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-rw-r--r--src/core/CL/CLKernelLibrary.cpp2
-rw-r--r--src/core/CL/cl_kernels/direct_convolution.cl616
-rw-r--r--src/core/CL/cl_kernels/tile_helpers.h420
-rw-r--r--src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp27
-rw-r--r--tests/validation/CL/DirectConvolutionLayer.cpp4
5 files changed, 584 insertions, 485 deletions
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 14d3a2cad5..726efa3575 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -547,7 +547,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map =
{
"convert_fc_weights.cl",
#include "./cl_kernels/convert_fc_weights.clembed"
- },
+ },
{
"convolution_layer.cl",
#include "./cl_kernels/convolution_layer.clembed"
diff --git a/src/core/CL/cl_kernels/direct_convolution.cl b/src/core/CL/cl_kernels/direct_convolution.cl
index 5d2a24e740..1de3737965 100644
--- a/src/core/CL/cl_kernels/direct_convolution.cl
+++ b/src/core/CL/cl_kernels/direct_convolution.cl
@@ -21,375 +21,12 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#include "gemm_helpers.h"
-#include "helpers_asymm.h"
-#include "repeat.h"
-
-#if defined(IS_QUANTIZED)
-
-#if defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
-#define ARM_DOT(x, y, val) val = arm_dot_acc((x), (y), (val));
-#elif defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
-#define ARM_DOT(x, y, val) val += arm_dot((x), (y));
-#else // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
-#define ARM_DOT(x, y, val) \
- ({ \
- val += (ACC_DATA_TYPE)x.s0 * (ACC_DATA_TYPE)y.s0; \
- val += (ACC_DATA_TYPE)x.s1 * (ACC_DATA_TYPE)y.s1; \
- val += (ACC_DATA_TYPE)x.s2 * (ACC_DATA_TYPE)y.s2; \
- val += (ACC_DATA_TYPE)x.s3 * (ACC_DATA_TYPE)y.s3; \
- })
-#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
-
-#define ARM_DOT1(a, b, c) \
- ({ \
- ARM_DOT(((VEC_DATA_TYPE(SRC_DATA_TYPE, 4))(a, (VEC_DATA_TYPE(SRC_DATA_TYPE, 3))0)), ((VEC_DATA_TYPE(WEI_DATA_TYPE, 4))(b, (VEC_DATA_TYPE(WEI_DATA_TYPE, 3))0)), c); \
- })
-#define ARM_DOT2(a, b, c) \
- ({ \
- ARM_DOT(((VEC_DATA_TYPE(SRC_DATA_TYPE, 4))(a, (VEC_DATA_TYPE(SRC_DATA_TYPE, 2))0)), ((VEC_DATA_TYPE(WEI_DATA_TYPE, 4))(b, (VEC_DATA_TYPE(WEI_DATA_TYPE, 2))0)), c); \
- })
-#define ARM_DOT3(a, b, c) \
- ({ \
- ARM_DOT(((VEC_DATA_TYPE(SRC_DATA_TYPE, 4))(a, (SRC_DATA_TYPE)0)), ((VEC_DATA_TYPE(WEI_DATA_TYPE, 4))(b, (WEI_DATA_TYPE)0)), c); \
- })
-#define ARM_DOT4(a, b, c) \
- ({ \
- ARM_DOT(a, b, c); \
- })
-#define ARM_DOT8(a, b, c) \
- ({ \
- ARM_DOT4((a.lo), (b.lo), c); \
- ARM_DOT4((a.hi), (b.hi), c); \
- })
-#define ARM_DOT16(a, b, c) \
- ({ \
- ARM_DOT8((a.lo), (b.lo), c); \
- ARM_DOT8((a.hi), (b.hi), c); \
- })
-
-#define ARM_OFFSET1(a, b, c) \
- ({ \
- c += (ACC_DATA_TYPE)a * (ACC_DATA_TYPE)b; \
- })
-#define ARM_OFFSET2(a, b, c) \
- ({ \
- c += (ACC_DATA_TYPE)a.s0 * (ACC_DATA_TYPE)b; \
- c += (ACC_DATA_TYPE)a.s1 * (ACC_DATA_TYPE)b; \
- })
-#define ARM_OFFSET3(a, b, c) \
- ({ \
- ARM_OFFSET2(a, b, c); \
- c += (ACC_DATA_TYPE)a.s2 * (ACC_DATA_TYPE)b; \
- })
-#define ARM_OFFSET4(a, b, c) \
- ({ \
- ARM_OFFSET3(a, b, c); \
- c += (ACC_DATA_TYPE)a.s3 * (ACC_DATA_TYPE)b; \
- })
-#define ARM_OFFSET8(a, b, c) \
- ({ \
- ARM_OFFSET4((a.lo), (b), c); \
- ARM_OFFSET4((a.hi), (b), c); \
- })
-#define ARM_OFFSET16(a, b, c) \
- ({ \
- ARM_OFFSET8((a.lo), (b), c); \
- ARM_OFFSET8((a.hi), (b), c); \
- })
-
-#if N0 == 1
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c)); \
- })
-#elif N0 == 2 // N) == 3
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##1), (a_offset), (c.s1)); \
- })
-#elif N0 == 3 // N0 == 3
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##1), (a_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##2), (a_offset), (c.s2)); \
- })
-#elif N0 == 4 // N0 == 4
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##1), (a_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##2), (a_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s3)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##3), (a_offset), (c.s3)); \
- })
-#elif N0 == 8 // N0 == 8
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##1), (a_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##2), (a_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s3)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##3), (a_offset), (c.s3)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s4)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##4), (a_offset), (c.s4)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s5)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##5), (a_offset), (c.s5)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s6)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##6), (a_offset), (c.s6)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s7)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##7), (a_offset), (c.s7)); \
- })
-#elif N0 == 16 // N0 == 16
-#define ARM_OFFSET_K0XN0(k0, a, b, a_offset, b_offset, c) \
- ({ \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##0), (a_offset), (c.s0)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##1), (a_offset), (c.s1)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##2), (a_offset), (c.s2)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s3)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##3), (a_offset), (c.s3)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s4)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##4), (a_offset), (c.s4)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s5)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##5), (a_offset), (c.s5)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s6)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##6), (a_offset), (c.s6)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s7)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##7), (a_offset), (c.s7)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s8)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##8), (a_offset), (c.s8)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.s9)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##9), (a_offset), (c.s9)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sA)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##A), (a_offset), (c.sA)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sB)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##B), (a_offset), (c.sB)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sC)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##C), (a_offset), (c.sC)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sD)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##D), (a_offset), (c.sD)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sE)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##E), (a_offset), (c.sE)); \
- CONCAT(ARM_OFFSET, k0) \
- ((a), (b_offset), (c.sF)); \
- CONCAT(ARM_OFFSET, k0) \
- ((b##F), (a_offset), (c.sF)); \
- })
-#else // N0 not supported
-#error "N0 value not supported"
-#endif // N0 conditions
-#else // defined(IS_QUANTIZED)
-
-#define ARM_DOT1(a, b, c) \
- ({ \
- c += (ACC_DATA_TYPE)a * (ACC_DATA_TYPE)b; \
- })
-#define ARM_DOT2(a, b, c) \
- ({ \
- c += (ACC_DATA_TYPE)a.s0 * (ACC_DATA_TYPE)b.s0; \
- c += (ACC_DATA_TYPE)a.s1 * (ACC_DATA_TYPE)b.s1; \
- })
-#define ARM_DOT3(a, b, c) \
- ({ \
- ARM_DOT2(a, b, c); \
- c += (ACC_DATA_TYPE)a.s2 * (ACC_DATA_TYPE)b.s2; \
- })
-#define ARM_DOT4(a, b, c) \
- ({ \
- ARM_DOT3(a, b, c); \
- c += (ACC_DATA_TYPE)a.s3 * (ACC_DATA_TYPE)b.s3; \
- })
-#define ARM_DOT8(a, b, c) \
- ({ \
- ARM_DOT4((a.lo), (b.lo), c); \
- ARM_DOT4((a.hi), (b.hi), c); \
- })
-#define ARM_DOT16(a, b, c) \
- ({ \
- ARM_DOT8((a.lo), (b.lo), c); \
- ARM_DOT8((a.hi), (b.hi), c); \
- })
-#endif // defined(IS_QUANTIZED)
-#if N0 == 1
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c)); \
- })
-#elif N0 == 2 // N) == 3
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c.s0)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##1), (c.s1)); \
- })
-#elif N0 == 3 // N0 == 3
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c.s0)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##1), (c.s1)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##2), (c.s2)); \
- })
-#elif N0 == 4 // N0 == 4
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c.s0)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##1), (c.s1)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##2), (c.s2)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##3), (c.s3)); \
- })
-#elif N0 == 8 // N0 == 8
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c.s0)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##1), (c.s1)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##2), (c.s2)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##3), (c.s3)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##4), (c.s4)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##5), (c.s5)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##6), (c.s6)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##7), (c.s7)); \
- })
-#elif N0 == 16 // N0 == 16
-#define ARM_DOT_K0XN0(k0, a, b, c) \
- ({ \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##0), (c.s0)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##1), (c.s1)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##2), (c.s2)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##3), (c.s3)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##4), (c.s4)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##5), (c.s5)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##6), (c.s6)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##7), (c.s7)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##8), (c.s8)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##9), (c.s9)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##A), (c.sA)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##B), (c.sB)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##C), (c.sC)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##D), (c.sD)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##E), (c.sE)); \
- CONCAT(ARM_DOT, k0) \
- ((a), (b##F), (c.sF)); \
- })
-#else // N0 not supported
-#error "N0 value not supported"
-#endif // N0 conditions
+#include "helpers.h"
+#include "helpers_asymm.h"
+#include "tile_helpers.h"
+//! @cond Doxygen_Suppress
/** OpenCL kernel to compute the direct convolution.
*
* @note Data layout supported: NHWC
@@ -403,6 +40,9 @@
* @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH and -DDST_HEIGHT (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64)
* @note The channels of the source tensor must be passed at compile time using -DSRC_CHANNELS (e.g. -DSRC_CHANNELS=64)
* @note The channels of the destination tensor must be passed at compile time using -DDST_CHANNELS (e.g. -DDDST_CHANNELS=64)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the weights tensor must be passed at compile time using -DWEI_TENSOR_TYPE (e.g. -DWEI_TENSOR_TYPE=BUFFER)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER)
* @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float)
* @note The data type of the weights tensor must be passed at compile time using -DWEI_DATA_TYPE (e.g. -DWEI_DATA_TYPE=float)
* @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float)
@@ -410,12 +50,12 @@
* @note The number of M0 rows (width*height) to process must be passed at compile time using -DM0 (e.g. -DM0=2)
* @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note The number of K0 inner accumulations must be passed at compile time using -DK0 (e.g. -DK0=2)
- * @note The size of the partial store block in y must be passed at compile time using -DPARTIAL_STORE_M0 (e.g. -DPARTIAL_STORE_M0=1)
- * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_STORE_N0 (e.g. -DPARTIAL_STORE_N0=1)
+ * @note The size of the partial store block in x must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1)
+ * @note The zero value must be passed at compile time using -DZERO_VALUE (e.g. -DZERO_VALUE=0)
* @note Only the following configurations of M0, N0 and K0 are currently supported:
- * - M0 = 1
+ * - M0 = 1, 2, 3, 4, 5, .... n
* - N0 = 2, 3, 4, 8, 16
- * - K0 = 2, 3, 4, 8, 16
+ * - K0 = 2, 3, 4, 8, 16 (only 4, 8 and 16 if WEI_TENSOR_TYPE=IMAGE)
*
*@note In case of QASYMM8/QASYMM8_SIGNED, the following extra information must be passed at compile time:
* - -DIS_QUANTIZED
@@ -426,13 +66,15 @@
* - The weights offset e.g. -DWEI_OFFSET=4
* - The quantized zero value e.g. -DZERO_VALUE=4
*
- * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32
+ * @param[in] src_ptr Pointer to the source tensor. Supported data type: F16/F32/QASYMM8
* @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 type: same as @p src_ptr
* @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
@@ -441,6 +83,8 @@
* @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
+ * @param[in] dst_step_w dst_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
* @param[in] wei_ptr Pointer to the weights tensor. Supported data type: same as @p src_ptr
* @param[in] wei_stride_x Stride of the weights tensor in X dimension (in bytes)
@@ -449,156 +93,184 @@
* @param[in] wei_step_y wei_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] wei_stride_z Stride of the weights tensor in Z dimension (in bytes)
* @param[in] wei_step_z wei_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes)
+ * @param[in] wei_step_w wei_stride_w * number of elements along W processed per workitem(in bytes)
* @param[in] wei_offset_first_element_in_bytes The offset of the first element in the bias matrix
* @param[in] bia_ptr (Optional) Pointer to the bias tensor Supported data type: same as @p src_ptr (if F32/F16) or S32 (if QASYMM8/QASYMM8_SIGNED)
* @param[in] bia_stride_x (Optional) Stride of the bias tensor in X dimension (in bytes)
* @param[in] bia_step_x (Optional) bia_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] bia_offset_first_element_in_bytes (Optional) The offset of the first element in the bias matrix
- * @param[in] wei_stride_w Stride of the weights tensor in W dimension (in bytes)
*/
+//! @endcond
__kernel void direct_convolution_nhwc(
- TENSOR3D_DECLARATION(src),
- TENSOR3D_DECLARATION(dst),
- TENSOR3D_DECLARATION(wei),
+ TENSOR4D(src, SRC_TENSOR_TYPE),
+ TENSOR4D(dst, DST_TENSOR_TYPE),
+ TENSOR4D(wei, WEI_TENSOR_TYPE),
#if defined(HAS_BIAS)
- VECTOR_DECLARATION(bia),
+ VECTOR_DECLARATION(bia)
#endif // defined(HAS_BIAS)
- unsigned int wei_stride_w)
+)
{
-#if M0 != 1
-#error "M0: Only supported 1"
-#endif // M0 != 1
-
- const int cout = max((int)(get_global_id(0) * N0 - (N0 - PARTIAL_STORE_N0) % N0), 0); // input channels
- const int mout = get_global_id(1); // width x height
- const int zout = get_global_id(2); // batch size index
+ // All the tensor dimensions are passed at compile time.
+ // In case of dynamic tensor support, the following dimensions should be passed as function argument.
+#define _IWEI_WIDTH WEI_WIDTH
+#define _IWEI_HEIGHT WEI_HEIGHT
+#define _ISRC_WIDTH SRC_WIDTH
+#define _ISRC_HEIGHT SRC_HEIGHT
+#define _ISRC_CHANNELS SRC_CHANNELS
+#define _IDST_WIDTH DST_WIDTH
+#define _IDST_HEIGHT DST_HEIGHT
+#define _IDST_CHANNELS DST_CHANNELS
+
+ // If quantized, the output tile has to be quantized first before being stored to global memory
+#if defined(IS_QUANTIZED)
+#define _IOUTPUT_TILE cq
+#else // defined(IS_QUANTIZED)
+#define _IOUTPUT_TILE c
+#endif // defined(IS_QUANTIZED)
- REPEAT_VAR_INIT_TO_CONST(16, int, zero, 0);
- REPEAT_VAR_INIT_TO_CONST(M0, int, xi, 0);
- REPEAT_VAR_INIT_TO_CONST(M0, int, yi, 0);
+ const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM
+ const int mout = GET_SPATIAL_IDX(1, M0, 0); // WIDTH x HEIGHT
+ const int bout = GET_SPATIAL_IDX(2, 1, 0); // BATCH SIZE IDX
-#define LINEAR_2_COORDS(i) \
- xi##i = ((mout * M0 + i) % DST_WIDTH) * STRIDE_X; \
- yi##i = ((mout * M0 + i) / DST_WIDTH) * STRIDE_Y; \
- xi##i -= PAD_LEFT; \
- yi##i -= PAD_TOP;
+ // .v = access the whole vector (OpenCL vector)
+ // .s[x] = access the vector element at position x (scalar access)
+ TILE(int, M0, 1, xi) = { { 0 } };
+ TILE(int, M0, 1, yi) = { { 0 } };
// Convert the linear index to coordinate
- LINEAR_2_COORDS(0);
-
-#undef LINEAR_2_COORDS
+ LOOP_UNROLLING(int, i, 0, M0, 1)
+ {
+ xi[i].v = ((mout + i) % _IDST_WIDTH) * STRIDE_X;
+ yi[i].v = ((mout + i) / _IDST_WIDTH) * STRIDE_Y;
+ xi[i].v -= PAD_LEFT;
+ yi[i].v -= PAD_TOP;
+ }
- uint src_offset = src_offset_first_element_in_bytes + zout * src_stride_y * (SRC_WIDTH * SRC_HEIGHT);
- uint wei_offset = wei_offset_first_element_in_bytes + cout * wei_stride_w;
+ uint wei_x = 0;
// Initialize the accumulators
- REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0);
+ TILE(ACC_DATA_TYPE, M0, N0, c) = { { 0 } };
- for(int i = 0; i < (WEI_WIDTH * WEI_HEIGHT); ++i)
+ for(int i = 0; i < (_IWEI_WIDTH * _IWEI_HEIGHT); ++i)
{
- int xk = i % WEI_WIDTH;
- int yk = i / WEI_WIDTH;
-
- REPEAT_VAR_INIT_TO_CONST(M0, int, mi_valid_row, 0);
- REPEAT_VAR_INIT_TO_CONST(M0, int, mi_mask, 0);
+ uint src_x = 0;
+ int xk = i % _IWEI_WIDTH;
+ int yk = i / _IWEI_WIDTH;
- // Calculate the input row to read from source tensor
-#define MI_INIT(i) \
- mi_valid_row##i = max(min(xi##i + xk, SRC_WIDTH - 1), 0) + max(min(yi##i + yk, SRC_HEIGHT - 1), 0) * SRC_WIDTH; \
- mi_mask##i = (xi##i + xk) >= 0 && (xi##i + xk) < SRC_WIDTH && (yi##i + yk) >= 0 && (yi##i + yk) < SRC_HEIGHT;
+ TILE(int, M0, 1, src_indirect_y) = { { 0 } };
+ TILE(int, M0, 1, src_indirect_mask) = { { 0 } };
- MI_INIT(0);
-
-#undef MI_INIT
+ // Calculate the source indirect Y and the source indirect mask
+ // Since the indirect Y is clamped when out-of-bound, the mask is used to
+ // force to zero the out-of-bound values
+ LOOP_UNROLLING(int, i, 0, M0, 1)
+ {
+ src_indirect_y[i].v = (CLAMP(xi[i].v + xk, 0, (int)_ISRC_WIDTH - 1) + CLAMP(yi[i].v + yk, 0, (int)_ISRC_HEIGHT - 1) * _ISRC_WIDTH);
+ src_indirect_y[i].v += bout * (int)_ISRC_WIDTH * (int)_ISRC_HEIGHT;
+ src_indirect_mask[i].v = ((xi[i].v + xk) >= 0 && (xi[i].v + xk) < (int)_ISRC_WIDTH && (yi[i].v + yk) >= 0 && (yi[i].v + yk) < (int)_ISRC_HEIGHT);
+ }
int k = 0;
- for(; k <= (SRC_CHANNELS - K0); k += K0)
+ for(; k <= (_ISRC_CHANNELS - K0); k += K0)
{
- // Load values from src tensor
- LOAD_BLOCK_INDIRECT(M0, K0, SRC_DATA_TYPE, a, src_ptr, src_offset + k * sizeof(SRC_DATA_TYPE), src_stride_y, mi_valid_row, mi_mask);
+ TILE(SRC_DATA_TYPE, M0, K0, a);
+ TILE(WEI_DATA_TYPE, N0, K0, b);
- // Load values from weights tensor
- LOAD_BLOCK(N0, K0, WEI_DATA_TYPE, b, wei_ptr, wei_offset, wei_stride_w, zero);
+ // Load tile from the src tensor
+ T_LOAD_INDIRECT(SRC_DATA_TYPE, M0, K0, SRC_TENSOR_TYPE, src, src_x, src_stride_y, src_indirect_y, a);
-#if defined(IS_QUANTIZED)
-#define TENSOR_DOT(K0, i) \
- if(mi_mask##i != 0) \
- { \
- ARM_DOT_K0XN0(K0, a##i, b, c##i); \
- ARM_OFFSET_K0XN0(K0, a##i, b, SRC_OFFSET, WEI_OFFSET, c##i); \
- } \
- else \
- { \
- ARM_DOT_K0XN0(K0, ((VEC_DATA_TYPE(SRC_DATA_TYPE, K0))ZERO_VALUE), b, c##i); \
- ARM_OFFSET_K0XN0(K0, ((VEC_DATA_TYPE(SRC_DATA_TYPE, K0))ZERO_VALUE), b, SRC_OFFSET, WEI_OFFSET, c##i); \
- }
-#else // defined(IS_QUANTIZED)
-#define TENSOR_DOT(K0, i) \
- ARM_DOT_K0XN0(K0, a##i, b, c##i);
-#endif // defined(IS_QUANTIZED)
+ // Load tile from the weights tensor
+ T_LOAD(WEI_DATA_TYPE, N0, K0, WEI_TENSOR_TYPE, wei, wei_x, cout, wei_stride_w, b);
- TENSOR_DOT(K0, 0);
+ // Fill with zero the out-of-bound rows
+ T_ROWSET_MASK(SRC_DATA_TYPE, M0, K0, ZERO_VALUE, a, src_indirect_mask);
- wei_offset += K0 * sizeof(WEI_DATA_TYPE);
+ // Compute the matrix multiplication between two tiles
+ T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, K0, NT, T, a, b, c);
+
+ // Apply the offset correction (correction usually needed for asymmetric quantized computation)
+ // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero
+ T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, K0, SRC_OFFSET, WEI_OFFSET, a, b, c);
+
+ src_x += K0;
+ wei_x += K0;
}
-#if(SRC_CHANNELS % K0) != 0
+ // We voluntarily use SRC_CHANNELS rather than _DSRC_CHANNELS
+ // This #if directive should be removed in case of dynamic tensor support
+#if((SRC_CHANNELS % K0) != 0)
// Left-over accumulations
- for(; k < SRC_CHANNELS; ++k)
+ for(; k < _ISRC_CHANNELS; ++k)
{
- // Load values from src tensor
- LOAD_BLOCK_INDIRECT(M0, 1, SRC_DATA_TYPE, a, src_ptr, src_offset + k * sizeof(SRC_DATA_TYPE), src_stride_y, mi_valid_row, mi_mask);
+ TILE(SRC_DATA_TYPE, M0, 1, a);
+ TILE(WEI_DATA_TYPE, N0, 1, b);
- // Load values from weights tensor
- LOAD_BLOCK(N0, 1, WEI_DATA_TYPE, b, wei_ptr, wei_offset, wei_stride_w, zero);
+ // Load tile from the src tensor
+ T_LOAD_INDIRECT(SRC_DATA_TYPE, M0, 1, SRC_TENSOR_TYPE, src, src_x, src_stride_y, src_indirect_y, a);
- TENSOR_DOT(1, 0);
+ // Load tile from the weights tensor
+ T_LOAD(WEI_DATA_TYPE, N0, 1, WEI_TENSOR_TYPE, wei, wei_x, cout, wei_stride_w, b);
-#undef TENSOR_DOT
+ // Fill with zero the out-of-bound rows
+ T_ROWSET_MASK(SRC_DATA_TYPE, M0, 1, ZERO_VALUE, a, src_indirect_mask);
- wei_offset += sizeof(WEI_DATA_TYPE);
- }
-#endif // (SRC_CHANNELS % K0) != 0
+ // Compute the matrix multiplication between two tiles
+ T_MMUL(SRC_DATA_TYPE, WEI_DATA_TYPE, ACC_DATA_TYPE, M0, N0, 1, NT, T, a, b, c);
- c0 += (SRC_CHANNELS * SRC_OFFSET * WEI_OFFSET);
- }
+ // Apply the offset correction (operation usually needed for asymmetric quantized computation)
+ // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero
+ T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, 1, SRC_OFFSET, WEI_OFFSET, a, b, c);
- __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (cout * sizeof(DST_DATA_TYPE)) + (mout * M0 * dst_stride_y);
+ ++src_x;
+ ++wei_x;
+ }
+#endif // ((SRC_CHANNELS % K0) != 0)
+ }
- // Batched direct convolution
- dst_addr += zout * dst_stride_y * (DST_WIDTH * DST_HEIGHT);
+ // Offset correction required for the quantized asymmetric computation
+ // The computation is not performed if both SRC_OFFSET and WEI_OFFSET are zero
+ T_ADD_CONSTANT(ACC_DATA_TYPE, M0, N0, c, (_IWEI_WIDTH * _IWEI_HEIGHT * _ISRC_CHANNELS * SRC_OFFSET * WEI_OFFSET), c);
#if defined(HAS_BIAS)
- __global uchar *bias_addr = bia_ptr + bia_offset_first_element_in_bytes + (cout * sizeof(BIA_DATA_TYPE));
+ TILE(BIA_DATA_TYPE, 1, N0, bias0);
- LOAD_BLOCK(1, N0, BIA_DATA_TYPE, bias, bias_addr, 0, zero0, zero);
+ T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout, 0, 0, bias0);
// c = c + bias[broadcasted]
- ADD_BLOCK_BROADCAST(M0, c, bias0);
+ T_ADD_BROADCAST_X(ACC_DATA_TYPE, M0, N0, c, bias0, c);
+
#endif // HAS_BIAS
-#if defined(IS_QUANTIZED)
+ TILE(uint, M0, 1, dst_indirect_y);
- REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DST_DATA_TYPE, N0), cq, 0);
+ // Calculate the destination indirect Y
+ LOOP_UNROLLING(int, i, 0, M0, 1)
+ {
+ dst_indirect_y[i].v = (uint)min(mout + i, (int)(_IDST_WIDTH * _IDST_HEIGHT) - 1);
+ dst_indirect_y[i].v += bout * (int)(_IDST_WIDTH * _IDST_HEIGHT);
+ }
-#if DST_SHIFT < 0
-#define QUANTIZE(i) \
- c##i = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(c##i, DST_MULTIPLIER, DST_SHIFT, N0); \
- c##i = c##i + DST_OFFSET; \
- cq##i = CONVERT_SAT(c##i, VEC_DATA_TYPE(DST_DATA_TYPE, N0));
-#else // OUTPUT_SHIFT < 0
-#define QUANTIZE(i) \
- c##i = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(c##i, DST_MULTIPLIER, DST_SHIFT, N0); \
- c##i = c##i + DST_OFFSET; \
- cq##i = CONVERT_SAT(c##i, VEC_DATA_TYPE(DST_DATA_TYPE, N0));
-#endif // OUTPUT_SHIFT < 0
+ bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0;
- QUANTIZE(0);
+#if defined(IS_QUANTIZED)
-#undef QUANTIZE
+ TILE(DST_DATA_TYPE, M0, N0, cq);
- STORE_VECTOR_SELECT(cq, DST_DATA_TYPE, dst_addr, N0, PARTIAL_STORE_N0, PARTIAL_STORE_N0 != 0 && get_global_id(0) == 0);
-#else // defined(IS_QUANTIZED)
- STORE_VECTOR_SELECT(c, DST_DATA_TYPE, dst_addr, N0, PARTIAL_STORE_N0, PARTIAL_STORE_N0 != 0 && get_global_id(0) == 0);
+ // Quantize the tile
+ T_QUANTIZE8_ASYMMETRIC(ACC_DATA_TYPE, DST_DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, cq);
#endif // defined(IS_QUANTIZED)
+
+ // _IOUTPUT_TILE: c = fp32/fp16, cq=qasymm8
+ // Store the tile in reverse order so the invalid values are overwritten with the valid ones
+ T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, M0, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, _IOUTPUT_TILE, dst_indirect_y);
+
+#undef _IWEI_WIDTH
+#undef _IWEI_HEIGHT
+#undef _ISRC_WIDTH
+#undef _ISRC_HEIGHT
+#undef _ISRC_CHANNELS
+#undef _IDST_WIDTH
+#undef _IDST_HEIGHT
+#undef _IDST_CHANNELS
} \ No newline at end of file
diff --git a/src/core/CL/cl_kernels/tile_helpers.h b/src/core/CL/cl_kernels/tile_helpers.h
new file mode 100644
index 0000000000..19241cf219
--- /dev/null
+++ b/src/core/CL/cl_kernels/tile_helpers.h
@@ -0,0 +1,420 @@
+/*
+ * Copyright (c) 2021 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.
+ */
+
+/** Tile object
+ * A tile object is a 2D memory block and can be accessed using the following syntax:
+ * -# a[m0].v = access the the vector at row "m0" (OpenCL vector)
+ * -# a[m0].s[x] = access the scalar element at row "m0" and column "n0" (scalar access)
+ *
+ * @param[in] DATA_TYPE Data type of the tile
+ * @param[in] H Number of tile rows
+ * @param[in] W Number of tile colums
+ * @param[in] BASENAME Tile's name
+ */
+#define TILE(DATA_TYPE, H, W, BASENAME) TILE_STR(DATA_TYPE, H, W, BASENAME)
+#define TILE_STR(DATA_TYPE, H, W, BASENAME) \
+ union { \
+ DATA_TYPE s[W]; \
+ DATA_TYPE##W v; \
+ } BASENAME[H]
+
+#define TENSOR4D_IMAGE(name) \
+ __read_only image2d_t name##_img, \
+ __global uchar *name##_ptr, \
+ uint name##_stride_x, \
+ uint name##_step_x, \
+ uint name##_stride_y, \
+ uint name##_step_y, \
+ uint name##_stride_z, \
+ uint name##_step_z, \
+ uint name##_stride_w, \
+ uint name##_step_w, \
+ uint name##_offset_first_element_in_bytes
+
+#define TENSOR4D_BUFFER(name) \
+ __global uchar *name##_ptr, \
+ uint name##_stride_x, \
+ uint name##_step_x, \
+ uint name##_stride_y, \
+ uint name##_step_y, \
+ uint name##_stride_z, \
+ uint name##_step_z, \
+ uint name##_stride_w, \
+ uint name##_step_w, \
+ uint name##_offset_first_element_in_bytes
+
+#define TENSOR4D_STR(name, type) TENSOR4D_##type(name)
+#define TENSOR4D(name, type) TENSOR4D_STR(name, type)
+
+/** Loop unrolling */
+#define LOOP_UNROLLING(DATA_TYPE, VAR, START_IDX, NUM_ITERATIONS, STEP) \
+ _Pragma("unroll") for(DATA_TYPE VAR = START_IDX; VAR < NUM_ITERATIONS; VAR += STEP)
+
+/** Get the get_global_id with partial N0. This function is useful when the dimension is not multiple of N0 and we need to use a partial N0
+ * to avoid out-of-bound read/write
+ *
+ * @note PARTIAL_N0 is used for get_global_id(n) = 0.
+ *
+ * @param[in] IDX get_global_id index (0,1 and 2 only)
+ * @param[in] N0 Number of elements read/written on the IDX direction
+ * @param[in] PARTIAL_N0 Number of elements read/written on the IDX direction for get_global_id(IDX) = 0. If zero,
+ * the Number of elements read/written on the IDX direction for get_global_id(IDX) = 0 is N0
+ */
+#define GET_SPATIAL_IDX(IDX, N0, PARTIAL_N0) (max((int)(get_global_id(IDX) * N0 - (N0 - PARTIAL_N0) % N0), 0))
+
+/** Offset (in bytes) calculation for a 1D BUFFER (cl_buffer) tensor */
+#define OFFSET1D(base, data_type, x) (base##_offset_first_element_in_bytes + x * sizeof(data_type))
+
+/** Offset (in bytes) calculation for a 2D BUFFER (cl_buffer) tensor */
+#define OFFSET2D(base, data_type, x, y) (base##_offset_first_element_in_bytes + x * sizeof(data_type) + y * base##_stride_y)
+
+/** Offset (in bytes) calculation for a 3D BUFFER (cl_buffer) tensor */
+#define OFFSET3D(base, data_type, x, y, z) (base##_offset_first_element_in_bytes + x * sizeof(data_type) + y * base##_stride_y + z * base##_stride_z)
+
+/** Offset (in bytes) calculation for a 4D BUFFER (cl_buffer) tensor */
+#define OFFSET4D(base, data_type, x, y, z, w) (base##_offset_first_element_in_bytes + x * sizeof(data_type) + y * base##_stride_y + z * base##_stride_z + w * base##_stride_w)
+
+/** Dot product integet 8bit function
+ *
+ * @note Performs: c += dot(a, b)
+ *
+ * @param[in] DST_DATA_TYPE Accumulator data type
+ * @param[in] K0 Number of accumulations
+ * @param[in] a OpenCL vector a
+ * @param[in] b OpenCL vector b
+ * @param[in] c Scalar variable c
+ */
+#define DOT_PRODUCT_INTEGER8(DST_DATA_TYPE, K0, a, b, c) DOT_PRODUCT_INTEGER8_STR(DST_DATA_TYPE, K0, a, b, c)
+#define DOT_PRODUCT_INTEGER8_STR(DST_DATA_TYPE, K0, a, b, c) DOT_PRODUCT##K0##_INTEGER8(DST_DATA_TYPE, a, b, c)
+#define DOT_PRODUCT1_INTEGER8(DST_DATA_TYPE, a, b, c) \
+ ({ \
+ c += (DST_DATA_TYPE)a * (DST_DATA_TYPE)b; \
+ })
+#define DOT_PRODUCT2_INTEGER8(DST_DATA_TYPE, a, b, c) \
+ ({ \
+ c += (DST_DATA_TYPE)a.s0 * (DST_DATA_TYPE)b.s0; \
+ c += (DST_DATA_TYPE)a.s1 * (DST_DATA_TYPE)b.s1; \
+ })
+#define DOT_PRODUCT3_INTEGER8(DST_DATA_TYPE, a, b, c) \
+ ({ \
+ DOT_PRODUCT2_INTEGER8(DST_DATA_TYPE, a, b, c); \
+ c += (DST_DATA_TYPE)a.s2 * (DST_DATA_TYPE)b.s2; \
+ })
+#if defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
+#define DOT_PRODUCT4_INTEGER8(DST_DATA_TYPE, x, y, val) val = arm_dot_acc((x), (y), (val));
+#elif defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
+#define DOT_PRODUCT4_INTEGER8(DST_DATA_TYPE, x, y, val) val += arm_dot((x), (y));
+#else // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
+#define DOT_PRODUCT4_INTEGER8(DST_DATA_TYPE, x, y, val) \
+ ({ \
+ val += (DST_DATA_TYPE)x.s0 * (DST_DATA_TYPE)y.s0; \
+ val += (DST_DATA_TYPE)x.s1 * (DST_DATA_TYPE)y.s1; \
+ val += (DST_DATA_TYPE)x.s2 * (DST_DATA_TYPE)y.s2; \
+ val += (DST_DATA_TYPE)x.s3 * (DST_DATA_TYPE)y.s3; \
+ })
+#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8)
+#define DOT_PRODUCT8_INTEGER8(DST_DATA_TYPE, a, b, c) \
+ ({ \
+ DOT_PRODUCT4_INTEGER8((a.lo), (b.lo), c); \
+ DOT_PRODUCT4_INTEGER8((a.hi), (b.hi), c); \
+ })
+#define DOT_PRODUCT16_INTEGER8(DST_DATA_TYPE, a, b, c) \
+ ({ \
+ DOT_PRODUCT8_INTEGER8((a.lo), (b.lo), c); \
+ DOT_PRODUCT8_INTEGER8((a.hi), (b.hi), c); \
+ })
+
+/** Load a vector from global memory (tensor)
+ *
+ * @param[in] DATA_TYPE Data type
+ * @param[in] WIDTH Number of dst columns
+ * @param[in] TENSOR_TYPE Type of cl_type used to store the tensor in global memory (BUFFER=cl_buffer, IMAGE=cl_image).
+ * In case of cl_image, only WIDTH multiples of 4 are supported (4, 8, 16)
+ * @param[in] TENSOR Tensor basename
+ * @param[in] X Starting X position
+ * @param[in] Y Starting Y position
+ * @param[in] STRIDE_Y Stride Y (in bytes)
+ */
+#define V_LOAD(DATA_TYPE, WIDTH, TENSOR_TYPE, TENSOR, X, Y, STRIDE_Y) V_LOAD_STR(DATA_TYPE, WIDTH, TENSOR_TYPE, TENSOR, X, Y, STRIDE_Y)
+#define V_LOAD_STR(DATA_TYPE, WIDTH, TENSOR_TYPE, TENSOR, X, Y, STRIDE_Y) V_LOAD_##TENSOR_TYPE(DATA_TYPE, WIDTH, TENSOR, X, Y, STRIDE_Y)
+#define V_LOAD_BUFFER(DATA_TYPE, WIDTH, TENSOR, X, Y, STRIDE_Y) \
+ VLOAD(WIDTH) \
+ (0, (__global DATA_TYPE *)(TENSOR##_ptr + (X) * sizeof(DATA_TYPE) + (Y)*STRIDE_Y))
+#define V_LOAD_IMAGE(DATA_TYPE, WIDTH, TENSOR, X, Y, STRIDE_Y) READ_IMAGE2D(DATA_TYPE, CONVERT_VECTOR_SIZE_TO_PIXEL_UNIT(WIDTH), TENSOR##_img, (X) / 4, (Y))
+
+/** Load a tile from global memory (tensor)
+ *
+ * @param[in] DATA_TYPE Data type
+ * @param[in] HEIGHT Number of dst rows
+ * @param[in] WIDTH Number of dst columns
+ * @param[in] TENSOR_TYPE Type of cl_type used to store the tensor in global memory (BUFFER=cl_buffer, IMAGE=cl_image).
+ * In case of cl_image, only WIDTH multiples of 4 are supported (4, 8, 16)
+ * @param[in] TENSOR Tensor basename
+ * @param[in] X Starting X position
+ * @param[in] Y Starting Y position
+ * @param[in] STRIDE_Y Stride Y (in bytes)
+ * @param[out] dst Output tile
+ */
+#define T_LOAD(DATA_TYPE, HEIGHT, WIDTH, TENSOR_TYPE, TENSOR, X, Y, STRIDE_Y, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _i, 0, HEIGHT, 1) \
+ { \
+ dst[_i].v = V_LOAD(DATA_TYPE, WIDTH, TENSOR_TYPE, TENSOR, X, ((Y) + _i), STRIDE_Y); \
+ } \
+ })
+
+/** Load a tile from global memory (tensor) using an indirect Y index tile
+ *
+ * @param[in] DATA_TYPE Data type
+ * @param[in] HEIGHT Number of dst rows
+ * @param[in] WIDTH Number of dst columns
+ * @param[in] TENSOR_TYPE Type of cl_type used to store the tensor in global memory (BUFFER=cl_buffer, IMAGE=cl_image). Currently BUFFER only is supported
+ * In case of cl_image, only WIDTH multiples of 4 are supported (4, 8, 16)
+ * @param[in] TENSOR Tensor basename
+ * @param[in] X Starting X position
+ * @param[in] STRIDE_Y Stride Y (in bytes)
+ * @param[in] indirect_y Indirect Y index tile
+ * @param[out] dst Output tile
+ */
+#define T_LOAD_INDIRECT(DATA_TYPE, HEIGHT, WIDTH, TENSOR_TYPE, TENSOR, X, STRIDE_Y, indirect_y, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _i, 0, HEIGHT, 1) \
+ { \
+ dst[_i].v = V_LOAD(DATA_TYPE, WIDTH, TENSOR_TYPE, TENSOR, X, (indirect_y[_i].v), STRIDE_Y); \
+ } \
+ })
+
+/** Store a tile to global memory (tensor) using an indirect Y index tile and conditionally use a different length for the store
+ *
+ * @note If WIDTH1_CONDITION is true, the store will use the WIDTH1 length for the store
+ * @note The vectors are stored in reverse order so the invalid rows are overwritten by the valid ones
+ *
+ * @param[in] DATA_TYPE Data type
+ * @param[in] HEIGHT Number of src rows
+ * @param[in] WIDTH0 Store width to use if WIDTH1_CONDITION = false
+ * @param[in] WIDTH1 Store width to use if WIDTH1_CONDITION = true
+ * @param[in] TENSOR_TYPE Type of cl_type used to store the tensor in global memory (BUFFER=cl_buffer, IMAGE=cl_image). Currently BUFFER only is supported
+ * cl_image is not supported.
+ * @param[in] TENSOR Tensor basename
+ * @param[in] X Starting X position
+ * @param[in] STRIDE_Y Stride Y (in bytes)
+ * @param[in] WIDTH1_CONDITION Condition to select the WIDTH1 store
+ * @param[in] src Input tile
+ * @param[in] indirect_y Indirect Y index tile
+ */
+#define T_STORE_INDIRECT_WIDTH_SELECT(DATA_TYPE, HEIGHT, WIDTH0, WIDTH1, TENSOR_TYPE, TENSOR, X, STRIDE_Y, WIDTH1_CONDITION, src, indirect_y) \
+ ({ \
+ if(WIDTH1_CONDITION) \
+ { \
+ LOOP_UNROLLING(int, _i, 0, HEIGHT, 1) \
+ { \
+ VSTORE_PARTIAL(WIDTH0, WIDTH1) \
+ (src[HEIGHT - 1 - _i].v, 0, (__global DATA_TYPE *)(TENSOR##_ptr + (X) * sizeof(DATA_TYPE) + (indirect_y[HEIGHT - 1 - _i].v) * STRIDE_Y)); \
+ } \
+ } \
+ else \
+ { \
+ LOOP_UNROLLING(int, _i, 0, HEIGHT, 1) \
+ { \
+ VSTORE(WIDTH0) \
+ (src[HEIGHT - 1 - _i].v, 0, (__global DATA_TYPE *)(TENSOR##_ptr + (X) * sizeof(DATA_TYPE) + (indirect_y[HEIGHT - 1 - _i].v) * STRIDE_Y)); \
+ } \
+ } \
+ })
+
+/** Offset correction for the QASYMM8 computation
+ *
+ * @param[in] ACC_DATA_TYPE Accumulator data type
+ * @param[in] M0 Number of src/dst rows
+ * @param[in] N0 Number of src/dst columns
+ * @param[in] K0 Number of src columns
+ * @param[in] SRC_OFFSET Source quantization offset
+ * @param[in] WEI_OFFSET Weights quantization shift
+ * @param[in] lhs LHS tile
+ * @param[in] rhs RHS tile
+ * @param[out] dst DST tile
+ */
+#define T_OFFSET_CORRECTION(ACC_DATA_TYPE, M0, N0, K0, SRC_OFFSET, WEI_OFFSET, lhs, rhs, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _m0, 0, M0, 1) \
+ { \
+ ACC_DATA_TYPE _tm = 0; \
+ LOOP_UNROLLING(int, _k0, 0, K0, 1) \
+ { \
+ _tm += ((ACC_DATA_TYPE)lhs[_m0].s[_k0] * (ACC_DATA_TYPE)WEI_OFFSET); \
+ } \
+ LOOP_UNROLLING(int, _n0, 0, N0, 1) \
+ { \
+ dst[_m0].s[_n0] += _tm; \
+ LOOP_UNROLLING(int, _k0, 0, K0, 1) \
+ { \
+ dst[_m0].s[_n0] += ((ACC_DATA_TYPE)rhs[_n0].s[_k0] * (ACC_DATA_TYPE)SRC_OFFSET); \
+ } \
+ } \
+ } \
+ })
+
+/** Quantized the tile (ASYMMETRIC) with fixed-point scale
+ *
+ * @param[in] SRC_DATA_TYPE SRC data type
+ * @param[in] DST_DATA_TYPE DST data type
+ * @param[in] M0 Number of src/dst rows
+ * @param[in] N0 Number of src/dst columns
+ * @param[in] DST_OFFSET Quantization offset
+ * @param[in] DST_SHIFT Quantization shift
+ * @param[in] DST_MULTIPLIER Quantization multiplier
+ * @param[in] src Input tile
+ * @param[out] dst Output tile
+ */
+#define T_QUANTIZE8_ASYMMETRIC(SRC_DATA_TYPE, DST_DATA_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, src, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _m0, 0, M0, 1) \
+ { \
+ LOOP_UNROLLING(int, _n0, 0, N0, 1) \
+ { \
+ SRC_DATA_TYPE _tmp = 0; \
+ if(DST_SHIFT < 0) \
+ { \
+ _tmp = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(src[_m0].s[_n0], DST_MULTIPLIER, DST_SHIFT, 1); \
+ } \
+ else \
+ { \
+ _tmp = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(src[_m0].s[_n0], DST_MULTIPLIER, DST_SHIFT, 1); \
+ } \
+ _tmp += DST_OFFSET; \
+ dst[_m0].s[_n0] = CONVERT_SAT(_tmp, DST_DATA_TYPE); \
+ } \
+ } \
+ })
+
+/** Conditional rowset (memset by row)
+ *
+ * @note Set the row to VALUE_TO_SET if the corresponding mask == 0
+ *
+ * @param[in] DATA_TYPE Data type
+ * @param[in] M0 Number of LHS rows
+ * @param[in] N0 Number of LHS columns
+ * @param[in] VALUE_TO_SET Value to set the row
+ * @param[in, out] a Input/output tile
+ * @param[out] mask Mask to check for setting the row to VALUE_TO_SET
+ */
+#define T_ROWSET_MASK(DATA_TYPE, M0, N0, VALUE_TO_SET, a, mask) \
+ ({ \
+ LOOP_UNROLLING(int, _m0, 0, M0, 1) \
+ { \
+ LOOP_UNROLLING(int, _n0, 0, N0, 1) \
+ { \
+ a[_m0].s[_n0] = select((DATA_TYPE)(a[_m0].s[_n0]), (DATA_TYPE)(VALUE_TO_SET), (SELECT_DATA_TYPE(DATA_TYPE))(mask[_m0].v == (DATA_TYPE)0)); \
+ } \
+ } \
+ })
+
+/** Element-wise addition with a constant value
+ *
+ * @note Performs: LHS + constant = DST
+ *
+ * @param[in] DATA_TYPE LHS/RHS/DST data type
+ * @param[in] M0 Number of LHS rows
+ * @param[in] N0 Number of LHS columns
+ * @param[in] lhs LHS tile
+ * @param[in] rhs_constant Constant value
+ * @param[out] dst DST tile
+ */
+#define T_ADD_CONSTANT(DATA_TYPE, M0, N0, lhs, rhs_constant, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _m0, 0, M0, 1) \
+ { \
+ LOOP_UNROLLING(int, _n0, 0, N0, 1) \
+ { \
+ dst[_m0].s[_n0] = lhs[_m0].s[_n0] + rhs_constant; \
+ } \
+ } \
+ })
+
+/** Element-wise addition with RHS broadcasted (RHS has the X dimension only)
+ *
+ * @note Performs: LHS + RHS[broadcasted] = DST
+ * @note Both tiles must have same data type
+ *
+ * @param[in] DATA_TYPE LHS/RHS/DST data type
+ * @param[in] M0 Number of LHS rows
+ * @param[in] N0 Number of LHS columns
+ * @param[in] lhs LHS tile
+ * @param[in] rhs RHS tile
+ * @param[out] dst DST tile
+ */
+#define T_ADD_BROADCAST_X(DATA_TYPE, M0, N0, lhs, rhs, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _m0, 0, M0, 1) \
+ { \
+ dst[_m0].v = lhs[_m0].v + rhs[0].v; \
+ } \
+ })
+
+/** Matrix multiplication
+ *
+ * @note Performs: LHS X RHS + DST = DST
+ *
+ * @param[in] LHS_DATA_TYPE LHS tile data type
+ * @param[in] RHS_DATA_TYPE RHS tile data type
+ * @param[in] DST_DATA_TYPE RHS tile data type
+ * @param[in] M0 Number of LHS rows
+ * @param[in] N0 Number of RHS columns
+ * @param[in] K0 Number of LHS columns
+ * @param[in] LHS_LAYOUT LHS layout (T= transposed, NT= not transposed)
+ * @param[in] RHS_LAYOUT RHS layout (T= transposed, NT= not transposed)
+ * @param[in] lhs LHS tile
+ * @param[in] rhs RHS tile
+ * @param[in, out] dst DST tile
+ */
+#define T_MMUL(LHS_DATA_TYPE, RHS_DATA_TYPE, DST_DATA_TYPE, M0, N0, K0, LHS_LAYOUT, RHS_LAYOUT, lhs, rhs, dst) T_MMUL_##LHS_LAYOUT##_##RHS_LAYOUT(LHS_DATA_TYPE, RHS_DATA_TYPE, DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T(LHS_DATA_TYPE, RHS_DATA_TYPE, DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_##LHS_DATA_TYPE##_##RHS_DATA_TYPE##_##DST_DATA_TYPE(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_float_float_float(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_FLOAT(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_half_half_half(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_FLOAT(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_char_char_int(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_INTEGER8(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_uchar_uchar_uint(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_INTEGER8(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_uchar_uchar_int(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) T_MMUL_NT_T_INTEGER8(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst)
+#define T_MMUL_NT_T_FLOAT(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) \
+ { \
+ LOOP_UNROLLING(int, _m, 0, M0, 1) \
+ { \
+ LOOP_UNROLLING(int, _n, 0, N0, 1) \
+ { \
+ LOOP_UNROLLING(int, _k, 0, K0, 1) \
+ { \
+ dst[_m].s[_n] = fma((lhs[_m].s[_k]), (rhs[_n].s[_k]), dst[_m].s[_n]); \
+ } \
+ } \
+ } \
+ }
+#define T_MMUL_NT_T_INTEGER8(DST_DATA_TYPE, M0, N0, K0, lhs, rhs, dst) \
+ ({ \
+ LOOP_UNROLLING(int, _m, 0, M0, 1) \
+ { \
+ LOOP_UNROLLING(int, _n, 0, N0, 1) \
+ { \
+ DOT_PRODUCT_INTEGER8(DST_DATA_TYPE, K0, (lhs[_m].v), (rhs[_n].v), dst[_m].s[_n]); \
+ } \
+ } \
+ }) \ No newline at end of file
diff --git a/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
index f071dbc468..72801fa6c8 100644
--- a/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
+++ b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
@@ -276,10 +276,12 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITenso
if(data_layout == DataLayout::NHWC)
{
const unsigned int vec_size = std::min(static_cast<unsigned int>(dst->tensor_shape()[0]), 4u);
+ const unsigned int num_rows = dst->tensor_shape()[0] > 16 ? 2u : 1U;
// Create window and update padding
- Window win = calculate_max_window(*dst, Steps(vec_size, 1U));
+ Window win = calculate_max_window(*dst, Steps(vec_size, num_rows));
dst->set_valid_region(ValidRegion(Coordinates(), dst->tensor_shape()));
+
Status err = Status{};
return std::make_pair(err, win);
}
@@ -368,9 +370,9 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
const unsigned int n0 = win_config.second.x().step();
const unsigned int m0 = win_config.second.y().step();
- const unsigned int k0 = adjust_vec_size(16u, src->dimension(channel_idx));
+
+ const unsigned int k0 = adjust_vec_size(8u, src->dimension(channel_idx));
const unsigned int partial_store_n0 = dst->dimension(channel_idx) % n0;
- const unsigned int partial_store_m0 = (dst->dimension(width_idx) * dst->dimension(height_idx)) % m0;
const unsigned int pad_left = conv_info.pad_left();
const unsigned int pad_top = conv_info.pad_top();
@@ -379,14 +381,19 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
build_options.add_option(std::string("-DHAS_BIAS"));
build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(biases->data_type())));
}
+
+ build_options.add_option("-cl-fast-relaxed-math");
+ build_options.add_option("-DSRC_TENSOR_TYPE=BUFFER");
build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(width_idx)));
build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(height_idx)));
build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(src->dimension(channel_idx)));
build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
+ build_options.add_option("-DDST_TENSOR_TYPE=BUFFER");
build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(dst->dimension(width_idx)));
build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(height_idx)));
build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(channel_idx)));
build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(dst->data_type()));
+ build_options.add_option("-DWEI_TENSOR_TYPE=BUFFER");
build_options.add_option("-DWEI_WIDTH=" + support::cpp11::to_string(weights->dimension(width_idx)));
build_options.add_option("-DWEI_HEIGHT=" + support::cpp11::to_string(weights->dimension(height_idx)));
build_options.add_option("-DWEI_DATA_TYPE=" + get_cl_type_from_data_type(weights->data_type()));
@@ -397,8 +404,7 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
build_options.add_option("-DN0=" + support::cpp11::to_string(n0));
build_options.add_option("-DM0=" + support::cpp11::to_string(m0));
build_options.add_option("-DK0=" + support::cpp11::to_string(k0));
- build_options.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
- build_options.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
+ build_options.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0));
if(is_data_type_quantized(data_type))
{
@@ -426,6 +432,7 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
else
{
build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(data_type));
+ build_options.add_option("-DZERO_VALUE=" + support::cpp11::to_string(0));
build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(0));
build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(0));
build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(0));
@@ -529,18 +536,18 @@ void ClDirectConvolutionKernel::run_op(ITensorPack &tensors, const Window &windo
if(_data_layout == DataLayout::NHWC)
{
- slice.set(Window::DimY, Window::Dimension(0, dst->info()->dimension(1) * dst->info()->dimension(2), 1));
+ const size_t dim_y_collapsed = ceil_to_multiple(dst->info()->dimension(1) * dst->info()->dimension(2), slice.y().step());
+ slice.set(Window::DimY, Window::Dimension(0, dim_y_collapsed, slice.y().step()));
slice.set(Window::DimZ, Window::Dimension(0, dst->info()->dimension(3), 1));
unsigned int idx = 0;
- add_3D_tensor_argument(idx, src, slice);
- add_3D_tensor_argument(idx, dst, slice);
- add_3D_tensor_argument(idx, weights, slice);
+ add_4D_tensor_argument(idx, src, slice);
+ add_4D_tensor_argument(idx, dst, slice);
+ add_4D_tensor_argument(idx, weights, slice);
if(biases != nullptr)
{
add_1D_tensor_argument(idx, biases, slice);
}
- _kernel.setArg(idx++, static_cast<unsigned int>(weights->info()->strides_in_bytes()[3]));
enqueue(queue, *this, slice, lws_hint());
}
else
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index e244576daf..4671d8c3ec 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -183,7 +183,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<half>, framewor
framework::dataset::make("PadX", { 1, 3, 0, 4 })),
framework::dataset::make("PadY", { 1, 3, 0, 4 })),
framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
- framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("NumKernels", { 17, 3, 1, 19 })),
framework::dataset::make("DataType", DataType::F16)),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
framework::dataset::make("DataLayout", DataLayout::NHWC)))
@@ -221,7 +221,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolutionLayerFixture<float>, framewo
framework::dataset::make("PadX", { 1, 3, 0, 4 })),
framework::dataset::make("PadY", { 1, 3, 0, 4 })),
framework::dataset::make("KernelSize", { 3, 8, 1, 9 })),
- framework::dataset::make("NumKernels", { 7, 3, 1, 3 })),
+ framework::dataset::make("NumKernels", { 17, 3, 1, 19 })),
framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) )),
framework::dataset::make("DataLayout", DataLayout::NHWC)))
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-23 08:07:30 +0000