradBase::template OutputTransform<T>;
const ITensor *_biases;
- const T *_output_workspace;
+ const ITensor *_output_workspace;
int _matrix_stride;
int _matrix_row_stride;
ITensor *_output_nhwc;
@@ -379,14 +379,14 @@
/** Configure the weights transform kernel.
*
- * @param[in] weights_hwio Pointer to the weights tensor
- * @param[in] output Pointer to working space for the output tensor in the Winograd domain.
- * @param[in] matrix_stride Stride across matrices in the output workspace.
- * @param[in] num_output_channels Number of filters.
- * @param[in] num_input_channels Number of channels in each filter.
+ * @param[in] weights_hwio Pointer to the weights tensor
+ * @param[out] output Pointer to working space for the output tensor in the Winograd domain.
+ * @param[in] matrix_stride Stride across matrices in the output workspace.
+ * @param[in] num_output_channels Number of filters.
+ * @param[in] num_input_channels Number of channels in each filter.
*/
- virtual void configure(const ITensor *weights_hwio, T *const output, const int matrix_stride, const int num_output_channels, const int num_input_channels) = 0;
+ virtual void configure(const ITensor *weights_hwio, ITensor *output, const int matrix_stride, const int num_output_channels, const int num_input_channels) = 0;
virtual ~INEWinogradLayerTransformWeightsKernel()
{
@@ -428,7 +428,7 @@
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info);
// Inherited methods overridden:
- void configure(const ITensor *weights_hwio, T *const output, const int matrix_stride, const int num_output_channels, const int num_input_channels) override;
+ void configure(const ITensor *weights_hwio, ITensor *output, const int matrix_stride, const int num_output_channels, const int num_input_channels) override;
unsigned int get_weight_storage_size(int num_output_channels, int num_input_channels) const override;
int get_matrix_stride(const KernelShape &kernel_shape) const override;
void run(const Window &window, const ThreadInfo &info) override;
@@ -440,147 +440,26 @@
using WeightsTransform = typename WinogradBase::template WeightsTransform<T>;
const ITensor *_weights_hwio;
- T *_output;
+ ITensor *_output;
int _matrix_stride;
int _num_output_channels;
int _num_input_channels;
};
-/** Interface for the NEON kernel to perform Winograd. */
-template <typename TIn, typename TOut>
-class INEWinogradLayerBatchedGEMMKernel : public INEKernel
-{
-public:
- /** Get the number of GEMMs to compute
- */
- virtual unsigned int get_number_gemms() const = 0;
- /** Initialise the kernel
- *
- * @param[in] n_gemms Number of GEMMs to compute.
- * @param[in] M in_shape.num_batches * tile_rows * tile_cols.
- * @param[in] K Number of channels in the input tensor.
- * @param[in] N Number of channels in the output tensor.
- * @param[in] a_matrix_stride Stride between input matrices.
- * @param[in] a_row_stride Row stride inside input matrix.
- * @param[in] b_matrix_stride Stride between weights matrices.
- * @param[in] b_row_stride Row stride inside the weights matrix.
- * @param[in] c_matrix_stride Stride between output matrices.
- * @param[in] c_row_stride Row stride inside the output matrix.
- * @param[out] a_ptr Input workspace.
- * @param[out] b_ptr Kernel workspace.
- * @param[out] c_ptr Output workspace.
- */
- virtual void configure(
- const unsigned int n_gemms,
- const int M, const int K, const int N,
- const int a_matrix_stride,
- const int a_row_stride,
- const int b_matrix_stride,
- const int b_row_stride,
- const int c_matrix_stride,
- const int c_row_stride,
- const TIn *const a_ptr,
- const TIn *const b_ptr,
- TOut *const c_ptr) = 0;
-
- /** Get the number of tiles per row
- */
- virtual int get_output_tile_rows() const = 0;
- /** Get the number of tiles per columns
- */
- virtual int get_output_tile_cols() const = 0;
- /** Get the number of blocks
- */
- virtual int get_number_blocks() const = 0;
-};
-
/** NEON kernel to perform Winograd. */
template <typename TIn, typename TOut, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols>
-class NEWinogradLayerBatchedGEMMKernel : public INEWinogradLayerBatchedGEMMKernel<TIn, TOut>
+class NEWinogradLayerConfiguration
{
public:
/** Winograd base kernel */
using WinogradBase = winograd::WinogradGEMM<OutputTileRows, OutputTileCols, KernelRows, KernelCols>;
/** Winograd convolution kernel */
+
using WinogradConv = typename WinogradBase::template Convolution<TIn, TOut>;
- /** Winograd batched blocked GEMM operator */
- using MultiGEMM = winograd::BatchedBlockedGemm<WinogradConv::M_BLOCK, WinogradConv::N_BLOCK, TIn, TOut>;
- const char *name() const override
- {
- return "NEWinogradLayerBatchedGEMMKernel";
- }
- /** Constructor */
- NEWinogradLayerBatchedGEMMKernel();
-
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEWinogradLayerBatchedGEMMKernel(const NEWinogradLayerBatchedGEMMKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NEWinogradLayerBatchedGEMMKernel &operator=(const NEWinogradLayerBatchedGEMMKernel &) = delete;
- /** Allow instances of this class to be moved */
- NEWinogradLayerBatchedGEMMKernel(NEWinogradLayerBatchedGEMMKernel &&) = default;
- /** Allow instances of this class to be moved */
- NEWinogradLayerBatchedGEMMKernel &operator=(NEWinogradLayerBatchedGEMMKernel &&) = default;
- /** Default destructor. */
- ~NEWinogradLayerBatchedGEMMKernel() = default;
-
- // Inherited methods overridden:
-
- unsigned int get_number_gemms() const override;
- int get_output_tile_rows() const override;
- int get_output_tile_cols() const override;
- int get_number_blocks() const override;
-
- /** Initialise the kernel
- *
- * @param[in] n_gemms Number of GEMMs to compute.
- * @param[in] M in_shape.num_batches * tile_rows * tile_cols.
- * @param[in] K Number of channels in the input tensor.
- * @param[in] N Number of channels in the output tensor.
- * @param[in] a_matrix_stride Stride between input matrices.
- * @param[in] a_row_stride Row stride inside input matrix.
- * @param[in] b_matrix_stride Stride between weights matrices.
- * @param[in] b_row_stride Row stride inside the weights matrix.
- * @param[in] c_matrix_stride Stride between output matrices.
- * @param[in] c_row_stride Row stride inside the output matrix.
- * @param[out] a_ptr Input workspace.
- * @param[out] b_ptr Kernel workspace.
- * @param[out] c_ptr Output workspace.
- */
- void configure(
- const unsigned int n_gemms,
- const int M, const int K, const int N,
- const int a_matrix_stride,
- const int a_row_stride,
- const int b_matrix_stride,
- const int b_row_stride,
- const int c_matrix_stride,
- const int c_row_stride,
- const TIn *const a_ptr,
- const TIn *const b_ptr,
- TOut *const c_ptr) override;
-
- void run(const Window &window, const ThreadInfo &info) override;
-
- /** Static function to check if given info will lead to a valid configuration of @ref NEWinogradLayerBatchedGEMMKernel.
- *
- * @param[in] a First input tensor (Matrix or Vector A). Data types supported: F32
- * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a.
- * @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a.
- * @param[out] output Output tensor. Data type supported: same as @p a
- * @param[in] alpha Weight of the matrix product
- * @param[in] beta Weight of matrix C
- * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and
- * if the reshape of matrix B should happen only for the first run
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensor *c, const ITensorInfo *output, const float alpha, const float beta, const GEMMInfo &gemm_info = GEMMInfo());
-
-private:
- static const int _output_tile_rows = OutputTileRows;
- static const int _output_tile_cols = OutputTileCols;
- std::unique_ptr<MultiGEMM> _gemms;
+ using TransformInputKernel = NEWinogradLayerTransformInputKernel<TIn, OutputTileRows, OutputTileCols, KernelRows, KernelCols>;
+ using TransformWeightsKernel = NEWinogradLayerTransformWeightsKernel<TIn, OutputTileRows, OutputTileCols, KernelRows, KernelCols>;
+ using TransformOutputKernel = NEWinogradLayerTransformOutputKernel<TOut, OutputTileRows, OutputTileCols, KernelRows, KernelCols>;
};
} // namespace arm_compute