COMPMID-935 - Implementing Convolution with Winograd on OpenCL (part 4)
Implemented Winograd Output Transform (2x2,3x3) on OpenCL
Implemented CLWinogradConvolutionLayer on OpenCL
Change-Id: I6a113fc5f052ca07f878d2b800d2ab003f84af65
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125148
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 4b7fa8a..9df2dcb 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -354,6 +354,7 @@
{ "winograd_filter_transform_2x2_3x3_nchw", "winograd.cl" },
{ "winograd_input_transform_2x2_3x3_stepz1_nchw", "winograd.cl" },
{ "winograd_input_transform_2x2_3x3_stepz2_nchw", "winograd.cl" },
+ { "winograd_output_transform_2x2_3x3_nchw", "winograd.cl" },
{ "YUYV422_to_IYUV_bt709", "color_convert.cl" },
{ "YUYV422_to_NV12_bt709", "color_convert.cl" },
{ "YUYV422_to_RGB888_bt709", "color_convert.cl" },
diff --git a/src/core/CL/cl_kernels/gemm.cl b/src/core/CL/cl_kernels/gemm.cl
index cba5eea..a5b0acb 100644
--- a/src/core/CL/cl_kernels/gemm.cl
+++ b/src/core/CL/cl_kernels/gemm.cl
@@ -162,6 +162,8 @@
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
* @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
* @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -199,8 +201,18 @@
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
- __global float *src_addr_a = (__global float *)(src0_ptr + z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes);
- __global float *src_addr_b = (__global float *)(src1_ptr + z * src1_stride_z + x * src1_stride_y + src1_offset_first_element_in_bytes);
+ int src0_addr_in_bytes = z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
+ int src1_addr_in_bytes = x * src1_stride_y + src1_offset_first_element_in_bytes;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src1_addr_in_bytes += (z % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
+ src1_addr_in_bytes += z * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
+
+ __global float *src_addr_a = (__global float *)(src0_ptr + src0_addr_in_bytes);
+ __global float *src_addr_b = (__global float *)(src1_ptr + src1_addr_in_bytes);
// Compute end row address for matrix B
__global float *src_end_addr_b = src_addr_b + COLS_B;
@@ -277,6 +289,9 @@
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
* @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
* @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -314,8 +329,18 @@
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
- __global float *src_addr_a = (__global float *)(src0_ptr + z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes);
- __global float *src_addr_b = (__global float *)(src1_ptr + z * src1_stride_z + x * src1_stride_y + src1_offset_first_element_in_bytes);
+ int src0_addr_in_bytes = z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
+ int src1_addr_in_bytes = x * src1_stride_y + src1_offset_first_element_in_bytes;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src1_addr_in_bytes += (z % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
+ src1_addr_in_bytes += z * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
+
+ __global float *src_addr_a = (__global float *)(src0_ptr + src0_addr_in_bytes);
+ __global float *src_addr_b = (__global float *)(src1_ptr + src1_addr_in_bytes);
// Compute end row address for matrix B
__global float *src_end_addr_b = src_addr_b + COLS_B;
@@ -510,6 +535,8 @@
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
* @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
* @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -547,8 +574,18 @@
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
- __global half *src_addr_a = (__global half *)(src0_ptr + z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes);
- __global half *src_addr_b = (__global half *)(src1_ptr + z * src1_stride_z + x * src1_stride_y + src1_offset_first_element_in_bytes);
+ int src0_addr_in_bytes = z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
+ int src1_addr_in_bytes = x * src1_stride_y + src1_offset_first_element_in_bytes;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src1_addr_in_bytes += (z % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
+ src1_addr_in_bytes += z * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
+
+ __global half *src_addr_a = (__global half *)(src0_ptr + src0_addr_in_bytes);
+ __global half *src_addr_b = (__global half *)(src1_ptr + src1_addr_in_bytes);
// Compute end row address for matrix B
__global half *src_end_addr_b = src_addr_b + COLS_B;
@@ -627,8 +664,9 @@
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
* @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
* @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- *
- * @note: ALPHA must be passed in 8 bit fixed point format
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note:ALPHA must be passed in 8 bit fixed point format
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -666,8 +704,18 @@
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
- __global char *src_addr_a = src0_ptr + z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
- __global char *src_addr_b = src1_ptr + z * src1_stride_z + x * src1_stride_y + src1_offset_first_element_in_bytes;
+ int src0_addr_in_bytes = z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
+ int src1_addr_in_bytes = x * src1_stride_y + src1_offset_first_element_in_bytes;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src1_addr_in_bytes += (z % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
+ src1_addr_in_bytes += z * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
+
+ __global char *src_addr_a = (__global char *)(src0_ptr + src0_addr_in_bytes);
+ __global char *src_addr_b = (__global char *)(src1_ptr + src1_addr_in_bytes);
// Compute end row address for matrix B
__global char *src_end_addr_b = src_addr_b + COLS_B;
@@ -738,8 +786,9 @@
* @note The number of columns of matrix B and the optional alpha's value need to be passed at compile time using -DCOLS_B and -DALPHA
* @note The multiplication factor for the transposition width (mult_transpose1xW_width) must be passed at compile time using -DMULT_TRANSPOSE1XW_WIDTH (i.e. -DMULT_TRANSPOSE1XW_WIDTH=2)
* @note The multiplication factor for the height of the 4x4 interleaved block must be passed at compile time using -DMULT_INTERLEAVE4X4_HEIGHT (i.e. -DMULT_INTERLEAVE4X4_HEIGHT=2)
- *
- * @note: ALPHA must be passed in 16 bit fixed point format
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
+ * @note:ALPHA must be passed in 16 bit fixed point format
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -777,8 +826,18 @@
// src_addr_a = address of matrix A
// src_addr_b = address of matrix B
- __global short *src_addr_a = (__global short *)(src0_ptr + z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes);
- __global short *src_addr_b = (__global short *)(src1_ptr + z * src1_stride_z + x * src1_stride_y + src1_offset_first_element_in_bytes);
+ int src0_addr_in_bytes = z * src0_stride_z + y * src0_stride_y + src0_offset_first_element_in_bytes;
+ int src1_addr_in_bytes = x * src1_stride_y + src1_offset_first_element_in_bytes;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src1_addr_in_bytes += (z % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
+ src1_addr_in_bytes += z * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
+
+ __global short *src_addr_a = (__global short *)(src0_ptr + src0_addr_in_bytes);
+ __global short *src_addr_b = (__global short *)(src1_ptr + src1_addr_in_bytes);
// Compute end row address for matrix B
__global short *src_end_addr_b = src_addr_b + COLS_B;
@@ -845,6 +904,8 @@
* @note The floating point data type must be passed at compile time using -DDATA_TYPE (e.g. -DDATA_TYPE=float)
* @note The number of elements processed along the x and y directions must be passed at compile time using -DNUM_ELEMS_PROCESSED_PER_THREAD_X and -DNUM_ELEMS_PROCESSED_PER_THREAD_Y
* @note The number of matrix A columns and the optional alpha's value need to be passed at compile time using -DCOLS_A and -DALPHA
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -885,7 +946,13 @@
// Add offset for batched GEMM
src_addr.s0 += get_global_id(2) * src0_stride_z;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
src_addr.s1 += get_global_id(2) * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(DATA_TYPE));
@@ -1013,6 +1080,8 @@
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=4.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -1054,8 +1123,12 @@
// Add offset for batched GEMM
src_addr.s0 += get_global_id(2) * src0_stride_z;
- // For convolution layer we do not want to slide the matrix B along Z
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
src_addr.s1 += get_global_id(2) * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
// Address boundary for matrix A
int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(float));
@@ -1251,6 +1324,8 @@
* This kernel optimally uses -DNUM_ELEMS_PROCESSED_PER_THREAD_X=2.
* @note The number of matrix A columns must be passed at compile time using -DCOLS_A.
* @note The optional value of scalar alpha is passed at compile time using -DALPHA=alpha if alpha!=1.0f.
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: F16/F32
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -1293,8 +1368,12 @@
// Add offset for batched GEMM
src_addr.s0 += get_global_id(2) * src0_stride_z;
- // For convolution layer we do not want to slide the matrix B along Z
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
src_addr.s1 += get_global_id(2) * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
// Address boundary for the matrix A
int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(float));
@@ -1460,6 +1539,8 @@
* @note The number matrix A columns, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA
* @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION
* @note The optional alpha value must be passed in 8 bit fixed point format using -DALPHA
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -1500,7 +1581,13 @@
// Add offset for batched GEMM
src_addr.s0 += get_global_id(2) * src0_stride_z;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
src_addr.s1 += get_global_id(2) * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(char));
@@ -1636,6 +1723,8 @@
* @note The number of matrix A columns, the number of elements processed per thread along the Y direction and the alpha's value need to be passed at compile time using -DCOLS_A, -DNUM_ELEMS_PROCESSED_PER_THREAD_Y and -DALPHA
* @note The fixed point position need to be passed at compile time using -DFIXED_POINT_POSITION
* @note The optional alpha value must be passed in 16 bit fixed point format using -DALPHA
+ * @note In case the matrix B has 3 dimensions and the matrix A more than 3, in order to avoid out-of-bounds reads, the number of channels of matrix B must be passed at compile time using MATRIX_B_DEPTH (i.e. -DMATRIX_B_DEPTH=16)
+ * This case can happen when GEMM is used to perform the element-wise multiplication through a batched matrix multiplication (2D Winograd) and we have multiple inputs (i.e. a = [K, M, 16, Batches], b = [N, K, 16])
*
* @param[in] src0_ptr Pointer to the source matrix. Supported data types: QS8/QS16
* @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes)
@@ -1676,7 +1765,13 @@
// Add offset for batched GEMM
src_addr.s0 += get_global_id(2) * src0_stride_z;
+
+#if defined(MATRIX_B_DEPTH)
+ // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
+ src_addr.s1 += (get_global_id(2) % MATRIX_B_DEPTH) * src1_stride_z;
+#else // defined(MATRIX_B_DEPTH)
src_addr.s1 += get_global_id(2) * src1_stride_z;
+#endif // defined(MATRIX_B_DEPTH)
int end_row_vec_a = src_addr.s0 + (COLS_A * sizeof(short));
diff --git a/src/core/CL/cl_kernels/winograd.cl b/src/core/CL/cl_kernels/winograd.cl
index 238e21a..25c129d 100644
--- a/src/core/CL/cl_kernels/winograd.cl
+++ b/src/core/CL/cl_kernels/winograd.cl
@@ -23,8 +23,102 @@
*/
#include "helpers.h"
-#if defined(NUM_TILES_X)
+#if defined(NUM_CHANNELS)
+/** This OpenCL kernel performs Winograd filter transform 3x3 when the data format is NCHW and the output tile is 2x2
+ *
+ * @note The number of channels must be passed at compile time using -DNUM_CHANNELS: e.g. -DNUM_CHANNELS=64
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: F32
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
+ * @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ */
+__kernel void winograd_filter_transform_2x2_3x3_nchw(
+ TENSOR4D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst))
+{
+ Tensor4D src = CONVERT_TO_TENSOR4D_STRUCT(src, NUM_CHANNELS);
+
+ const __global uchar *src_addr = tensor4D_offset(&src, 0, 0, 0, 0);
+
+ // Load the values from the input tensor
+ float3 w0 = vload3(0, (__global float *)(src_addr + 0 * src_stride_y));
+ float3 w1 = vload3(0, (__global float *)(src_addr + 1 * src_stride_y));
+ float3 w2 = vload3(0, (__global float *)(src_addr + 2 * src_stride_y));
+
+ // Transform the 3x3 tile in a 4x4 tile
+ float4 out0 = 0.0f;
+ float4 out1 = 0.0f;
+ float4 out2 = 0.0f;
+ float4 out3 = 0.0f;
+
+ // Row 0
+ out0.s0 = (w0.s0);
+ out0.s1 = (w0.s0 + w0.s1 + w0.s2) * 0.5f;
+ out0.s2 = (w0.s0 + w0.s2 - w0.s1) * 0.5f;
+ out0.s3 = (w0.s2);
+
+ // Row 1
+ out1.s0 = (w0.s0 + w1.s0 + w2.s0) * 0.5f;
+ out1.s1 = (w0.s0 + w1.s0 + w2.s0 + w0.s1 + w1.s1 + w2.s1 + w0.s2 + w1.s2 + w2.s2) * 0.25f;
+ out1.s2 = (w0.s0 + w1.s0 + w2.s0 + w0.s2 + w1.s2 + w2.s2 - w0.s1 - w1.s1 - w2.s1) * 0.25f;
+ out1.s3 = (w0.s2 + w1.s2 + w2.s2) * 0.5f;
+
+ // Row 2
+ out2.s0 = (w0.s0 + w2.s0 - w1.s0) * 0.5f;
+ out2.s1 = (w0.s0 + w2.s0 + w0.s1 + w2.s1 + w0.s2 + w2.s2 - w1.s0 - w1.s1 - w1.s2) * 0.25f;
+ out2.s2 = (w0.s0 + w2.s0 + w1.s1 + w0.s2 + w2.s2 - w1.s0 - w0.s1 - w2.s1 - w1.s2) * 0.25f;
+ out2.s3 = (w0.s2 + w2.s2 - w1.s2) * 0.5f;
+
+ // Row 3
+ out3.s0 = (w2.s0);
+ out3.s1 = (w2.s0 + w2.s1 + w2.s2) * 0.5f;
+ out3.s2 = (w2.s0 + w2.s2 - w2.s1) * 0.5f;
+ out3.s3 = (w2.s2);
+
+ int z = get_global_id(2);
+ int x0 = z / NUM_CHANNELS; // idx filter
+ int y0 = z % NUM_CHANNELS; // idx channel
+
+ // Get output address
+ __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x0 * dst_stride_x + y0 * dst_stride_y;
+
+ // Store the 16 values across the 16 channels
+ *(__global float *)(dst_addr + 0 * dst_stride_z) = out0.s0;
+ *(__global float *)(dst_addr + 1 * dst_stride_z) = out0.s1;
+ *(__global float *)(dst_addr + 2 * dst_stride_z) = out0.s2;
+ *(__global float *)(dst_addr + 3 * dst_stride_z) = out0.s3;
+ *(__global float *)(dst_addr + 4 * dst_stride_z) = out1.s0;
+ *(__global float *)(dst_addr + 5 * dst_stride_z) = out1.s1;
+ *(__global float *)(dst_addr + 6 * dst_stride_z) = out1.s2;
+ *(__global float *)(dst_addr + 7 * dst_stride_z) = out1.s3;
+ *(__global float *)(dst_addr + 8 * dst_stride_z) = out2.s0;
+ *(__global float *)(dst_addr + 9 * dst_stride_z) = out2.s1;
+ *(__global float *)(dst_addr + 10 * dst_stride_z) = out2.s2;
+ *(__global float *)(dst_addr + 11 * dst_stride_z) = out2.s3;
+ *(__global float *)(dst_addr + 12 * dst_stride_z) = out3.s0;
+ *(__global float *)(dst_addr + 13 * dst_stride_z) = out3.s1;
+ *(__global float *)(dst_addr + 14 * dst_stride_z) = out3.s2;
+ *(__global float *)(dst_addr + 15 * dst_stride_z) = out3.s3;
+}
+#endif // defined(NUM_CHANNELS)
+
+#if defined(NUM_TILES_X) && defined(PAD_LEFT) && defined(PAD_TOP)
/** This OpenCL kernel computes the input transform when the kernel size is 3x3 and the output tile is 2x2
*
* @note The number of tiles in the x axis must be passed at compile time using -DNUM_TILES_X (i.e.-DNUM_TILES_X=5).
@@ -205,13 +299,12 @@
vstore2(out32, 0, (__global float *)(dst_addr + 14 * dst_stride_z));
vstore2(out33, 0, (__global float *)(dst_addr + 15 * dst_stride_z));
}
-#endif //defined(NUM_TILES_X)
+#endif // defined(NUM_TILES_X) && defined(PAD_LEFT) && defined(PAD_TOP)
-#if defined(NUM_CHANNELS)
-
-/** This OpenCL kernel performs Winograd filter transform 3x3 when the data format is NCHW and the output tile is 2x2
+#if defined(NUM_TILES_X)
+/** This OpenCL kernel performs Winograd output transform when the output tile is 2x2, the filter size 3x3 and the data format is NCHW
*
- * @note The number of channels must be passed at compile time using -DNUM_CHANNELS: e.g. -DNUM_CHANNELS=64
+ * @note The number of tiles along the X direction must be passed at compile time using -DNUM_TILES_X: e.g. -DNUM_TILES_X=16
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: F32
* @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
@@ -220,8 +313,6 @@
* @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
- * @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
@@ -232,72 +323,84 @@
* @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
*/
-__kernel void winograd_filter_transform_2x2_3x3_nchw(
- TENSOR4D_DECLARATION(src),
- TENSOR3D_DECLARATION(dst))
+__kernel void winograd_output_transform_2x2_3x3_nchw(
+ TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst)
+#if defined(HAS_BIAS)
+ ,
+ VECTOR_DECLARATION(bias)
+#endif // defined(HAS_BIAS)
+)
{
- Tensor4D src = CONVERT_TO_TENSOR4D_STRUCT(src, NUM_CHANNELS);
+ // Each thread stores a 2x2 tile
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
- const __global uchar *src_addr = tensor4D_offset(&src, 0, 0, 0, 0);
+ const __global uchar *src_addr = tensor3D_offset(&src, 0, 0, 0);
- // Load the values from the input tensor
- float3 w0 = vload3(0, (__global float *)(src_addr + 0 * src_stride_y));
- float3 w1 = vload3(0, (__global float *)(src_addr + 1 * src_stride_y));
- float3 w2 = vload3(0, (__global float *)(src_addr + 2 * src_stride_y));
+ // Load the values across the 16 channels to compose the 4x4 tile
+ float d00 = *((__global float *)(src_addr + 0 * src_stride_z));
+ float d01 = *((__global float *)(src_addr + 1 * src_stride_z));
+ float d02 = *((__global float *)(src_addr + 2 * src_stride_z));
+ float d03 = *((__global float *)(src_addr + 3 * src_stride_z));
- // Transform the 3x3 tile in a 4x4 tile
- float4 out0 = 0.0f;
- float4 out1 = 0.0f;
- float4 out2 = 0.0f;
- float4 out3 = 0.0f;
+ float d10 = *((__global float *)(src_addr + 4 * src_stride_z));
+ float d11 = *((__global float *)(src_addr + 5 * src_stride_z));
+ float d12 = *((__global float *)(src_addr + 6 * src_stride_z));
+ float d13 = *((__global float *)(src_addr + 7 * src_stride_z));
- // Row 0
- out0.s0 = (w0.s0);
- out0.s1 = (w0.s0 + w0.s1 + w0.s2) * 0.5f;
- out0.s2 = (w0.s0 + w0.s2 - w0.s1) * 0.5f;
- out0.s3 = (w0.s2);
+ float d20 = *((__global float *)(src_addr + 8 * src_stride_z));
+ float d21 = *((__global float *)(src_addr + 9 * src_stride_z));
+ float d22 = *((__global float *)(src_addr + 10 * src_stride_z));
+ float d23 = *((__global float *)(src_addr + 11 * src_stride_z));
- // Row 1
- out1.s0 = (w0.s0 + w1.s0 + w2.s0) * 0.5f;
- out1.s1 = (w0.s0 + w1.s0 + w2.s0 + w0.s1 + w1.s1 + w2.s1 + w0.s2 + w1.s2 + w2.s2) * 0.25f;
- out1.s2 = (w0.s0 + w1.s0 + w2.s0 + w0.s2 + w1.s2 + w2.s2 - w0.s1 - w1.s1 - w2.s1) * 0.25f;
- out1.s3 = (w0.s2 + w1.s2 + w2.s2) * 0.5f;
+ float d30 = *((__global float *)(src_addr + 12 * src_stride_z));
+ float d31 = *((__global float *)(src_addr + 13 * src_stride_z));
+ float d32 = *((__global float *)(src_addr + 14 * src_stride_z));
+ float d33 = *((__global float *)(src_addr + 15 * src_stride_z));
- // Row 2
- out2.s0 = (w0.s0 + w2.s0 - w1.s0) * 0.5f;
- out2.s1 = (w0.s0 + w2.s0 + w0.s1 + w2.s1 + w0.s2 + w2.s2 - w1.s0 - w1.s1 - w1.s2) * 0.25f;
- out2.s2 = (w0.s0 + w2.s0 + w1.s1 + w0.s2 + w2.s2 - w1.s0 - w0.s1 - w2.s1 - w1.s2) * 0.25f;
- out2.s3 = (w0.s2 + w2.s2 - w1.s2) * 0.5f;
+ // Compute the 2x2 output tile
+ float k0 = d01 + d11 + d21;
+ float k1 = d02 + d12 + d22;
+ float k2 = d11 - d21 - d31;
+ float k3 = d12 - d22 - d32;
- // Row 3
- out3.s0 = (w2.s0);
- out3.s1 = (w2.s0 + w2.s1 + w2.s2) * 0.5f;
- out3.s2 = (w2.s0 + w2.s2 - w2.s1) * 0.5f;
- out3.s3 = (w2.s2);
+ // out00 = d00 + d10 + d20 + d01 + d11 + d21 + d02 + d12 + d22
+ // out01 = d01 + d11 + d21 - (d02 + d12 + d22) - (d03 + d13 + d23)
+ // out10 = d10 - d20 - d30 + (d11 - d21 - d31) + (d12 - d22 - d32)
+ // out11 = d11 - d21 - d31 - (d12 - d22 - d32) - (d13 - d23 - d33)
- int z = get_global_id(2);
- int x0 = z / NUM_CHANNELS; // idx filter
- int y0 = z % NUM_CHANNELS; // idx channel
+ float out00 = d10;
+ float out01 = -d13;
+ float out10 = d10;
+ float out11 = -d13;
+
+ out00 += d00 + d20 + k0 + k1;
+ out01 += k0 - k1 - (d03 + d23);
+ out10 += -d20 - d30 + k2 + k3;
+ out11 += k2 - k3 + d23 + d33;
+
+ int y_in = get_global_id(1);
+ int x_out = (y_in % NUM_TILES_X) * 2;
+ int y_out = (y_in / NUM_TILES_X) * 2;
+ int z_out = get_global_id(0);
+
+#if defined(HAS_BIAS)
+ // Add bias
+ Vector bias = CONVERT_TO_VECTOR_STRUCT_NO_STEP(bias);
+
+ float b = (float) * ((__global float *)(vector_offset(&bias, z_out)));
+
+ out00 += (float)b;
+ out01 += (float)b;
+ out10 += (float)b;
+ out11 += (float)b;
+#endif // defined(HAS_BIAS)
// Get output address
- __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x0 * dst_stride_x + y0 * dst_stride_y;
+ __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x_out * dst_stride_x + y_out * dst_stride_y + z_out * dst_stride_z;
- // Store the 16 values across the 16 channels
- *(__global float *)(dst_addr + 0 * dst_stride_z) = out0.s0;
- *(__global float *)(dst_addr + 1 * dst_stride_z) = out0.s1;
- *(__global float *)(dst_addr + 2 * dst_stride_z) = out0.s2;
- *(__global float *)(dst_addr + 3 * dst_stride_z) = out0.s3;
- *(__global float *)(dst_addr + 4 * dst_stride_z) = out1.s0;
- *(__global float *)(dst_addr + 5 * dst_stride_z) = out1.s1;
- *(__global float *)(dst_addr + 6 * dst_stride_z) = out1.s2;
- *(__global float *)(dst_addr + 7 * dst_stride_z) = out1.s3;
- *(__global float *)(dst_addr + 8 * dst_stride_z) = out2.s0;
- *(__global float *)(dst_addr + 9 * dst_stride_z) = out2.s1;
- *(__global float *)(dst_addr + 10 * dst_stride_z) = out2.s2;
- *(__global float *)(dst_addr + 11 * dst_stride_z) = out2.s3;
- *(__global float *)(dst_addr + 12 * dst_stride_z) = out3.s0;
- *(__global float *)(dst_addr + 13 * dst_stride_z) = out3.s1;
- *(__global float *)(dst_addr + 14 * dst_stride_z) = out3.s2;
- *(__global float *)(dst_addr + 15 * dst_stride_z) = out3.s3;
+ // Store the 2x2 output tile
+ vstore2((float2)(out00, out01), 0, (__global float *)(dst_addr + 0 * dst_stride_y));
+ vstore2((float2)(out10, out11), 0, (__global float *)(dst_addr + 1 * dst_stride_y));
}
-#endif // defined(NUM_CHANNELS)
+#endif // defined(NUM_TILES_X)
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index 9c69800..7b785bb 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -55,6 +55,7 @@
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the matrix B must be <= 3");
if(!is_interleaved_transposed)
{
@@ -174,7 +175,7 @@
} // namespace
CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel()
- : _input0(nullptr), _input1(nullptr), _output(nullptr)
+ : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true)
{
}
@@ -192,9 +193,10 @@
// Perform validate step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info));
- _input0 = input0;
- _input1 = input1;
- _output = output;
+ _input0 = input0;
+ _input1 = input1;
+ _output = output;
+ _slide_matrix_b = _input1->info()->num_dimensions() >= _input0->info()->num_dimensions();
const DataType data_type = input0->info()->data_type();
const int fp_pos = input0->info()->fixed_point_position();
@@ -257,6 +259,9 @@
"-DALPHA=" + float_to_string_with_full_precision(alpha));
}
+ // Do not slide matrix B if _slide_matrix_b = false
+ build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
+
std::string kernel_name;
if(is_interleaved_transposed)
{
@@ -365,7 +370,7 @@
Window slice_b = slice;
// Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
// This scenario can happen when the matrix multiplication is used to perform a convolution operation
- if(_input1->info()->num_dimensions() < 3)
+ if(!_slide_matrix_b)
{
slice_b = slice_matrix_b;
}
@@ -374,9 +379,9 @@
add_2D_tensor_argument(idx, _input0, slice);
add_2D_tensor_argument(idx, _input1, slice_b);
add_2D_tensor_argument(idx, _output, slice);
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[3]));
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[3]));
- _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
enqueue(queue, *this, slice, _lws_hint);
}
while(window.slide_window_slice_3D(slice));
diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
index 5489fde..f69a39e 100644
--- a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
@@ -76,15 +76,18 @@
}
AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
- window_changed = window_changed || update_window_and_padding(win, input_access);
// Configure window in case of configured output
if(output->total_size() != 0)
{
AccessWindowTranspose output_access(output, 0, 0, num_elems_processed_per_iteration, 1, scale_x, 1.f / scale_x);
- window_changed = window_changed || update_window_and_padding(win, output_access);
+ window_changed = window_changed || update_window_and_padding(win, input_access, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), input->tensor_shape()));
}
+ else
+ {
+ window_changed = window_changed || update_window_and_padding(win, input_access);
+ }
// Collapse along the Z direction
Window collapsed = win.collapse(win, Window::DimZ);
diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
index 3dbbe15..655b82b 100644
--- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
+++ b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
@@ -76,7 +76,7 @@
AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
AccessWindowStatic output_access(output, 0, 0, output->dimension(0), output->dimension(1));
window_changed = update_window_and_padding(win, input_access, output_access);
- output_access.set_valid_region(win, input->valid_region());
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
Window win_collapsed = win.collapse(win, Window::DimZ);
diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
index 72adb5f..3b9350f 100644
--- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
+++ b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
@@ -44,11 +44,11 @@
ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_dims.width != 3 || kernel_dims.height != 3, "Winograd input transform only supports 3x3 kernels");
ARM_COMPUTE_UNUSED(kernel_dims);
- const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, conv_info, Size2D(3U, 3U));
-
// Validate configured output
if(output->total_size() != 0)
{
+ const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, conv_info, kernel_dims);
+
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
@@ -151,7 +151,8 @@
Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PadStrideInfo &conv_info, const Size2D &kernel_dims)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON(validate_arguments(input, output, conv_info, kernel_dims));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, conv_info, kernel_dims));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), conv_info, kernel_dims).first);
return Status{};
}
diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
new file mode 100644
index 0000000..c982327
--- /dev/null
+++ b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
@@ -0,0 +1,188 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include "support/ToolchainSupport.h"
+
+#include <cmath>
+
+using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
+
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, const Size2D &num_tiles)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != num_tiles.area());
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_dims.width != 3 || kernel_dims.height != 3, "Only 3x3 kernels are supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(static_cast<unsigned int>(std::sqrt(input->dimension(2))) != 4, "Only 2x2 output tile is supported");
+ ARM_COMPUTE_UNUSED(kernel_dims);
+
+ if(bias != nullptr)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias);
+ ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0));
+ }
+
+ // Checks performed when output is configured
+ if(output->total_size() != 0)
+ {
+ const TensorInfo tensor_info_output = input->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*input, output_convolved_dims, DataLayout::NCHW));
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+ constexpr unsigned int num_elems_processed_per_iteration = 1;
+
+ Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+ bool window_changed = false;
+
+ AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration, num_elems_processed_per_iteration);
+ AccessWindowStatic output_access(output, 0, 0, ceil_to_multiple(output->dimension(0), 2), ceil_to_multiple(output->dimension(1), 2));
+
+ if(bias != nullptr)
+ {
+ AccessWindowStatic bias_access(bias, 0, 0, bias->dimension(0), bias->dimension(1));
+ window_changed = update_window_and_padding(win, input_access, bias_access, output_access);
+ }
+ else
+ {
+ window_changed = update_window_and_padding(win, input_access, output_access);
+ }
+ output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
+CLWinogradOutputTransformKernel::CLWinogradOutputTransformKernel()
+ : _input(nullptr), _bias(nullptr), _output(nullptr)
+{
+}
+
+void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims,
+ const Size2D &num_tiles)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_UNUSED(kernel_dims);
+
+ // Output tensor auto initialization if not yet initialized
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*input->info(), output_convolved_dims, DataLayout::NCHW)));
+
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), kernel_dims, output_convolved_dims, num_tiles));
+
+ _input = input;
+ _bias = bias;
+ _output = output;
+
+ // Set build options
+ CLBuildOptions build_opts;
+ build_opts.add_option_if(_bias != nullptr, std::string("-DHAS_BIAS"));
+ build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(num_tiles.width));
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("winograd_output_transform_2x2_3x3_nchw", build_opts.options()));
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure(win_config.second);
+
+ // Set config_id for enabling LWS tuning
+ _config_id = "winograd_output_transform_2x2_3x3";
+ _config_id += lower_string(string_from_data_type(input->info()->data_type()));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(input->info()->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(input->info()->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(output->info()->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(output->info()->dimension(1));
+}
+
+Status CLWinogradOutputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims,
+ const Size2D &num_tiles)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, (bias != nullptr ? bias->clone().get() : nullptr), output, kernel_dims, output_convolved_dims, num_tiles));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (bias != nullptr ? bias->clone().get() : nullptr), output->clone().get()).first);
+
+ return Status{};
+}
+
+void CLWinogradOutputTransformKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ // Get initial windows
+ Window slice = window.first_slice_window_3D();
+ slice.set(Window::DimZ, Window::Dimension(0, 1, 1));
+
+ // Setup output slice
+ Window slice_out(slice);
+ slice_out.set(Window::DimX, Window::Dimension(0, 0, 0));
+ slice_out.set(Window::DimY, Window::Dimension(0, 0, 0));
+
+ if(_bias != nullptr)
+ {
+ unsigned int idx1 = 2 * num_arguments_per_3D_tensor();
+ Window slice_biases;
+ slice_biases.use_tensor_dimensions(_bias->info()->tensor_shape());
+ add_1D_tensor_argument(idx1, _bias, slice_biases);
+ }
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, _input, slice);
+ add_3D_tensor_argument(idx, _output, slice_out);
+ enqueue(queue, *this, slice, _lws_hint);
+ }
+ while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_out));
+}
\ No newline at end of file