COMPMID-1611 CLDirectConvolution NHWC QASYMM not implemented
Change-Id: I358c729cb81b83d35f1bc7f70ea593d5bff5f1ed
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2738
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/src/core/CL/cl_kernels/direct_convolution_quantized.cl b/src/core/CL/cl_kernels/direct_convolution_quantized.cl
index 0a8c5fa..3324e9c 100644
--- a/src/core/CL/cl_kernels/direct_convolution_quantized.cl
+++ b/src/core/CL/cl_kernels/direct_convolution_quantized.cl
@@ -31,6 +31,435 @@
#define CONVERT_SAT_STR(x, type) (convert_##type##8_sat((x)))
#define CONVERT_SAT(x, type) CONVERT_SAT_STR(x, type)
+#if defined(DATA_LAYOUT_NHWC)
+
+#if KERNEL_SIZE == 5
+
+#if STRIDE_X == 1
+#define CONVOLUTION1x5(acc, src_ptr, weights_ptr) CONVOLUTION1x5_STRIDE1(acc, src_ptr, weights_ptr)
+#elif STRIDE_X == 2
+#define CONVOLUTION1x5(acc, src_ptr, weights_ptr) CONVOLUTION1x5_STRIDE2(acc, src_ptr, weights_ptr)
+#else /* STRIDE_X not equals 1 or 2 */
+#error "STRIDE_X larger than 2 is not supported"
+#endif /* STRIDE_X */
+
+#define CONVOLUTION1x5_STRIDE1(acc, src_ptr, weights_ptr) \
+ ({ \
+ int4 weights_values0 = 0; \
+ int weights_value1 = 0; \
+ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \
+ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \
+ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \
+ weights_values0.s3 = convert_int(*(weights_ptr + 3 * weights_stride_y)); \
+ weights_value1 = convert_int(*(weights_ptr + 4 * weights_stride_y)); \
+ \
+ int8 src0 = 0; \
+ int4 src1 = 0; \
+ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \
+ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \
+ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \
+ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \
+ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \
+ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \
+ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \
+ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \
+ src1.s0 = convert_int(*(src_ptr + 8 * weights_stride_y)); \
+ src1.s1 = convert_int(*(src_ptr + 9 * weights_stride_y)); \
+ src1.s2 = convert_int(*(src_ptr + 10 * weights_stride_y)); \
+ src1.s3 = convert_int(*(src_ptr + 11 * weights_stride_y)); \
+ \
+ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \
+ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
+ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
+ acc += ((int8)(src0.s345, src0.s67, src1.s012) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \
+ acc += ((int8)(src0.s45, src0.s67, src1.s0123) + input_offset) * ((int8)weights_value1 + weight_offset); \
+ })
+
+#define CONVOLUTION1x5_STRIDE2(acc, src_ptr, weights_ptr) \
+ ({ \
+ int4 weights_values0 = 0; \
+ int weights_value1 = 0; \
+ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \
+ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \
+ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \
+ weights_values0.s3 = convert_int(*(weights_ptr + 3 * weights_stride_y)); \
+ weights_value1 = convert_int(*(weights_ptr + 4 * weights_stride_y)); \
+ \
+ int16 src0 = 0; \
+ int4 src1 = 0; \
+ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \
+ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \
+ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \
+ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \
+ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \
+ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \
+ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \
+ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \
+ src0.s8 = convert_int(*(src_ptr + 8 * weights_stride_y)); \
+ src0.s9 = convert_int(*(src_ptr + 9 * weights_stride_y)); \
+ src0.sa = convert_int(*(src_ptr + 10 * weights_stride_y)); \
+ src0.sb = convert_int(*(src_ptr + 11 * weights_stride_y)); \
+ src0.sc = convert_int(*(src_ptr + 12 * weights_stride_y)); \
+ src0.sd = convert_int(*(src_ptr + 13 * weights_stride_y)); \
+ src0.se = convert_int(*(src_ptr + 14 * weights_stride_y)); \
+ src0.sf = convert_int(*(src_ptr + 15 * weights_stride_y)); \
+ src1.s0 = convert_int(*(src_ptr + 16 * weights_stride_y)); \
+ src1.s1 = convert_int(*(src_ptr + 17 * weights_stride_y)); \
+ src1.s2 = convert_int(*(src_ptr + 18 * weights_stride_y)); \
+ src1.s3 = convert_int(*(src_ptr + 19 * weights_stride_y)); \
+ \
+ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \
+ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
+ acc += ((int8)(src0.s2468, src0.sACE, src1.s0) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
+ acc += ((int8)(src0.s3579, src0.sBDF, src1.s1) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \
+ acc += ((int8)(src0.s468a, src0.sCE, src1.s02) + input_offset) * ((int8)weights_value1 + weight_offset); \
+ })
+
+#elif KERNEL_SIZE == 3
+
+#if STRIDE_X == 1
+#define CONVOLUTION1x3(acc, src_ptr, weights_ptr) CONVOLUTION1x3_STRIDE1(acc, src_ptr, weights_ptr)
+#elif STRIDE_X == 2
+#define CONVOLUTION1x3(acc, src_ptr, weights_ptr) CONVOLUTION1x3_STRIDE2(acc, src_ptr, weights_ptr)
+#else /* STRIDE_X not equals 1 or 2 */
+#error "STRIDE_X larger than 2 is not supported"
+#endif /* STRIDE_X */
+
+#define CONVOLUTION1x3_STRIDE1(acc, src_ptr, weights_ptr) \
+ ({ \
+ int3 weights_values0 = 0; \
+ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \
+ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \
+ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \
+ \
+ int8 src0 = 0; \
+ int2 src1 = 0; \
+ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \
+ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \
+ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \
+ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \
+ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \
+ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \
+ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \
+ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \
+ src1.s0 = convert_int(*(src_ptr + 8 * weights_stride_y)); \
+ src1.s1 = convert_int(*(src_ptr + 9 * weights_stride_y)); \
+ \
+ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \
+ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
+ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
+ })
+
+#define CONVOLUTION1x3_STRIDE2(acc, src_ptr, weights_ptr) \
+ ({ \
+ int3 weights_values0 = 0; \
+ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \
+ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \
+ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \
+ \
+ int16 src0 = 0; \
+ int src1 = 0; \
+ src0.s0 = convert_int(*(src_ptr + 0 * src_stride_y)); \
+ src0.s1 = convert_int(*(src_ptr + 1 * src_stride_y)); \
+ src0.s2 = convert_int(*(src_ptr + 2 * src_stride_y)); \
+ src0.s3 = convert_int(*(src_ptr + 3 * src_stride_y)); \
+ src0.s4 = convert_int(*(src_ptr + 4 * src_stride_y)); \
+ src0.s5 = convert_int(*(src_ptr + 5 * src_stride_y)); \
+ src0.s6 = convert_int(*(src_ptr + 6 * src_stride_y)); \
+ src0.s7 = convert_int(*(src_ptr + 7 * src_stride_y)); \
+ src0.s8 = convert_int(*(src_ptr + 8 * src_stride_y)); \
+ src0.s9 = convert_int(*(src_ptr + 9 * src_stride_y)); \
+ src0.sa = convert_int(*(src_ptr + 10 * src_stride_y)); \
+ src0.sb = convert_int(*(src_ptr + 11 * src_stride_y)); \
+ src0.sc = convert_int(*(src_ptr + 12 * src_stride_y)); \
+ src0.sd = convert_int(*(src_ptr + 13 * src_stride_y)); \
+ src0.se = convert_int(*(src_ptr + 14 * src_stride_y)); \
+ src0.sf = convert_int(*(src_ptr + 15 * src_stride_y)); \
+ src1 = convert_int(*(src_ptr + 16 * src_stride_y)); \
+ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \
+ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \
+ acc += ((int8)(src0.s2468, src0.sACE, src1) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \
+ })
+
+#elif KERNEL_SIZE == 1
+
+#if STRIDE_X == 3
+#define INPUT_VALUE extract_input_stride3
+#elif STRIDE_X == 2
+#define INPUT_VALUE extract_input_stride2
+#elif STRIDE_X == 1
+#define INPUT_VALUE extract_input_stride1
+
+#else /* STRIDE_X not equals 1, 2 or 3 */
+#error "Only support strides 1, 2 and 3"
+#endif /* STRIDE_X */
+
+#endif // KERNEL_SIZE == 1
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 1.
+ *
+ * @param[in] input_value Pointer to the first value.
+ *
+ * @return extracted input values.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_value, const uchar stride_y)
+{
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ vals;
+ vals.s0 = *(input_value + 0 * stride_y);
+ vals.s1 = *(input_value + 1 * stride_y);
+ vals.s2 = *(input_value + 2 * stride_y);
+ vals.s3 = *(input_value + 3 * stride_y);
+ vals.s4 = *(input_value + 4 * stride_y);
+ vals.s5 = *(input_value + 5 * stride_y);
+ vals.s6 = *(input_value + 6 * stride_y);
+ vals.s7 = *(input_value + 7 * stride_y);
+
+ return vals;
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 2.
+ *
+ * @param[in] input_value Pointer to the first value.
+ *
+ * @return extracted input values.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_value, const uchar stride_y)
+{
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ vals;
+ vals.s0 = *(input_value + 0 * stride_y);
+ vals.s1 = *(input_value + 2 * stride_y);
+ vals.s2 = *(input_value + 4 * stride_y);
+ vals.s3 = *(input_value + 6 * stride_y);
+ vals.s4 = *(input_value + 8 * stride_y);
+ vals.s5 = *(input_value + 10 * stride_y);
+ vals.s6 = *(input_value + 12 * stride_y);
+ vals.s7 = *(input_value + 14 * stride_y);
+
+ return vals;
+}
+
+/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size.
+ *
+ * @param[in] input_value Pointer to the first value.
+ *
+ * @return extracted input values.
+ */
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3(__global const DATA_TYPE *input_value, const uchar stride_y)
+{
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ vals;
+ vals.s0 = *(input_value + 0 * stride_y);
+ vals.s1 = *(input_value + 3 * stride_y);
+ vals.s2 = *(input_value + 6 * stride_y);
+ vals.s3 = *(input_value + 9 * stride_y);
+ vals.s4 = *(input_value + 12 * stride_y);
+ vals.s5 = *(input_value + 15 * stride_y);
+ vals.s6 = *(input_value + 18 * stride_y);
+ vals.s7 = *(input_value + 21 * stride_y);
+
+ return vals;
+}
+
+/** This kernel performs a direct convolution to convolve the low three dimensions.
+ *
+ * @note The convolution stride x must be passed at compile time using -DSTRIDE_X e.g. -DSTRIDE_X=1
+ * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH
+ * @note If biases are used then -DHAS_BIAS has to be passed at compile time
+ * @note The output quantization multiplier must be passed at compile time using -DOUTPUT_MULTIPLIER e.g. -DOUTPUT_MULTIPLIER=1234
+ * @note The output quantization shift must be passed at compile time using -DOUTPUT_SHIFT e.g. -DOUTPUT_SHIFT=4
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED
+ * @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_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Z 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_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: same as @p src_ptr
+ * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes)
+ * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes)
+ * @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes)
+ * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes)
+ * @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
+ * @param[in] biases_ptr Pointer to the biases tensor. Supported data types: S32
+ * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes)
+ * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor
+ * @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension
+ * @param[in] input_offset Input offset quantization parameter
+ * @param[in] weight_offset Weights offset quantization parameter
+ * @param[in] output_offset Output offset quantization parameter
+ */
+__kernel void direct_convolution_quantized(
+ TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst),
+ TENSOR3D_DECLARATION(weights),
+#ifdef HAS_BIAS
+ VECTOR_DECLARATION(biases),
+#endif /* defined(HAS_BIAS) */
+ unsigned int weights_stride_w,
+ int input_offset,
+ int weight_offset,
+ int output_offset)
+{
+ Image src = CONVERT_TO_IMAGE_STRUCT(src);
+ Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
+ Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
+
+ int8 values0 = 0;
+
+ const int y_coord = (get_global_id(2) * STRIDE_Y) - PAD_TOP;
+
+ __global DATA_TYPE *weights_addr = (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 0, 0);
+ __global DATA_TYPE *src_addr = (__global DATA_TYPE *)offset(&src, 0, 0) - src_stride_x * get_global_id(0) + y_coord * (int)src_stride_z;
+
+ const int kernel_index = get_global_id(2);
+ weights_addr += kernel_index * weights_stride_w;
+
+ for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d)
+ {
+#if KERNEL_SIZE == 5
+#if(PAD_TOP == 1)
+ if(y_coord < 0) // special case Z = -1 doesn't exists
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+ }
+ else if(get_global_id(2) == (DST_HEIGHT - 1))
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ }
+ else
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+ }
+#elif(PAD_TOP == 2)
+ if(y_coord < -1)
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+ }
+ else if(y_coord == -1)
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+ }
+ else if(y_coord == (SRC_HEIGHT - 3))
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ }
+ else if(y_coord >= (SRC_HEIGHT - 4))
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ }
+ else
+ {
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+ }
+#else /* PAD_TOP == 2 */
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z));
+#endif /* PAD_TOP == 1 */
+#elif KERNEL_SIZE == 3
+#if PAD_TOP > 0
+ if(y_coord < 0) // special case Z = -1 doesn't exists
+ {
+ //skip first row and load the two next ones
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ }
+ else if(y_coord == (SRC_HEIGHT - PAD_TOP - 1))
+ {
+ // special case when computing the last row of the output we must read the last three rows from the input buffer (including padding) but the
+ // Z axis has no padding at all.
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ }
+ else
+ {
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+ }
+#else // PAD_TOP > 0
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z));
+#endif // PAD_TOP > 0
+#elif KERNEL_SIZE == 1
+ int weight = convert_int(*(__global DATA_TYPE *)weights_addr);
+ int8 input_value = convert_int8(INPUT_VALUE((__global DATA_TYPE *)src_addr, src_stride_y));
+ values0 += (input_value + input_offset) * ((int8)weight + weight_offset);
+#endif /* (KERNEL_SIZE == 1) || (KERNEL_SIZE == 3) || (KERNEL_SIZE == 5) */
+
+ src_addr += src_stride_x;
+ weights_addr += weights_stride_x;
+ }
+
+#ifdef HAS_BIAS
+ Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
+ __global int *bias_addr = ((__global int *)(vector_offset(&biases, get_global_id(0))));
+ values0 += (int8)(*bias_addr);
+#endif /* defined(HAS_BIAS) */
+
+#if OUTPUT_SHIFT < 0
+ values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
+#else // OUTPUT_SHIFT < 0
+ values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
+#endif // OUTPUT_SHIFT < 0
+ values0 = values0 + output_offset;
+
+ VEC_DATA_TYPE(DATA_TYPE, 8)
+ values = CONVERT_SAT(values0, DATA_TYPE);
+ *(dst.ptr + 0 * dst_stride_y) = values.s0;
+ *(dst.ptr + 1 * dst_stride_y) = values.s1;
+ *(dst.ptr + 2 * dst_stride_y) = values.s2;
+ *(dst.ptr + 3 * dst_stride_y) = values.s3;
+ *(dst.ptr + 4 * dst_stride_y) = values.s4;
+ *(dst.ptr + 5 * dst_stride_y) = values.s5;
+ *(dst.ptr + 6 * dst_stride_y) = values.s6;
+ *(dst.ptr + 7 * dst_stride_y) = values.s7;
+}
+
+#else // defined(DATA_LAYOUT_NHWC)
+
#if KERNEL_SIZE == 9
#if STRIDE_X == 1
@@ -143,11 +572,11 @@
#elif KERNEL_SIZE == 1
#if STRIDE_X == 3
-#define INPUT_PIXEL extract_input_stride3
+#define INPUT_VALUE extract_input_stride3
#elif STRIDE_X == 2
-#define INPUT_PIXEL extract_input_stride2
+#define INPUT_VALUE extract_input_stride2
#elif STRIDE_X == 1
-#define INPUT_PIXEL extract_input_stride1
+#define INPUT_VALUE extract_input_stride1
#else /* STRIDE_X not equals 1, 2 or 3 */
#error "Only support strides 1, 2 and 3"
@@ -155,40 +584,40 @@
/** Extracts a 1D horizontal vector from the input tensor with stride as 1.
*
- * @param[in] input_pixel Pointer to the first pixel.
+ * @param[in] input_value Pointer to the first value.
*
- * @return extracted input pixels.
+ * @return extracted input values.
*/
-inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_pixel)
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_value)
{
- return vload8(0, input_pixel);
+ return vload8(0, input_value);
}
/** Extracts a 1D horizontal vector from the input tensor with stride as 2.
*
- * @param[in] input_pixel Pointer to the first pixel.
+ * @param[in] input_value Pointer to the first value.
*
- * @return extracted input pixels.
+ * @return extracted input values.
*/
-inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_pixel)
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_value)
{
VEC_DATA_TYPE(DATA_TYPE, 16)
- temp = vload16(0, input_pixel);
+ temp = vload16(0, input_value);
return temp.s02468ace;
}
/** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size.
*
- * @param[in] input_pixel Pointer to the first pixel.
+ * @param[in] input_value Pointer to the first value.
*
- * @return extracted input pixels.
+ * @return extracted input values.
*/
-inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3(__global const DATA_TYPE *input_pixel)
+inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3(__global const DATA_TYPE *input_value)
{
VEC_DATA_TYPE(DATA_TYPE, 16)
- temp1 = vload16(0, input_pixel);
+ temp1 = vload16(0, input_value);
VEC_DATA_TYPE(DATA_TYPE, 16)
- temp2 = vload16(0, input_pixel + 12);
+ temp2 = vload16(0, input_value + 12);
return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s0369, temp2.s0369);
}
@@ -253,7 +682,7 @@
Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
- int8 pixels0 = 0;
+ int8 values0 = 0;
__global DATA_TYPE *weights_addr = (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 0, 0);
__global DATA_TYPE *src_addr = (__global DATA_TYPE *)offset(&src, 0, 0);
@@ -264,29 +693,29 @@
for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d)
{
#if KERNEL_SIZE == 9
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 5 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 5 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 6 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 6 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 7 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 7 * weights_stride_y));
- CONVOLUTION1x9(pixels0, (__global DATA_TYPE *)(src_addr + 8 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 8 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 5 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 5 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 6 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 6 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 7 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 7 * weights_stride_y));
+ CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 8 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 8 * weights_stride_y));
#elif KERNEL_SIZE == 5
- CONVOLUTION1x5(pixels0, (__global DATA_TYPE *)src_addr, (__global DATA_TYPE *)weights_addr);
- CONVOLUTION1x5(pixels0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
- CONVOLUTION1x5(pixels0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
- CONVOLUTION1x5(pixels0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y));
- CONVOLUTION1x5(pixels0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)src_addr, (__global DATA_TYPE *)weights_addr);
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y));
+ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y));
#elif KERNEL_SIZE == 3
- CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y));
- CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
- CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
+ CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
#elif KERNEL_SIZE == 1
int weight = convert_int(*(__global DATA_TYPE *)weights_addr);
- int8 input_pixel = convert_int8(INPUT_PIXEL((__global DATA_TYPE *)src_addr));
- pixels0 += (input_pixel + input_offset) * ((int8)weight + weight_offset);
+ int8 input_value = convert_int8(INPUT_VALUE((__global DATA_TYPE *)src_addr));
+ values0 += (input_value + input_offset) * ((int8)weight + weight_offset);
#endif /* (KERNEL_SIZE == 1) || (KERNEL_SIZE == 3) || (KERNEL_SIZE == 5) */
src_addr += src_stride_z;
@@ -296,16 +725,18 @@
#ifdef HAS_BIAS
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
__global int *bias_addr = ((__global int *)(vector_offset(&biases, kernel_index)));
- pixels0 += (int8)(*bias_addr);
+ values0 += (int8)(*bias_addr);
#endif /* defined(HAS_BIAS) */
#if OUTPUT_SHIFT < 0
- pixels0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(pixels0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
+ values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#else // OUTPUT_SHIFT < 0
- pixels0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(pixels0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
+ values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8);
#endif // OUTPUT_SHIFT < 0
- pixels0 = pixels0 + output_offset;
+ values0 = values0 + output_offset;
- vstore8(CONVERT_SAT(pixels0, DATA_TYPE), 0, (__global DATA_TYPE *)dst.ptr);
+ vstore8(CONVERT_SAT(values0, DATA_TYPE), 0, (__global DATA_TYPE *)dst.ptr);
}
+
+#endif // defined(DATA_LAYOUT_NHWC)
#endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT)