COMPMID-1162: Enable NHWC data layout support for NEWinogradConvolutionLayer - part1
In this first part we reworked the configuration of the kernels as before we
passed the raw pointer to the buffer within the configuration of the function
Change-Id: I83d3cb64c562303093c7f0ae52395ecd080a5d52
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/133560
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h b/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
index 6b8866c..68c133e 100644
--- a/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h
@@ -42,15 +42,15 @@
/** Determine how much memory (in units of TIn) to allocate for the
* transformed input.
*
- * @param[in] n_batches Number of batches in the input tensor.
- * @param[in] n_channels Number of feature maps in the input tensor.
- * @param[in] n_rows Number of rows in each feature map.
- * @param[in] n_cols Number of columns in each feature map.
+ * @param[in] num_batches Number of batches in the input tensor.
+ * @param[in] num_channels Number of feature maps in the input tensor.
+ * @param[in] num_rows Number of rows in each feature map.
+ * @param[in] num_cols Number of columns in each feature map.
* @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
*
* @return Storage size (in units of TIn) required.
*/
- virtual unsigned int get_input_storage_size(int n_batches, int n_channels, int n_rows, int n_cols, bool same_padding) const = 0;
+ virtual unsigned int get_input_storage_size(int num_batches, int num_channels, int num_rows, int num_cols, bool same_padding) const = 0;
/** Gets the stride between matrices in the input worspace
*
@@ -64,16 +64,17 @@
/** Configure the output transform kernel.
*
- * @param[in] input Input tensor data
- * @param[in] n_batches Number of batches in input tensor.
- * @param[in] n_rows Number of rows in input tensor.
- * @param[in] n_cols Number of columns in input tensor.
- * @param[in] n_channels Number of channels in input tensor.
+ * @param[in] input_nhwc Input tensor in NHWC data layout format.
+ * @param[in] num_batches Number of batches in input tensor.
+ * @param[in] num_rows Number of rows in input tensor.
+ * @param[in] num_cols Number of columns in input tensor.
+ * @param[in] num_channels Number of channels in input tensor.
* @param[in] padding Padding type.
* @param[out] output Base of output matrices.
* @param[in] matrix_stride Stride between output matrices.
*/
- virtual void configure(const T *const input, const int n_batches, const int n_rows, const int n_cols, const int n_channels, const PaddingType padding, T *const output, const int matrix_stride) = 0;
+ 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;
/** Destructor */
virtual ~INEWinogradLayerTransformInputKernel()
@@ -86,22 +87,33 @@
class NEWinogradLayerTransformInputKernel : public INEWinogradLayerTransformInputKernel<T>
{
public:
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEWinogradLayerTransformInputKernel(const NEWinogradLayerTransformInputKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEWinogradLayerTransformInputKernel &operator=(const NEWinogradLayerTransformInputKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ NEWinogradLayerTransformInputKernel(NEWinogradLayerTransformInputKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ NEWinogradLayerTransformInputKernel &operator=(NEWinogradLayerTransformInputKernel &&) = default;
+ /** Default destructor */
+ ~NEWinogradLayerTransformInputKernel() = default;
+
/** Determine how much memory (in units of TIn) to allocate for the
* transformed input.
*
- * @param[in] n_batches Number of batches in the input tensor.
- * @param[in] n_channels Number of feature maps in the input tensor.
- * @param[in] n_rows Number of rows in each feature map.
- * @param[in] n_cols Number of columns in each feature map.
+ * @param[in] num_batches Number of batches in the input tensor.
+ * @param[in] num_channels Number of feature maps in the input tensor.
+ * @param[in] num_rows Number of rows in each feature map.
+ * @param[in] num_cols Number of columns in each feature map.
* @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
*
* @return Storage size (in units of TIn) required.
*/
unsigned int get_input_storage_size(
- int n_batches,
- int n_channels,
- int n_rows,
- int n_cols,
+ int num_batches,
+ int num_channels,
+ int num_rows,
+ int num_cols,
bool same_padding) const override;
/** Gets the stride between matrices in the input worspace
@@ -124,21 +136,21 @@
/** Configure the output transform kernel.
*
- * @param[in] input Input tensor data. Data types supported: F32.
- * @param[in] n_batches Number of batches in input tensor.
- * @param[in] n_rows Number of rows in input tensor.
- * @param[in] n_cols Number of columns in input tensor.
- * @param[in] n_channels Number of channels in input tensor.
+ * @param[in] input_nhwc Input tensor. Data types supported: F32. Layout supported NHWC.
+ * @param[in] num_batches Number of batches in input tensor.
+ * @param[in] num_rows Number of rows in input tensor.
+ * @param[in] num_cols Number of columns in input tensor.
+ * @param[in] num_channels Number of channels in input tensor.
* @param[in] padding Padding type.
* @param[out] output Base of output matrices.
* @param[in] matrix_stride Stride between output matrices.
*/
void configure(
- const T *const input,
- const int n_batches,
- const int n_rows,
- const int n_cols,
- const int n_channels,
+ 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) override;
@@ -163,7 +175,14 @@
private:
using InputTransform = typename WinogradBase::template InputTransform<T>;
- std::unique_ptr<InputTransform> _transform;
+ const ITensor *_input_nhwc;
+ int _num_batches; /**< Number of batches in input tensor. */
+ int _num_rows; /**< Number of rows in input tensor. */
+ 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. */
+ int _matrix_stride; /**< Stride between output matrices. */
};
/** Interface for the NEON kernel to perform Winograd output transform. */
@@ -174,15 +193,15 @@
/** Determine how much memory (in units of TOut) to allocate for the
* (Winograd domain) output.
*
- * @param[in] n_batches Number of batches in the output tensor.
- * @param[in] n_rows Number of rows in each feature map of the input tensor.
- * @param[in] n_cols Number of columns in each feature map of the input tensor.
- * @param[in] n_output_channels Number of feature maps in the output tensor.
- * @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
+ * @param[in] num_batches Number of batches in the output tensor.
+ * @param[in] num_rows Number of rows in each feature map of the input tensor.
+ * @param[in] num_cols Number of columns in each feature map of the input tensor.
+ * @param[in] num_output_channels Number of feature maps in the output tensor.
+ * @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
*
* @return Storage size (in units of TOut) required.
*/
- virtual unsigned int get_output_storage_size(int n_batches, int n_rows, int n_cols, int n_output_channels, bool same_padding) const = 0;
+ virtual unsigned int get_output_storage_size(int num_batches, int num_rows, int num_cols, int num_output_channels, bool same_padding) const = 0;
/** Gets the stride between matrices in the output worspace
*
@@ -209,21 +228,21 @@
* @param[in] biases Pointer to the biases tensor.
* @param[in] output_workingspace Pointer to working space for the output tensor in the Winograd domain.
* @param[in] matrix_stride Output matrix stride, can be computed with winograd::WinogradGEMM<2, 2, 3, 3>::Convolution<float, float>::get_output_matrix_stride()
- * @param[out] output Pointer to NHWC ordered output tensor, in the spatial domain.
- * @param[in] n_batches Number of batches in the input tensor.
- * @param[in] n_rows Number of rows in output tensor.
- * @param[in] n_cols Number of columns in output tensor.
- * @param[in] n_channels Number of feature maps in the output tensor.
+ * @param[out] output_nhwc Pointer to a tensor in NHWC data layout ordered output tensor, in the spatial domain.
+ * @param[in] num_batches Number of batches in the input tensor.
+ * @param[in] num_rows Number of rows in output tensor.
+ * @param[in] num_cols Number of columns in output tensor.
+ * @param[in] num_channels Number of feature maps in the output tensor.
*/
virtual void configure(
const ITensor *biases,
const T *const output_workingspace,
const int matrix_stride,
- T *const output,
- const int n_batches,
- const int n_rows,
- const int n_cols,
- const int n_channels) = 0;
+ ITensor *const output_nhwc,
+ const int num_batches,
+ const int num_rows,
+ const int num_cols,
+ const int num_channels) = 0;
virtual ~INEWinogradLayerTransformOutputKernel()
{
@@ -257,15 +276,15 @@
/** Determine how much memory (in units of TOut) to allocate for the
* (Winograd domain) output.
*
- * @param[in] n_batches Number of batches in the output tensor.
- * @param[in] n_rows Number of rows in each feature map of the input tensor.
- * @param[in] n_cols Number of columns in each feature map of the input tensor.
- * @param[in] n_output_channels Number of feature maps in the output tensor.
- * @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
+ * @param[in] num_batches Number of batches in the output tensor.
+ * @param[in] num_rows Number of rows in each feature map of the input tensor.
+ * @param[in] num_cols Number of columns in each feature map of the input tensor.
+ * @param[in] num_output_channels Number of feature maps in the output tensor.
+ * @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
*
* @return Storage size (in units of TOut) required.
*/
- unsigned int get_output_storage_size(int n_batches, int n_rows, int n_cols, int n_output_channels, bool same_padding) const override;
+ unsigned int get_output_storage_size(int num_batches, int num_rows, int num_cols, int num_output_channels, bool same_padding) const override;
/** Gets the stride between matrices in the output worspace
*
@@ -291,21 +310,21 @@
* @param[in] biases Pointer to the biases tensor.
* @param[in] output_workingspace Pointer to working space for the output tensor in the Winograd domain.
* @param[in] matrix_stride Output matrix stride, can be computed with winograd::WinogradGEMM<2, 2, 3, 3>::Convolution<float, float>::get_output_matrix_stride()
- * @param[out] output Pointer to NHWC ordered output tensor, in the spatial domain.
- * @param[in] n_batches Number of batches in the input tensor.
- * @param[in] n_rows Number of rows in output tensor.
- * @param[in] n_cols Number of columns in output tensor.
- * @param[in] n_channels Number of feature maps in the output tensor.
+ * @param[out] output_nhwc Pointer to a tensor with NHWC data layout, in the spatial domain.
+ * @param[in] num_batches Number of batches in the input tensor.
+ * @param[in] num_rows Number of rows in output tensor.
+ * @param[in] num_cols Number of columns in output tensor.
+ * @param[in] num_channels Number of feature maps in the output tensor.
*/
void configure(
const ITensor *biases,
const T *const output_workingspace,
const int matrix_stride,
- T *const output,
- const int n_batches,
- const int n_rows,
- const int n_cols,
- const int n_channels) override;
+ ITensor *const output_nhwc,
+ const int num_batches,
+ const int num_rows,
+ const int num_cols,
+ const int num_channels) override;
void run(const Window &window, const ThreadInfo &info) override;
@@ -329,11 +348,11 @@
const T *_output_workspace;
int _matrix_stride;
int _matrix_row_stride;
- T *_output;
- int _n_batches;
- int _n_rows;
- int _n_cols;
- int _n_channels;
+ ITensor *_output_nhwc;
+ int _num_batches;
+ int _num_rows;
+ int _num_cols;
+ int _num_channels;
};
/** Interface for the NEON kernel to perform Winograd weights transform. */
@@ -344,12 +363,12 @@
/** Determine how much memory (in units of T) to allocate for the
* transformed weights.
*
- * @param[in] n_output_channels Number of output feature maps.
- * @param[in] n_input_channels Number of input feature maps.
+ * @param[in] num_output_channels Number of output feature maps.
+ * @param[in] num_input_channels Number of input feature maps.
*
* @return Storage size (in units of T) required.
*/
- virtual unsigned int get_weight_storage_size(int n_output_channels, int n_input_channels) const = 0;
+ virtual unsigned int get_weight_storage_size(int num_output_channels, int num_input_channels) const = 0;
/** Gets the stride between matrices in the kernel worspace
*
* @param[in] kernel_shape The shape of the weights tensor.
@@ -360,13 +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] n_output_channels Number of filters.
- * @param[in] n_input_channels Number of channels in each filter.
+ * @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.
*/
- virtual void configure(const ITensor *weights_hwio, T *const output, const int matrix_stride, const int n_output_channels, const int n_input_channels) = 0;
+
+ 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 ~INEWinogradLayerTransformWeightsKernel()
{
@@ -378,6 +398,17 @@
class NEWinogradLayerTransformWeightsKernel final : public INEWinogradLayerTransformWeightsKernel<T>
{
public:
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEWinogradLayerTransformWeightsKernel(const NEWinogradLayerTransformWeightsKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ NEWinogradLayerTransformWeightsKernel &operator=(const NEWinogradLayerTransformWeightsKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ NEWinogradLayerTransformWeightsKernel(NEWinogradLayerTransformWeightsKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ NEWinogradLayerTransformWeightsKernel &operator=(NEWinogradLayerTransformWeightsKernel &&) = default;
+ /** Default destructor */
+ ~NEWinogradLayerTransformWeightsKernel() = default;
+
/** Default constructor. */
NEWinogradLayerTransformWeightsKernel();
const char *name() const override
@@ -397,8 +428,8 @@
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 n_output_channels, const int n_input_channels) override;
- unsigned int get_weight_storage_size(int n_output_channels, int n_input_channels) const override;
+ void configure(const ITensor *weights_hwio, T *const 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;
bool is_parallelisable() const override;
@@ -407,7 +438,12 @@
using WinogradBase = winograd::WinogradGEMM<OutputTileRows, OutputTileCols, KernelRows, KernelCols>;
using WinogradConv = typename WinogradBase::template Convolution<T, T>;
using WeightsTransform = typename WinogradBase::template WeightsTransform<T>;
- std::unique_ptr<WeightsTransform> _transform;
+
+ const ITensor *_weights_hwio;
+ T *_output;
+ int _matrix_stride;
+ int _num_output_channels;
+ int _num_input_channels;
};
/** Interface for the NEON kernel to perform Winograd. */
@@ -421,7 +457,7 @@
/** Initialise the kernel
*
* @param[in] n_gemms Number of GEMMs to compute.
- * @param[in] M in_shape.n_batches * tile_rows * tile_cols.
+ * @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.
@@ -498,7 +534,7 @@
/** Initialise the kernel
*
* @param[in] n_gemms Number of GEMMs to compute.
- * @param[in] M in_shape.n_batches * tile_rows * tile_cols.
+ * @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.