From d051e97e36b9981f411093904cc019c2c7f9ac75 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Wed, 20 Jun 2018 11:46:42 +0100 Subject: COMPMID-811 Add NHWC data format support for CL depthwise convolution Change-Id: I574f7945f0be009c638d860028bce8b52b4120fd Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136484 Tested-by: Jenkins Reviewed-by: Gian Marco Iodice --- src/core/CL/cl_kernels/depthwise_convolution.cl | 363 ++++++++++++++++++++- .../direct_convolution_1x1_3x3_5x5_quantized.cl | 5 + 2 files changed, 360 insertions(+), 8 deletions(-) (limited to 'src/core/CL/cl_kernels') diff --git a/src/core/CL/cl_kernels/depthwise_convolution.cl b/src/core/CL/cl_kernels/depthwise_convolution.cl index 5f4247e5d3..f3aa0d6dd8 100644 --- a/src/core/CL/cl_kernels/depthwise_convolution.cl +++ b/src/core/CL/cl_kernels/depthwise_convolution.cl @@ -451,6 +451,22 @@ __kernel void depthwise_convolution_3x3_stridex2_stridey2_bifrost_f32( #endif // defined(DEPTH_MULTIPLIER) +#if defined(NCHW) +#define in_stride_x src_stride_x +#define in_stride_y src_stride_y +#define in_stride_z src_stride_z +#define out_stride_x dst_stride_x +#define out_stride_y dst_stride_y +#define out_stride_z dst_stride_z +#else //defined(NCHW) +#define in_stride_x src_stride_y +#define in_stride_y src_stride_z +#define in_stride_z src_stride_x +#define out_stride_x dst_stride_y +#define out_stride_y dst_stride_z +#define out_stride_z dst_stride_x +#endif //defined(NCHW) + #if defined(SRC_WIDTH) && defined(DATA_TYPE) /** This kernel reshapes each of the tensor's low three dimensions to single rows. * @@ -484,17 +500,16 @@ __kernel void depthwise_weights_reshape( #endif /* HAS_BIAS */ ) { - Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); #ifdef HAS_BIAS Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); #endif /* HAS_BIAS */ - __global DATA_TYPE *input_ptr = (__global DATA_TYPE *)src.ptr; - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + get_global_id(1) * SRC_WIDTH * dst_stride_x + get_global_id(2) * dst_stride_y; + __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + get_global_id(1) * in_stride_y + get_global_id(2) * in_stride_z; + __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + get_global_id(1) * SRC_WIDTH * dst_stride_x + get_global_id(2) * dst_stride_y; - for(int i = 0; i < SRC_WIDTH; ++i, ++input_ptr) + for(int i = 0; i < SRC_WIDTH; ++i, input_ptr += in_stride_x) { - *((__global DATA_TYPE *)(output_ptr + i * dst_stride_x)) = *input_ptr; + *((__global DATA_TYPE *)(output_ptr + i * dst_stride_x)) = *((__global DATA_TYPE *)input_ptr); } #if defined(HAS_BIAS) @@ -541,7 +556,7 @@ __kernel void depthwise_im2col(TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(d const int src_y = -PAD_TOP + src_pixel_linear / max_initial_x * STRIDE_Y; const int src_z = get_global_id(2) / DEPTH_MULTIPLIER; - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + src_z * src_stride_z; + __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + src_z * in_stride_z; __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst.ptr)); for(int y = src_y; y < src_y + KERNEL_HEIGHT; ++y) @@ -554,7 +569,7 @@ __kernel void depthwise_im2col(TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(d } else { - *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); + *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * in_stride_x + y * in_stride_y)); } } } @@ -596,7 +611,7 @@ __kernel void depthwise_vector_to_tensor( const int z = id0 / patch_size; const int index2D = id0 - z * patch_size; - __global uchar *out_ptr = dst_ptr + dst_offset_first_element_in_bytes + index2D % CONV_WIDTH * dst_stride_x + index2D / CONV_WIDTH * dst_stride_y + z * dst_stride_z; + __global uchar *out_ptr = dst_ptr + dst_offset_first_element_in_bytes + index2D % CONV_WIDTH * out_stride_x + index2D / CONV_WIDTH * out_stride_y + z * out_stride_z; *((__global DATA_TYPE *)out_ptr) = *((__global DATA_TYPE *)src.ptr); } @@ -980,3 +995,335 @@ __kernel void depthwise_convolution_3x3_stridex2_stridey2_bifrost_f16( vstore4(pixels1, 0, (__global half *)(dst.ptr + 1 * dst_stride_y)); } #endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) && defined(DEPTH_MULTIPLIER) + +#if defined(VEC_SIZE) && defined(SRC_DIM_2) && defined(CONV_PAD_TOP) && defined(CONV_PAD_LEFT) + +#define VEC_FLOAT VEC_DATA_TYPE(float, VEC_SIZE) + +#if defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) +/** This function computes the depthwise convolution for NHWC data layout when the stride along the width or height is not 1. + * + * @note The number of elements read per thread must be passed at compile time using -DVEC_SIZE (e.g. -DVEC_SIZE=2) + * @note Dimension two of the input tensor (height for NHWC data layout) must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM_2=112) + * @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1) + * @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1) + * @note The convolution stride along the width must be passed at compile time using -DCONV_STRIDE_X (e.g. -DCONV_STRIDE_Y=X) + * @note The convolution stride along the height must be passed at compile time using -DCONV_STRIDE_Y (e.g. -DCONV_STRIDE_Y=1) + * + * @param[in] src_ptr Pointer to the source image. Supported data types: FP32 + * @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: same as src_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] 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] max_offset Max offset for the input tensor + * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: same as src_ptr + * @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_nhwc( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#if defined(HAS_BIAS) + VECTOR_DECLARATION(biases), +#endif /* defined(HAS_BIAS) */ + int max_offset) +{ + int x = get_global_id(0); // channels + int y = get_global_id(1); // spatial coordinate x + int z = get_global_id(2); // spatial coordinate y + + Vector weights = CONVERT_TO_VECTOR_STRUCT(weights); + + __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(float) * VEC_SIZE; + + int z_coord = 0; + int4 offset = 0; + int4 y_offset = ((int4)(y * CONV_STRIDE_X) + (int4)(0, 1, 2, 3) - CONV_PAD_LEFT) * (int4)src_stride_y; + + // We compute 2x1x1 [C,W,H] elements + VEC_FLOAT acc = 0; + + // Load weights + VEC_FLOAT w0 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w1 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w2 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w3 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w4 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w5 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w6 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 2 * weights_stride_z)); + VEC_FLOAT w7 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 2 * weights_stride_z)); + VEC_FLOAT w8 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 2 * weights_stride_z)); + + // Load input values + // z == 0 + // Clamp z_coord as for z = 0, it can be negative + // z_coord is casted to unsigned int in order to use just a min() operation + // A "-1" 32 bit signed variable converted to unsigned gives 4294967295 + z_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP; + z_coord = min((uint)z_coord, (uint)SRC_DIM_2); + offset = y_offset + (int4)(z_coord * src_stride_z); + offset = min(offset, max_offset); + + VEC_FLOAT values0 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values1 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values2 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + + // z == 1 + // z_coord can be only negative for z = 0 so we do not need to clamp it + // Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset + z_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP + 1; + offset = y_offset + (int4)(z_coord * src_stride_z); + VEC_FLOAT values3 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values4 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values5 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + + // z == 2 + // After z = 1 we can simply add src_stride_z to offset without updating z_coord + // However offset can be out-of-bound so we need to check if it is greater than max_offset + offset += (int4)src_stride_z; + offset = min(offset, max_offset); + VEC_FLOAT values6 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values7 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values8 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + + acc = fma(values0, w0, acc); + acc = fma(values1, w1, acc); + acc = fma(values2, w2, acc); + + acc = fma(values3, w3, acc); + acc = fma(values4, w4, acc); + acc = fma(values5, w5, acc); + + acc = fma(values6, w6, acc); + acc = fma(values7, w7, acc); + acc = fma(values8, w8, acc); + +#if defined(HAS_BIAS) + Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); + VEC_FLOAT bias_values = VLOAD(VEC_SIZE)(0, (__global float *)biases.ptr); + acc += bias_values; +#endif // defined(HAS_BIAS) + + Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); + VSTORE(VEC_SIZE) + (acc, 0, (__global float *)(dst.ptr)); +} +#endif // defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) + +#if defined(NUM_ROWS_PROCESSED) && defined(NUM_PLANES_PROCESSED) +/** This function computes the depthwise convolution for NHWC data layout when the stride along the width and height is 1. + * + * @note The number of elements read per thread must be passed at compile time using -DVEC_SIZE (e.g. -DVEC_SIZE=2) + * @note Dimension two of the input tensor (height for NHWC data layout) must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM_2=112) + * @note The number of rows processed per thread must be passed at compile time using -DNUM_ROWS_PROCESSED (i.e. -DNUM_ROWS_PROCESSED=2) + * @note The number of planes processed per thread must be passed at compile time using -DNUM_PLANES_PROCESSED (i.e. -DNUM_PLANES_PROCESSED=2) + * @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1) + * @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1) + * + * @param[in] src_ptr Pointer to the source image. Supported data types: FP32 + * @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: same as src_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] 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] max_offset Max offset for the input tensor + * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: same as src_ptr + * @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_nhwc_stride1( + TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + TENSOR3D_DECLARATION(weights), +#if defined(HAS_BIAS) + VECTOR_DECLARATION(biases), +#endif /* defined(HAS_BIAS) */ + int max_offset) +{ + int x = get_global_id(0); // channels + int y = get_global_id(1); // spatial coordinate x + int z = get_global_id(2); // spatial coordinate y + + Vector weights = CONVERT_TO_VECTOR_STRUCT(weights); + + __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(float) * VEC_SIZE; + + int z_coord = 0; + int4 offset = 0; + int4 y_offset = ((int4)(y * NUM_ROWS_PROCESSED) + (int4)(0, 1, 2, 3) - CONV_PAD_LEFT) * (int4)src_stride_y; + + // We compute 2x2x2 [C,W,H] elements + VEC_FLOAT acc0 = 0; + VEC_FLOAT acc1 = 0; + VEC_FLOAT acc2 = 0; + VEC_FLOAT acc3 = 0; + + // Load weights + VEC_FLOAT w0 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w1 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w2 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 0 * weights_stride_z)); + VEC_FLOAT w3 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w4 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w5 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 1 * weights_stride_z)); + VEC_FLOAT w6 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 0 * weights_stride_y + 2 * weights_stride_z)); + VEC_FLOAT w7 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 1 * weights_stride_y + 2 * weights_stride_z)); + VEC_FLOAT w8 = VLOAD(VEC_SIZE)(0, (__global float *)(weights.ptr + 2 * weights_stride_y + 2 * weights_stride_z)); + + // Load input values + // z == 0 + // Clamp z_coord as for z = 0, it can be negative + // z_coord is casted to unsigned int in order to use just a min() operation + // A "-1" 32 bit signed variable converted to unsigned gives 4294967295 + z_coord = z * NUM_PLANES_PROCESSED - (int)CONV_PAD_TOP; + z_coord = min((uint)z_coord, (uint)SRC_DIM_2); + offset = y_offset + (int4)(z_coord * src_stride_z); + offset = min(offset, max_offset); + + VEC_FLOAT values0 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values1 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values2 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + VEC_FLOAT values3 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s3)); + + // z == 1 + // z_coord can be only negative for z = 0 so we do not need to clamp it + // Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset + z_coord = z * NUM_PLANES_PROCESSED - (int)CONV_PAD_TOP + 1; + offset = y_offset + (int4)(z_coord * src_stride_z); + VEC_FLOAT values4 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values5 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values6 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + VEC_FLOAT values7 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s3)); + + // z == 2 + // After z = 1 we can simply add src_stride_z to offset without updating z_coord + // However offset can be out-of-bound so we need to check if it is greater than max_offset + offset += (int4)src_stride_z; + offset = min(offset, max_offset); + VEC_FLOAT values8 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values9 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values10 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + VEC_FLOAT values11 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s3)); + + // z == 3 + // After z = 1 we can simply add src_stride_z to offset without updating z_coord + // However offset can be out-of-bound so we need to check if it is greater than max_offset + offset += (int4)(src_stride_z); + offset = min(offset, max_offset); + VEC_FLOAT values12 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s0)); + VEC_FLOAT values13 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s1)); + VEC_FLOAT values14 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s2)); + VEC_FLOAT values15 = VLOAD(VEC_SIZE)(0, (__global float *)(src_addr + offset.s3)); + + acc0 = fma(values0, w0, acc0); + acc0 = fma(values1, w1, acc0); + acc0 = fma(values2, w2, acc0); + acc1 = fma(values1, w0, acc1); + acc1 = fma(values2, w1, acc1); + acc1 = fma(values3, w2, acc1); + + acc0 = fma(values4, w3, acc0); + acc0 = fma(values5, w4, acc0); + acc0 = fma(values6, w5, acc0); + acc1 = fma(values5, w3, acc1); + acc1 = fma(values6, w4, acc1); + acc1 = fma(values7, w5, acc1); + + acc0 = fma(values8, w6, acc0); + acc0 = fma(values9, w7, acc0); + acc0 = fma(values10, w8, acc0); + acc1 = fma(values9, w6, acc1); + acc1 = fma(values10, w7, acc1); + acc1 = fma(values11, w8, acc1); + + acc2 = fma(values4, w0, acc2); + acc2 = fma(values5, w1, acc2); + acc2 = fma(values6, w2, acc2); + acc3 = fma(values5, w0, acc3); + acc3 = fma(values6, w1, acc3); + acc3 = fma(values7, w2, acc3); + + acc2 = fma(values8, w3, acc2); + acc2 = fma(values9, w4, acc2); + acc2 = fma(values10, w5, acc2); + acc3 = fma(values9, w3, acc3); + acc3 = fma(values10, w4, acc3); + acc3 = fma(values11, w5, acc3); + + acc2 = fma(values12, w6, acc2); + acc2 = fma(values13, w7, acc2); + acc2 = fma(values14, w8, acc2); + acc3 = fma(values13, w6, acc3); + acc3 = fma(values14, w7, acc3); + acc3 = fma(values15, w8, acc3); + +#if defined(HAS_BIAS) + Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); + + VEC_FLOAT bias_values = VLOAD(VEC_SIZE)(0, (__global float *)biases.ptr); + + acc0 += bias_values; + acc1 += bias_values; + acc2 += bias_values; + acc3 += bias_values; +#endif // defined(HAS_BIAS) + + __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * dst_step_x + y * dst_step_y + (z * NUM_PLANES_PROCESSED) * dst_step_z; + + VSTORE(VEC_SIZE) + (acc0, 0, (__global float *)(dst_addr + 0 * dst_stride_y)); + VSTORE(VEC_SIZE) + (acc1, 0, (__global float *)(dst_addr + 1 * dst_stride_y)); + +#if((DST_DIM_2 % NUM_PLANES_PROCESSED) != 0) + if((z * NUM_PLANES_PROCESSED + 1) < DST_DIM_2) +#endif // ((DST_DIM_2 % NUM_PLANES_PROCESSED) != 0) + { + VSTORE(VEC_SIZE) + (acc2, 0, (__global float *)(dst_addr + 0 * dst_stride_y + 1 * dst_stride_z)); + VSTORE(VEC_SIZE) + (acc3, 0, (__global float *)(dst_addr + 1 * dst_stride_y + 1 * dst_stride_z)); + } +} + +#endif // defined(NUM_ROWS_PROCESSED) && defined(NUM_PLANES_PROCESSED) +#endif // defined(VEC_SIZE) && defined(SRC_DIM_2) && defined(CONV_PAD_TOP) && defined(CONV_PAD_LEFT) \ No newline at end of file diff --git a/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl b/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl index b58dc7af72..ae87420774 100644 --- a/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl +++ b/src/core/CL/cl_kernels/direct_convolution_1x1_3x3_5x5_quantized.cl @@ -296,7 +296,12 @@ __kernel void output_stage_quantized( #if defined(HAS_BIAS) // Load and add bias +#if defined(NCHW) int bias_value = *((__global int *)(vector_offset(&bias, get_global_id(2)))); +#else // defined(NCHW) + int16 bias_value = vload16(0, ((__global int *)(vector_offset(&bias, get_global_id(0) * 16)))); +#endif // defined(NCHW) + vals += (int16)(bias_value); #endif //defined(HAS_BIAS) -- cgit v1.2.1