Rework gemmlowp reshaped_only_rhs using the new macros
Resolve COMPMID-4416
Change-Id: I83cdf0de7adaf4d465ffebd494ab913182072485
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5788
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl
index d3eba89..5cafb53 100644
--- a/src/core/CL/cl_kernels/gemmlowp.cl
+++ b/src/core/CL/cl_kernels/gemmlowp.cl
@@ -24,6 +24,7 @@
#include "gemm_helpers.h"
#include "helpers_asymm.h"
#include "repeat.h"
+#include "tile_helpers.h"
#if defined(DATA_TYPE) && defined(ACC_DATA_TYPE)
@@ -464,190 +465,10 @@
#if defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0)
-/** This OpenCL kernel computes the matrix multiplication between 2 matrices.
- * The LHS matrix is NOT reshaped
- * The RHS matrix is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed
- *
- * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar)
- * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint)
- * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64)
- * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (i.e. -DN0=8, -DK0=4).
- * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2)
- * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2)
- * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time.
- * @note Only the following configurations of M0, N0 and K0 are currently supported:
- * - M0 = 1, 2, 3, 4, 5, 6, 7, 8
- * - N0 = 2, 3, 4, 8, 16
- * - K0 = 2, 3, 4, 8, 16
- * - H0 >= 1
- *
- * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time:
- * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D
- * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D
- * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor.
- * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor
- * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix
- *
- * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: QASYMM8/QASYMM8_SIGNED
- * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes)
- * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes)
- * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix
- * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr
- * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes)
- * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes)
- * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix
- * @param[out] dst_ptr Pointer to the destination matrix Supported data type: S32
- * @param[in] dst_stride_x Stride of the destination matrix 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 matrix 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] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix
- * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes)
- * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes)
- * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
- * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D)
- * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D)
- */
-__kernel void gemmlowp_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs),
- IMAGE_DECLARATION(rhs),
- IMAGE_DECLARATION(dst),
- uint lhs_stride_z,
- uint rhs_stride_z,
- uint dst_stride_z
-#if defined(REINTERPRET_INPUT_AS_3D)
- ,
- uint lhs_cross_plane_pad
-#endif // REINTERPRET_INPUT_AS_3D
-#if defined(REINTERPRET_OUTPUT_AS_3D)
- ,
- uint dst_cross_plane_pad
-#endif // REINTERPRET_OUTPUT_AS_3D
- )
-{
- // Block size
-#define RHS_BLOCK_SIZE ((K0) * (N0))
+#if defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT)
+#define FUSED_OUTPUT_STAGE_FIXED_POINT
+#endif // defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT)
- // RHS offset and step X
-#if defined(RHS_INTERLEAVE)
-#define RHS_OFFSET_X (K0)
-#define RHS_STEP_X ((K0) * (H0))
-#define RHS_STEP_LOOP (1)
-#else // defined(RHS_INTERLEAVE)
-#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
-#define RHS_STEP_X (K0)
-#define RHS_STEP_LOOP (H0)
-#endif // defined(RHS_INTERLEAVE)
-
- uint x = get_global_id(0);
- uint y = get_global_id(1);
- uint z = get_global_id(2);
-
-#if defined(DUMMY_WORK_ITEMS)
- if((x * N0 >= N) || (y * M0 >= M))
- {
- return;
- }
-#endif // defined(DUMMY_WORK_ITEMS)
-
- // Compute LHS matrix address
- uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
-
- // Compute RHS matrix address
- uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X + (x / (uint)H0) * rhs_stride_y;
-
-#if defined(MATRIX_B_DEPTH)
- // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
- rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z;
-#else // defined(MATRIX_B_DEPTH)
- rhs_offset += z * rhs_stride_z;
-#endif // defined(MATRIX_B_DEPTH)
-
- REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
- REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0);
-
-#if defined(REINTERPRET_INPUT_AS_3D)
- // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
- CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
-
- // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
- // multiply lhs_stride_z by DEPTH_GEMM3D
- lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
-
-#else // defined(REINTERPRET_INPUT_AS_3D)
-
- // Add offset for batched GEMM
- lhs_offset += z * lhs_stride_z;
-
-#endif // defined(REINTERPRET_INPUT_AS_3D)
-
- // Initialize the accumulators
- REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0;
-
- int i = 0;
- for(; i <= (K - K0); i += K0)
- {
- // Load values from LHS matrix
- LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
-
- // Load values from RHS matrix
- LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs);
-
- // Partial matrix multiplication M0,N0,K0
- ARM_MM_K0XN0XM0(M0, N0, K0, a, b, c);
-
- lhs_offset += K0;
- rhs_offset += N0 * RHS_STEP_X * RHS_STEP_LOOP;
- }
- // Left-over accumulations
- for(; i < K; ++i)
- {
- // Load values from LHS matrix
- LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
-
- // Load values from RHS reshaped matrix
- LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs);
-
- ARM_MM_K0XN0XM0(M0, N0, 1, a, b, c);
- lhs_offset += 1;
- rhs_offset += 1;
- }
- __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(int)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
-
- REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
-
-#if defined(REINTERPRET_OUTPUT_AS_3D)
- // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
- CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
-
- // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
- // multiply dst_stride_z by DEPTH_GEMM3D
- dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
-
- // Add offset for batched GEMM
- dst_addr += z * dst_stride_z;
-
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
-
- // Convert and store output block
- const bool cond_y = y == 0;
- const bool cond_x = ((x + 1) * N0 >= N);
-
- // Store output block
- REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(int, N0), c, c_lp);
- STORE_BLOCK_BOUNDARY_AWARE(M0, N0, int, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
-
-#undef RHS_BLOCK_SIZE
-#undef RHS_OFFSET_X
-#undef RHS_STEP_X
-}
-
-#if defined(RESULT_OFFSET) && defined(RESULT_SHIFT) && defined(RESULT_MULTIPLIER)
/** This OpenCL kernel computes the matrix multiplication between 2 matrices with fused output stage using fixed-point arithmetic.
* The LHS matrix is NOT reshaped
* The RHS matrix is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed
@@ -727,164 +548,162 @@
* @param[in] result_shifts_step_x (Optional) output_shifts_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] result_shifts_offset_first_element_in_bytes (Optional) The offset of the first element in the output shifts vector
*/
-__kernel void gemmlowp_mm_reshaped_only_rhs_t_fused_output_stage_fixedpoint(IMAGE_DECLARATION(lhs),
- IMAGE_DECLARATION(rhs),
- IMAGE_DECLARATION(dst),
- uint lhs_stride_z,
- uint rhs_stride_z,
- uint dst_stride_z
+#if defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+__kernel void gemmlowp_mm_reshaped_only_rhs_t_fused_output_stage_fixedpoint
+#else // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+__kernel void gemmlowp_mm_reshaped_only_rhs_t
+#endif // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+(IMAGE_DECLARATION(lhs),
+ IMAGE_DECLARATION(rhs),
+ IMAGE_DECLARATION(dst),
+ uint lhs_stride_z,
+ uint rhs_stride_z,
+ uint dst_stride_z
#if defined(REINTERPRET_INPUT_AS_3D)
- ,
- uint lhs_cross_plane_pad
+ ,
+ uint lhs_cross_plane_pad
#endif // REINTERPRET_INPUT_AS_3D
#if defined(REINTERPRET_OUTPUT_AS_3D)
- ,
- uint dst_cross_plane_pad
+ ,
+ uint dst_cross_plane_pad
#endif // REINTERPRET_OUTPUT_AS_3D
#if defined(A_OFFSET)
- ,
- IMAGE_DECLARATION(sum_col)
+ ,
+ IMAGE_DECLARATION(sum_col)
#endif // defined(A_OFFSET)
#if defined(B_OFFSET)
- ,
- IMAGE_DECLARATION(sum_row)
+ ,
+ IMAGE_DECLARATION(sum_row)
#endif // defined(B_OFFSET)
#if defined(ADD_BIAS)
- ,
- VECTOR_DECLARATION(biases)
+ ,
+ VECTOR_DECLARATION(biases)
#endif // defined(ADD_BIAS)
#if defined(PER_CHANNEL_QUANTIZATION)
- ,
- VECTOR_DECLARATION(result_multipliers),
- VECTOR_DECLARATION(result_shifts)
+ ,
+ VECTOR_DECLARATION(result_multipliers),
+ VECTOR_DECLARATION(result_shifts)
#endif // defined(PER_CHANNEL_QUANTIZATION)
- )
+)
{
- // Block size
-#define RHS_BLOCK_SIZE ((K0) * (N0))
+ // @note: replace with (DIMENSION + PAD) once we pass the relevant info at compile time
+#define FULL_LHS_HEIGHT (lhs_stride_z / lhs_stride_y)
+#define FULL_DST_HEIGHT (dst_stride_z / dst_stride_y)
// RHS offset and step X
#if defined(RHS_INTERLEAVE)
#define RHS_OFFSET_X (K0)
-#define RHS_STEP_X ((K0) * (H0))
-#define RHS_STEP_LOOP (1)
+#define RHS_STEP_X (K0 * H0)
#else // defined(RHS_INTERLEAVE)
-#define RHS_OFFSET_X (RHS_BLOCK_SIZE)
+#define RHS_OFFSET_X (K0 * N0)
#define RHS_STEP_X (K0)
-#define RHS_STEP_LOOP (H0)
#endif // defined(RHS_INTERLEAVE)
+#define RHS_STEP_LOOP (N0 * K0 * H0)
- uint x = get_global_id(0);
- uint y = get_global_id(1);
- uint z = get_global_id(2);
+ uint x = GET_SPATIAL_IDX(0, 1, 1);
+ uint y = GET_SPATIAL_IDX(1, M0, PARTIAL_STORE_M0);
+ uint z = GET_SPATIAL_IDX(2, 1, 1);
+ int xo = (x * N0);
#if defined(DUMMY_WORK_ITEMS)
- if((x * N0 >= N) || (y * M0 >= M))
+ if((xo >= N) || (y >= M))
{
return;
}
#endif // defined(DUMMY_WORK_ITEMS)
// Compute LHS matrix address
- uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y;
+ uint lhs_y = y + z * FULL_LHS_HEIGHT;
// Compute RHS matrix address
- uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X + (x / (uint)H0) * rhs_stride_y;
+ uint rhs_offset_x = (x % H0) * RHS_OFFSET_X;
+ uint rhs_offset_y = (x / H0) * rhs_stride_y;
#if defined(MATRIX_B_DEPTH)
// Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3
- rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z;
+ rhs_offset_y += (z % MATRIX_B_DEPTH) * rhs_stride_z;
#else // defined(MATRIX_B_DEPTH)
- rhs_offset += z * rhs_stride_z;
+ rhs_offset_y += z * rhs_stride_z;
#endif // defined(MATRIX_B_DEPTH)
- REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
- REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0);
-
-#if defined(REINTERPRET_INPUT_AS_3D)
- // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
- CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y);
-
- // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
- // multiply lhs_stride_z by DEPTH_GEMM3D
- lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D;
-
-#else // defined(REINTERPRET_INPUT_AS_3D)
-
- // Add offset for batched GEMM
- lhs_offset += z * lhs_stride_z;
-
-#endif // defined(REINTERPRET_INPUT_AS_3D)
-
// Initialize the accumulators
- REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0;
+ TILE(ACC_DATA_TYPE, M0, N0, c);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c[i].v = 0;
+ })
int i = 0;
for(; i <= (K - K0); i += K0)
{
- // Load values from LHS matrix
- LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
+ TILE(DATA_TYPE, M0, K0, a);
+ TILE(DATA_TYPE, N0, K0, b);
- // Load values from RHS matrix
- LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs);
+ // Load values from LHS matrix
+ T_LOAD(DATA_TYPE, M0, K0, BUFFER, lhs, i, lhs_y, 1, lhs_stride_y, a);
+
+ // // Load values from RHS matrix
+ LOOP_UNROLLING(int, _i, 0, 1, N0,
+ {
+ b[_i].v = VLOAD(K0)(0, (__global DATA_TYPE *)(rhs_ptr + rhs_offset_first_element_in_bytes + rhs_offset_x + rhs_offset_y + _i * RHS_STEP_X));
+ })
// Partial matrix multiplication M0,N0,K0
- ARM_MM_K0XN0XM0(M0, N0, K0, a, b, c);
+ T_MMUL(DATA_TYPE, DATA_TYPE, ACC_DATA_TYPE, M0, N0, K0, NT, T, a, b, c);
- lhs_offset += K0;
- rhs_offset += N0 * RHS_STEP_X * RHS_STEP_LOOP;
+ rhs_offset_x += RHS_STEP_LOOP;
}
+
+#if((K % K0) != 0)
+
// Left-over accumulations
for(; i < K; ++i)
{
+ TILE(DATA_TYPE, M0, 1, a);
+ TILE(DATA_TYPE, N0, 1, b);
+
// Load values from LHS matrix
- LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs);
+ T_LOAD(DATA_TYPE, M0, 1, BUFFER, lhs, i, lhs_y, 1, lhs_stride_y, a);
- // Load values from RHS reshaped matrix
- LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs);
+ LOOP_UNROLLING(int, _i, 0, 1, N0,
+ {
+ b[_i].v = *(__global DATA_TYPE *)(rhs_ptr + rhs_offset_first_element_in_bytes + rhs_offset_x + rhs_offset_y + _i * RHS_STEP_X);
+ })
- ARM_MM_K0XN0XM0(M0, N0, 1, a, b, c);
- lhs_offset += 1;
- rhs_offset += 1;
+ T_MMUL(DATA_TYPE, DATA_TYPE, ACC_DATA_TYPE, M0, N0, 1, NT, T, a, b, c);
+
+ rhs_offset_x += 1;
}
- // Result of MM is of type DATA_TYPE
- __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y);
+#endif // ((K % K0) != 0)
- REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0;
+#if defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
-#if defined(REINTERPRET_OUTPUT_AS_3D)
- // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D
- CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y);
+ TILE(int, M0, N0, c_int);
+ TILE(int, M0, N0, offset_s32);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ offset_s32[i].v = (VEC_DATA_TYPE(int, N0))K_OFFSET;
+ })
- // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we
- // multiply dst_stride_z by DEPTH_GEMM3D
- dst_addr += z * dst_stride_z * DEPTH_GEMM3D;
-
-#else // defined(REINTERPRET_OUTPUT_AS_3D)
-
- // Add offset for batched GEMM
- dst_addr += z * dst_stride_z;
-
-#endif // defined(REINTERPRET_OUTPUT_AS_3D)
-
- // Convert result of matrix multiplication to S32
- REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(int, N0), c, c_int);
-
- // Offset contribution: c += (A_OFFSET * sum_col) + (B_OFFSET * sum_row) + K_OFFSET;
- REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(int, N0), offset_s32_, K_OFFSET);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c_int[i].v = CONVERT_SAT(c[i].v, VEC_DATA_TYPE(int, N0));
+ })
#if defined(A_OFFSET)
- // Compute the offset contribution due to A_OFFSET
- __global uchar *sum_col_addr = sum_col_ptr + sum_col_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int);
#if defined(SUM_COL_HAS_BATCHES)
- sum_col_addr += z * sum_col_stride_y;
+ int sum_col_y = z;
+#else // defined(SUM_COL_HAS_BATCHES)
+ int sum_col_y = 0;
#endif // defined(SUM_COL_HAS_BATCHES)
- VEC_DATA_TYPE(int, N0)
- a_offset_s32 = VLOAD(N0)(0, (__global int *)sum_col_addr);
- a_offset_s32 *= (VEC_DATA_TYPE(int, N0))A_OFFSET;
+ TILE(int, 1, N0, a_offset_s32);
- REPEAT_ADD_VECTOR_TO_VAR(M0, offset_s32_, a_offset_s32);
+ T_LOAD(int, 1, N0, BUFFER, sum_col, xo, sum_col_y, 1, sum_col_stride_y, a_offset_s32);
+
+ a_offset_s32[0].v *= A_OFFSET;
+
+ T_ADD_BROADCAST_X(int, M0, 1, offset_s32, a_offset_s32, offset_s32);
#endif // defined(A_OFFSET)
#if defined(B_OFFSET)
@@ -892,68 +711,93 @@
// Note: The sum_row tensor is generated through CLGEMMLowpMatrixAReductionKernel which
// does not introduce paddings. For this reason is safe to access the tensor in this manner
// without considering that the coordinate "y" could come from an input 3D tensor
- __global uchar *sum_row_addr = sum_row_ptr + sum_row_offset_first_element_in_bytes + (COMPUTE_M0_START_ROW(y, (uint)M0, PARTIAL_STORE_M0)) * sizeof(int) + z * sum_row_stride_y;
+ TILE(int, M0, N0, b_offset_s32);
- LOAD_SCALAR_AS_VECTOR(M0, N0, int, b_offset_s32_, sum_row_addr, 0, sum_row_stride_x);
+ T_LOAD(int, M0, 1, BUFFER, sum_row, y + z * (sum_row_stride_y / sizeof(int)), 0, 1, sum_row_stride_x, b_offset_s32);
- REPEAT_MLA_VAR_WITH_CONST_VEC(M0, offset_s32_, b_offset_s32_, (VEC_DATA_TYPE(int, N0))B_OFFSET);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ offset_s32[i].v += b_offset_s32[i].v *B_OFFSET;
+ })
+
#endif // defined(B_OFFSET)
#if defined(ADD_BIAS)
- // Add bias
- __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int);
- VEC_DATA_TYPE(int, N0)
- bias_values = VLOAD(N0)(0, (__global int *)bias_addr);
- REPEAT_ADD_VECTOR_TO_VAR(M0, offset_s32_, bias_values);
+ TILE(int, 1, N0, bias);
+
+ T_LOAD(int, 1, N0, BUFFER, biases, xo, 0, 1, 0, bias);
+
+ T_ADD_BROADCAST_X(ACC_DATA_TYPE, M0, 1, offset_s32, bias, offset_s32);
#endif // defined(ADD_BIAS)
- REPEAT_ADD_TWO_VARS(M0, c_int, offset_s32_);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c_int[i].v += offset_s32[i].v;
+ })
+
+ TILE(DATA_TYPE, M0, N0, c_lp);
// Multiply by result_mult_int and shift
#if defined(PER_CHANNEL_QUANTIZATION)
- __global uchar *result_multipliers_addr = result_multipliers_ptr + result_multipliers_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int);
- __global uchar *result_shifts_addr = result_shifts_ptr + result_shifts_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int);
+ TILE(int, 1, N0, res_mul);
+ TILE(int, 1, N0, res_shift);
- VEC_DATA_TYPE(int, N0)
- res_mul = VLOAD(N0)(0, (__global int *)result_multipliers_addr);
- VEC_DATA_TYPE(int, N0)
- res_shift = VLOAD(N0)(0, (__global int *)result_shifts_addr);
+ T_LOAD(int, 1, N0, BUFFER, result_multipliers, xo, 0, 0, 0, res_mul);
+ T_LOAD(int, 1, N0, BUFFER, result_shifts, xo, 0, 0, 0, res_shift);
- REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_PER_CHANNEL(M0, N0, c_int, res_mul, res_shift);
-#else // defined(PER_CHANNEL_QUANTIZATION)
-
-#if RESULT_SHIFT < 0
- REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(M0, N0, c_int, RESULT_MULTIPLIER, RESULT_SHIFT);
-#else // RESULT_SHIFT >= 0
- REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(M0, N0, c_int, RESULT_MULTIPLIER, RESULT_SHIFT);
-#endif // RESULT_SHIFT < 0
-
+ T_QUANTIZE8(int, DATA_TYPE, PER_CHANNEL, M0, N0, RESULT_OFFSET, RESULT_SHIFT, RESULT_MULTIPLIER, c_int, res_mul, res_shift, c_lp);
+#else // defined(PER_CHANNEL_QUANTIZATION)
+ T_QUANTIZE8(int, DATA_TYPE, PER_TENSOR, M0, N0, RESULT_OFFSET, RESULT_SHIFT, RESULT_MULTIPLIER, c_int, 0, 0, c_lp);
#endif // defined(PER_CHANNEL_QUANTIZATION)
- // Add the offset terms to GEMM's result
- REPEAT_ADD_CONST_TO_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, RESULT_OFFSET);
-
#if defined(MIN_BOUND)
- REPEAT_MAX_CONST_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, MIN_BOUND);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c_lp[i].v = max(c_lp[i].v, (VEC_DATA_TYPE(DATA_TYPE, N0))MIN_BOUND);
+ })
#endif // defined(MIN_BOUND)
#if defined(MAX_BOUND)
- REPEAT_MIN_CONST_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, MAX_BOUND);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c_lp[i].v = min(c_lp[i].v, (VEC_DATA_TYPE(DATA_TYPE, N0))MAX_BOUND);
+ })
#endif // defined(MAX_BOUND)
- // Convert and store output block
- const bool cond_y = y == 0;
- const bool cond_x = ((x + 1) * N0 >= N);
+#else // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+ TILE(int, M0, N0, c_lp);
- // Store output block
- REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c_int, c_lp);
- STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x);
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+ c_lp[i].v = CONVERT_SAT(c[i].v, VEC_DATA_TYPE(int, N0));
+ })
+#endif // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
-#undef RHS_BLOCK_SIZE
+ TILE(uint, M0, 1, dst_indirect_y);
+
+ LOOP_UNROLLING(int, i, 0, 1, M0,
+ {
+#if defined(REINTERPRET_OUTPUT_AS_3D)
+ dst_indirect_y[i].v = (uint)min((int)((y + i) % HEIGHT_GEMM3D), (int)HEIGHT_GEMM3D - 1);
+ dst_indirect_y[i].v += (uint)min((int)((y + i) / HEIGHT_GEMM3D), (int)DEPTH_GEMM3D - 1) * FULL_DST_HEIGHT;
+ dst_indirect_y[i].v += z *FULL_DST_HEIGHT *DEPTH_GEMM3D;
+#else // (REINTERPRET_OUTPUT_AS_3D)
+ dst_indirect_y[i].v = (uint)min((int)y + i, (int)M - 1) + z *FULL_DST_HEIGHT;
+#endif // defined(REINTERPRET_OUTPUT_AS_3D)
+ })
+
+ const bool cond_x = (xo > (N - N0));
+
+#if defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+ T_STORE_INDIRECT_WIDTH_SELECT(DATA_TYPE, M0, N0, PARTIAL_STORE_N0, BUFFER, dst, xo, dst_stride_y, cond_x, c_lp, dst_indirect_y);
+#else // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+ T_STORE_INDIRECT_WIDTH_SELECT(int, M0, N0, PARTIAL_STORE_N0, BUFFER, dst, xo, dst_stride_y, cond_x, c_lp, dst_indirect_y);
+#endif // defined(FUSED_OUTPUT_STAGE_FIXED_POINT)
+
#undef RHS_OFFSET_X
#undef RHS_STEP_X
+#undef RHS_STEP_LOOP
}
-#endif // defined(RESULT_OFFSET) && defined(RESULT_SHIFT) && defined(RESULT_MULTIPLIER)
#endif // defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0)
#if defined(M0) && defined(N0) && defined(K0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0)
diff --git a/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h b/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h
index 7ab068c..b87b2fa 100644
--- a/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h
+++ b/tests/datasets/GEMMLowpFusedOffsetOutputDataset.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -167,10 +167,10 @@
public:
SmallGEMMLowpFusedOffsetOutputUint8Dataset()
{
- add_config(TensorShape(21U, 13U), TensorShape(1U, 21U), TensorShape(1U, 13U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 13, 10, 210));
- add_config(TensorShape(52U, 13U), TensorShape(33U, 52U), TensorShape(33U, 13U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 100, 2, 13, 10, 210));
- add_config(TensorShape(31U, 27U), TensorShape(23U, 31U), TensorShape(23U, 27U), 18, 23, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 200, 2, 13, 10, 210));
- add_config(TensorShape(32U, 72U), TensorShape(16U, 32U), TensorShape(16U, 72U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 13, 10, 210));
+ add_config(TensorShape(21U, 13U), TensorShape(1U, 21U), TensorShape(1U, 13U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
+ add_config(TensorShape(52U, 13U), TensorShape(33U, 52U), TensorShape(33U, 13U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 100, 2, 13, 10, 210));
+ add_config(TensorShape(31U, 27U), TensorShape(23U, 31U), TensorShape(23U, 27U), 18, 23, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 200, 2, 13, 10, 210));
+ add_config(TensorShape(32U, 72U), TensorShape(16U, 32U), TensorShape(16U, 72U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
add_config(TensorShape(21U, 1U), TensorShape(43U, 21U), TensorShape(43U, 1U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601600, 10, 10, 210));
add_config(TensorShape(31U, 3U), TensorShape(72U, 31U), TensorShape(72U, 3U), -2, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 0, 254601600, 10, 10, 210));
@@ -179,6 +179,38 @@
}
};
+class SmallGEMMLowpFusedOffsetOutputOutput3DUint8Dataset final : public GEMMLowpFusedOffsetOutputDataset
+{
+public:
+ SmallGEMMLowpFusedOffsetOutputOutput3DUint8Dataset()
+ {
+ add_config(TensorShape(21U, 1421U, 33U), TensorShape(34U, 21U), TensorShape(34U, 7U, 203U, 33U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
+ add_config(TensorShape(31U, 102U, 55U), TensorShape(23U, 31U), TensorShape(23U, 1U, 102U, 55U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 100, 2, 13, 10, 210));
+ add_config(TensorShape(38U, 1200U, 77U), TensorShape(21U, 38U), TensorShape(21U, 4U, 300U, 77U), 18, 23, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 200, 2, 13, 10, 210));
+ add_config(TensorShape(32U, 103U, 99U), TensorShape(17U, 32U), TensorShape(17U, 1U, 103U, 99U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
+ add_config(TensorShape(16U, 1600U, 111U), TensorShape(8U, 16U), TensorShape(8U, 8U, 200U, 111U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601600, 10, 10,
+ 210));
+ add_config(TensorShape(16U, 1600U, 113U), TensorShape(8U, 16U), TensorShape(8U, 8U, 200U, 113U), -2, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 0, 254601600, 10, 10,
+ 210));
+ }
+};
+
+class SmallGEMMLowpFusedOffsetOutputInputOutput3DUint8Dataset final : public GEMMLowpFusedOffsetOutputDataset
+{
+public:
+ SmallGEMMLowpFusedOffsetOutputInputOutput3DUint8Dataset()
+ {
+ add_config(TensorShape(21U, 7U, 203U, 33U), TensorShape(34U, 21U), TensorShape(34U, 7U, 203U, 33U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
+ add_config(TensorShape(31U, 1U, 102U, 55U), TensorShape(23U, 31U), TensorShape(23U, 1U, 102U, 55U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 100, 2, 13, 10, 210));
+ add_config(TensorShape(38U, 4U, 300U, 77U), TensorShape(21U, 38U), TensorShape(21U, 4U, 300U, 77U), 18, 23, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 200, 2, 13, 10, 210));
+ add_config(TensorShape(32U, 1U, 103U, 99U), TensorShape(17U, 32U), TensorShape(17U, 1U, 103U, 99U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 13, 10, 210));
+ add_config(TensorShape(16U, 8U, 200U, 111U), TensorShape(8U, 16U), TensorShape(8U, 8U, 200U, 111U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -2, 254601600, 10, 10,
+ 210));
+ add_config(TensorShape(16U, 8U, 200U, 113U), TensorShape(8U, 16U), TensorShape(8U, 8U, 200U, 113U), -2, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 0, 254601600, 10, 10,
+ 210));
+ }
+};
+
class SmallGEMMLowpFusedOffsetOutputInt8Dataset final : public GEMMLowpFusedOffsetOutputDataset
{
public:
@@ -214,10 +246,10 @@
public:
LargeGEMMLowpFusedOffsetOutputUint8Dataset()
{
- add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 18, 10, 210));
- add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 100, 2, 18, 10, 210));
- add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, 200, 2, 18, 10, 210));
- add_config(TensorShape(941U, 1011U), TensorShape(623U, 941U), TensorShape(623U, 1011U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN, -100, 2, 18, 10, 210));
+ add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 18, 10, 210));
+ add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 100, 2, 18, 10, 210));
+ add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 200, 2, 18, 10, 210));
+ add_config(TensorShape(941U, 1011U), TensorShape(623U, 941U), TensorShape(623U, 1011U), -9, 1, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -100, 2, 18, 10, 210));
add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, -1, 254601600, 15, 10, 210));
add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, OutputStageInfo(GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT, 1, 254601600, 15, 10, 210));
diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp
index 5a1971b..1c7446f 100644
--- a/tests/validation/CL/GEMMLowp.cpp
+++ b/tests/validation/CL/GEMMLowp.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2020 Arm Limited.
+ * Copyright (c) 2017-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -68,16 +68,44 @@
TEST_SUITE(FusedOffsetOutput)
TEST_SUITE(QASYMM8)
-using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
-FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::ALL, combine(datasets::SmallGEMMLowpFusedOffsetOutputUint8Dataset(),
- framework::dataset::make("DataType", { DataType::QASYMM8 })))
+using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture = GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore>;
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::ALL, combine(combine(datasets::SmallGEMMLowpFusedOffsetOutputUint8Dataset(),
+ framework::dataset::make("DataType", { DataType::QASYMM8 })),
+ framework::dataset::make("reshape_b_only_on_first_run", { true, false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_quant);
}
-FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeGEMMLowpFusedOffsetOutputUint8Dataset(),
- framework::dataset::make("DataType", { DataType::QASYMM8 })))
+TEST_SUITE(Output3D)
+using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputOutput3DUint8Fixture =
+ GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, false, true>;
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputOutput3DUint8Fixture, framework::DatasetMode::ALL,
+ combine(combine(datasets::SmallGEMMLowpFusedOffsetOutputOutput3DUint8Dataset(),
+ framework::dataset::make("DataType", { DataType::QASYMM8 })),
+ framework::dataset::make("reshape_b_only_on_first_run", { true, false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_quant);
+}
+TEST_SUITE_END() // Output3D
+
+TEST_SUITE(InputOutput3D)
+using CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputInputOutput3DUint8Fixture =
+ GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<CLTensor, CLAccessor, CLGEMMLowpMatrixMultiplyCore, true, true>;
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputInputOutput3DUint8Fixture, framework::DatasetMode::ALL,
+ combine(combine(datasets::SmallGEMMLowpFusedOffsetOutputInputOutput3DUint8Dataset(),
+ framework::dataset::make("DataType", { DataType::QASYMM8 })),
+ framework::dataset::make("reshape_b_only_on_first_run", { true, false })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_quant);
+}
+TEST_SUITE_END() // InputOutput3D
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpMatrixMultiplyCoreFusedOffsetOutputUint8Fixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeGEMMLowpFusedOffsetOutputUint8Dataset(),
+ framework::dataset::make("DataType", { DataType::QASYMM8 })),
+ framework::dataset::make("reshape_b_only_on_first_run", { true, false })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_quant);
diff --git a/tests/validation/fixtures/GEMMLowpFixture.h b/tests/validation/fixtures/GEMMLowpFixture.h
index 5cf210b..ab9d35d 100644
--- a/tests/validation/fixtures/GEMMLowpFixture.h
+++ b/tests/validation/fixtures/GEMMLowpFixture.h
@@ -97,7 +97,7 @@
template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d, bool reinterpret_output_as_3d, typename OutputType, bool is_fused = false>
TensorType compute_gemmlowp_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
GEMMLowpOutputStageInfo output_stage = GEMMLowpOutputStageInfo(), DataType data_type_a = DataType::QASYMM8, DataType data_type_b = DataType::QASYMM8,
- QuantizationInfo b_qinfo = QuantizationInfo())
+ QuantizationInfo b_qinfo = QuantizationInfo(), bool reshape_b_only_on_first_run = false)
{
// Create tensors
DataType data_type_output = output_stage.type == GEMMLowpOutputStageType::NONE ? DataType::S32 : data_type_a;
@@ -126,7 +126,8 @@
// Create and configure function
// The GEMMinfo includes the values of the depth in case of reinterpreted 3d input/output
FunctionType gemmlowp;
- gemmlowp.configure(&a, &b, is_fused ? &bias : nullptr, &output, GEMMInfo(false, false, false, (reinterpret_output_as_3d ? shape_output[2] : 0), reinterpret_input_as_3d, false, output_stage));
+ gemmlowp.configure(&a, &b, is_fused ? &bias : nullptr, &output, GEMMInfo(false, false, reshape_b_only_on_first_run, (reinterpret_output_as_3d ? shape_output[2] : 0), reinterpret_input_as_3d, false,
+ output_stage));
ARM_COMPUTE_ASSERT(a.info()->is_resizable());
ARM_COMPUTE_ASSERT(b.info()->is_resizable());
@@ -208,11 +209,12 @@
};
template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TI = uint8_t, typename TW = uint8_t>
-class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public framework::Fixture
+class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b)
+ void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b,
+ bool reshape_b_only_on_first_run)
{
ARM_COMPUTE_ASSERT(output_stage.type != GEMMLowpOutputStageType::NONE);
DataType data_type_a = data_type_b == DataType::QASYMM8_SIGNED ? DataType::QASYMM8_SIGNED : DataType::QASYMM8;
@@ -232,21 +234,21 @@
}
_reference = compute_reference(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
- _target = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales));
+ _target = compute_target(shape_a, shape_b, shape_output, a_offset, 0, output_stage, data_type_a, data_type_b, QuantizationInfo(scales), reshape_b_only_on_first_run);
}
else
{
_reference = compute_reference(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
- _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo());
+ _target = compute_target(shape_a, shape_b, shape_output, a_offset, b_offset, output_stage, data_type_a, data_type_b, QuantizationInfo(), reshape_b_only_on_first_run);
}
}
protected:
TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage,
- DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo)
+ DataType data_type_a, DataType data_type_b, QuantizationInfo b_qinfo, bool reshape_b_only_on_first_run = false)
{
return compute_gemmlowp_target<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, qasymm8_t, true>(shape_a, shape_b, shape_output, a_offset, b_offset,
- output_stage, data_type_a, data_type_b, b_qinfo);
+ output_stage, data_type_a, data_type_b, b_qinfo, reshape_b_only_on_first_run);
}
SimpleTensor<TI> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_output, int32_t a_offset, int32_t b_offset,
@@ -277,6 +279,19 @@
SimpleTensor<TI> _reference{};
};
+template <typename TensorType, typename AccessorType, typename FunctionType, bool reinterpret_input_as_3d = false, bool reinterpret_output_as_3d = false, typename TI = uint8_t, typename TW = uint8_t>
+class GEMMLowpMatrixMultiplyCoreFusedOffsetOutputValidationFixture : public
+ GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, TI, TW>
+{
+public:
+ template <typename...>
+ void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_output, int32_t a_offset, int32_t b_offset, GEMMLowpOutputStageInfo output_stage, DataType data_type_b)
+ {
+ GEMMLowpMatrixMultiplyCoreFusedOffsetOutputGenericValidationFixture<TensorType, AccessorType, FunctionType, reinterpret_input_as_3d, reinterpret_output_as_3d, TI, TW>::setup(shape_a, shape_b,
+ shape_output, a_offset, b_offset, output_stage, data_type_b, false);
+ }
+};
+
template <typename TensorType, typename AccessorType, typename FunctionType>
class GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture : public framework::Fixture
{