From dfca60b8e8805966624c7c941f289e090e3d73bb Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Wed, 31 Jan 2018 10:30:59 +0000 Subject: COMPMID-811 Add NHWC data format support for CL depthwise convolution QASYMM8 Change-Id: I89de432f3fbcba7abf9e1d4f8396a4334b4fa2c2 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118324 Tested-by: Jenkins Reviewed-by: Gian Marco Iodice --- .../cl_kernels/depthwise_convolution_quantized.cl | 486 ++++++++++++++++++++- 1 file changed, 482 insertions(+), 4 deletions(-) (limited to 'src/core/CL/cl_kernels/depthwise_convolution_quantized.cl') diff --git a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl index 21daee8230..635bc9d50b 100644 --- a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl +++ b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl @@ -24,17 +24,21 @@ #include "helpers_asymm.h" -#if defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) +#if defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) #if defined(FUSED_ACTIVATION) #define DATA_TYPE uchar +#ifndef VEC_SIZE #define VEC_SIZE 8 +#endif /* VEC_SIZE */ #include "activation_layer_qa8.cl" #define ACTIVATION_FUNC(x) PERFORM_ACTIVATION_QA8(FUSED_ACTIVATION, x) #else /* defined(FUSED_ACTIVATION) */ #define ACTIVATION_FUNC(x) (x) #endif /* defined(FUSED_ACTIVATION) */ +#if defined(CONV_STRIDE_Y) && defined(CONV_STRIDE_X) + #if CONV_STRIDE_X > 3 #error "Stride X not supported" #endif /* CONV_STRIDE_X > 3 */ @@ -71,7 +75,7 @@ }) #endif /* CONV_STRIDE_X */ -/** This function computes the horizontal integral of the image and adds offsets. +/** This function computes the depthwise convolution quantized. * * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) @@ -103,7 +107,7 @@ * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector */ -__kernel void depthwise_convolution_3x3_quantized( +__kernel void depthwise_convolution_3x3_quantized_nchw( TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst), TENSOR3D_DECLARATION(weights) @@ -244,4 +248,478 @@ __kernel void depthwise_convolution_3x3_quantized( #endif /* CONV_STRIDE_Y == 1 */ } -#endif /* defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) */ +#endif /* defined(CONV_STRIDE_Y) && defined(CONV_STRIDE_X) */ + +#if defined(VEC_SIZE) && defined(SRC_DEPTH) && defined(CONV_PAD_TOP) && defined(ROWS_READ) + +#define asymm_mult_by_quant_multiplier_less_than_one(x, y, z) ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(x, y, z, VEC_SIZE) + +#define VEC_INT VEC_DATA_TYPE(int, VEC_SIZE) +#define VEC_UCHAR VEC_DATA_TYPE(uchar, VEC_SIZE) + +#define BIFROST_MAD_4(acc, x, y) \ + ({ \ + acc.s0 += (ushort)x.s0 * (ushort)y.s0; \ + acc.s1 += (ushort)x.s1 * (ushort)y.s1; \ + acc.s2 += (ushort)x.s2 * (ushort)y.s2; \ + acc.s3 += (ushort)x.s3 * (ushort)y.s3; \ + }) + +#if WEIGHTS_OFFSET != 0 +#define BIFROST_MAD_ACC_4(acc, sum, x, y) \ + ({ \ + sum += CONVERT(x, VEC_INT); \ + BIFROST_MAD_4(acc, x, y); \ + }) +#else /* WEIGHTS_OFFSET != 0 */ +#define BIFROST_MAD_ACC_4(acc, sum, x, y) BIFROST_MAD_4(acc, x, y) +#endif /* WEIGHTS_OFFSET != 0 */ + +/** This function computes the depthwise convolution quantized. + * + * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 + * @param[in] src_stride_x Stride of the source image 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 image 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_offset_first_element_in_bytes The offset of the first element in the source image + * @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 Y processed per workitem(in bytes) + * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] 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 Y 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: QASYMM8 + * @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 Y 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 (Optional) Pointer to the biases vector. Supported data types: QASYMM8 + * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) + * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector + */ + +__kernel void depthwise_convolution_3x3_quantized_nhwc_stride1( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#if defined(HAS_BIAS) + VECTOR_DECLARATION(biases) +#endif /* defined(HAS_BIAS) */ +) +{ + Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); + Vector weights = CONVERT_TO_VECTOR_STRUCT(weights); +#if defined(HAS_BIAS) + Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); + + VEC_INT bias_values = VLOAD(VEC_SIZE)(0, (__global int *)biases.ptr); +#endif /* defined(HAS_BIAS) */ + + __global uchar *first_elem = src_ptr + src_offset_first_element_in_bytes; + + const int z = get_global_id(2); + const int pad_offs = -ROWS_READ * src_stride_y; + const int src_offs0 = get_global_id(0) * src_step_x + get_global_id(1) * src_step_y + z * src_step_z - CONV_PAD_TOP * src_stride_z; + const int src_offs1 = src_offs0 + src_stride_z; + const int src_offs2 = src_offs1 + src_stride_z; + + const int cond_top = z - CONV_PAD_TOP < 0; + const int cond_bottom = z * (src_step_z / src_stride_z) + 2 >= SRC_DEPTH; + + __global uchar *src_addr0 = first_elem + select(src_offs0, pad_offs, cond_top); + __global uchar *src_addr1 = first_elem + src_offs1; + __global uchar *src_addr2 = first_elem + select(src_offs2, pad_offs, cond_bottom); + + VEC_INT sum_we = 0; + VEC_INT acc0 = 0, acc1 = 0, acc2 = 0, acc3 = 0; + VEC_INT sum0 = 0, sum1 = 0, sum2 = 0, sum3 = 0; + + // z == 0 + VEC_UCHAR w0, w1, w2; + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + VEC_UCHAR values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + BIFROST_MAD_ACC_4(acc1, sum1, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc1, sum1, values, w1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc1, sum1, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + BIFROST_MAD_ACC_4(acc3, sum3, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + BIFROST_MAD_ACC_4(acc3, sum3, values, w1); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc3, sum3, values, w2); + + weights.ptr += weights_stride_z; + + // z == 1 + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + BIFROST_MAD_ACC_4(acc1, sum1, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc1, sum1, values, w1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc1, sum1, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + BIFROST_MAD_ACC_4(acc3, sum3, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + BIFROST_MAD_ACC_4(acc3, sum3, values, w1); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc3, sum3, values, w2); + + weights.ptr += weights_stride_z; + + // z == 2 + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + BIFROST_MAD_ACC_4(acc1, sum1, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc1, sum1, values, w1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc1, sum1, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + BIFROST_MAD_ACC_4(acc3, sum3, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + BIFROST_MAD_ACC_4(acc3, sum3, values, w1); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc3, sum3, values, w2); + +#if defined(HAS_BIAS) + acc0 += bias_values; + acc1 += bias_values; + acc2 += bias_values; + acc3 += bias_values; +#endif /* defined(HAS_BIAS) */ + +#if WEIGHTS_OFFSET != 0 + acc0 += WEIGHTS_OFFSET * sum0; + acc1 += WEIGHTS_OFFSET * sum1; + acc2 += WEIGHTS_OFFSET * sum2; + acc3 += WEIGHTS_OFFSET * sum3; +#endif /* WEIGHTS_OFFSET != 0 */ + +#if INPUT_OFFSET != 0 + VEC_INT offs = INPUT_OFFSET * sum_we; + + acc0 += offs; + acc1 += offs; + acc2 += offs; + acc3 += offs; +#endif /* INPUT_OFFSET != 0 */ + +#if K_OFFSET != 0 + acc0 += (VEC_INT)K_OFFSET; + acc1 += (VEC_INT)K_OFFSET; + acc2 += (VEC_INT)K_OFFSET; + acc3 += (VEC_INT)K_OFFSET; +#endif /* K_OFFSET != 0 */ + + acc0 = asymm_mult_by_quant_multiplier_less_than_one(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + acc1 = asymm_mult_by_quant_multiplier_less_than_one(acc1, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + acc2 = asymm_mult_by_quant_multiplier_less_than_one(acc2, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + acc3 = asymm_mult_by_quant_multiplier_less_than_one(acc3, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + + acc0 += (VEC_INT)OUTPUT_OFFSET; + acc1 += (VEC_INT)OUTPUT_OFFSET; + acc2 += (VEC_INT)OUTPUT_OFFSET; + acc3 += (VEC_INT)OUTPUT_OFFSET; + + VEC_UCHAR res0 = CONVERT_SAT(acc0, VEC_UCHAR); + VEC_UCHAR res1 = CONVERT_SAT(acc1, VEC_UCHAR); + VEC_UCHAR res2 = CONVERT_SAT(acc2, VEC_UCHAR); + VEC_UCHAR res3 = CONVERT_SAT(acc3, VEC_UCHAR); + + res0 = CLAMP(res0, (VEC_UCHAR)0, (VEC_UCHAR)255); + res1 = CLAMP(res1, (VEC_UCHAR)0, (VEC_UCHAR)255); + res2 = CLAMP(res2, (VEC_UCHAR)0, (VEC_UCHAR)255); + res3 = CLAMP(res3, (VEC_UCHAR)0, (VEC_UCHAR)255); + + VSTORE(VEC_SIZE) + (res0, 0, dst.ptr + 0 * dst_stride_y); + VSTORE(VEC_SIZE) + (res1, 0, dst.ptr + 1 * dst_stride_y); + VSTORE(VEC_SIZE) + (res2, 0, dst.ptr + 2 * dst_stride_y); + VSTORE(VEC_SIZE) + (res3, 0, dst.ptr + 3 * dst_stride_y); +} + +/** This function computes the depthwise convolution quantized. + * + * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 + * @param[in] src_stride_x Stride of the source image 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 image 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_offset_first_element_in_bytes The offset of the first element in the source image + * @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 Y processed per workitem(in bytes) + * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] 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 Y 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: QASYMM8 + * @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 Y 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 (Optional) Pointer to the biases vector. Supported data types: QASYMM8 + * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) + * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector + */ + +__kernel void depthwise_convolution_3x3_quantized_nhwc_stride2( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#if defined(HAS_BIAS) + VECTOR_DECLARATION(biases) +#endif /* defined(HAS_BIAS) */ +) +{ + Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); + Vector weights = CONVERT_TO_VECTOR_STRUCT(weights); +#if defined(HAS_BIAS) + Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); + + VEC_INT bias_values = VLOAD(VEC_SIZE)(0, (__global int *)biases.ptr); +#endif /* defined(HAS_BIAS) */ + + __global uchar *first_elem = src_ptr + src_offset_first_element_in_bytes; + + const int z = get_global_id(2); + const int pad_offs = -ROWS_READ * src_stride_y; + const int src_offs0 = get_global_id(0) * src_step_x + get_global_id(1) * src_step_y + z * src_step_z - CONV_PAD_TOP * src_stride_z; + const int src_offs1 = src_offs0 + src_stride_z; + const int src_offs2 = src_offs1 + src_stride_z; + + const int cond_top = z - CONV_PAD_TOP < 0; + const int cond_bottom = z * (src_step_z / src_stride_z) + 2 >= SRC_DEPTH; + ; + + __global uchar *src_addr0 = first_elem + select(src_offs0, pad_offs, cond_top); + __global uchar *src_addr1 = first_elem + src_offs1; + __global uchar *src_addr2 = first_elem + select(src_offs2, pad_offs, cond_bottom); + + VEC_INT sum_we = 0; + VEC_INT acc0 = 0, acc2 = 0; + VEC_INT sum0 = 0, sum2 = 0; + + // z == 0 + VEC_UCHAR w0, w1, w2; + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + VEC_UCHAR values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + + src_addr0 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr0); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + + weights.ptr += weights_stride_z; + + // z == 1 + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + + src_addr1 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr1); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + + weights.ptr += weights_stride_z; + + // z == 2 + w0 = VLOAD(VEC_SIZE)(0, weights.ptr + 0 * weights_stride_y); + w1 = VLOAD(VEC_SIZE)(0, weights.ptr + 1 * weights_stride_y); + w2 = VLOAD(VEC_SIZE)(0, weights.ptr + 2 * weights_stride_y); + +#if INPUT_OFFSET != 0 + sum_we += CONVERT(w0, VEC_INT) + CONVERT(w1, VEC_INT) + CONVERT(w2, VEC_INT); +#endif /* INPUT_OFFSET != 0 */ + + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w1); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc0, sum0, values, w2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w0); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w1); + + src_addr2 += src_stride_y; + values = VLOAD(VEC_SIZE)(0, src_addr2); + BIFROST_MAD_ACC_4(acc2, sum2, values, w2); + +#if defined(HAS_BIAS) + acc0 += bias_values; + acc2 += bias_values; +#endif /* defined(HAS_BIAS) */ + +#if WEIGHTS_OFFSET != 0 + acc0 += WEIGHTS_OFFSET * sum0; + acc2 += WEIGHTS_OFFSET * sum2; +#endif /* WEIGHTS_OFFSET != 0 */ + +#if INPUT_OFFSET != 0 + VEC_INT offs = INPUT_OFFSET * sum_we; + + acc0 += offs; + acc2 += offs; +#endif /* INPUT_OFFSET != 0 */ + +#if K_OFFSET != 0 + acc0 += (VEC_INT)K_OFFSET; + acc2 += (VEC_INT)K_OFFSET; +#endif /* K_OFFSET != 0 */ + + acc0 = asymm_mult_by_quant_multiplier_less_than_one(acc0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + acc2 = asymm_mult_by_quant_multiplier_less_than_one(acc2, OUTPUT_MULTIPLIER, OUTPUT_SHIFT); + acc0 += (VEC_INT)OUTPUT_OFFSET; + acc2 += (VEC_INT)OUTPUT_OFFSET; + VEC_UCHAR res0 = CONVERT_SAT(acc0, VEC_UCHAR); + VEC_UCHAR res2 = CONVERT_SAT(acc2, VEC_UCHAR); + res0 = CLAMP(res0, (VEC_UCHAR)0, (VEC_UCHAR)255); + res2 = CLAMP(res2, (VEC_UCHAR)0, (VEC_UCHAR)255); + + VSTORE(VEC_SIZE) + (res0, 0, dst.ptr + 0 * dst_stride_y); + VSTORE(VEC_SIZE) + (res2, 0, dst.ptr + 1 * dst_stride_y); +} + +#endif /* defined(VEC_SIZE) && defined(SRC_DEPTH) && defined(CONV_PAD_TOP) && defined(ROWS_READ) */ + +#endif /* defined(WEIGHTS_OFFSET) && defined(INPUT_OFFSET) && defined(K_OFFSET) && defined(OUTPUT_OFFSET) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) */ -- cgit v1.2.1