diff options
Diffstat (limited to 'src/core/NEON/kernels/NELogicalKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NELogicalKernel.cpp | 345 |
1 files changed, 345 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/NELogicalKernel.cpp b/src/core/NEON/kernels/NELogicalKernel.cpp new file mode 100644 index 0000000000..27605e15c6 --- /dev/null +++ b/src/core/NEON/kernels/NELogicalKernel.cpp @@ -0,0 +1,345 @@ +/* + * Copyright (c) 2020 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. + */ +#include "src/core/NEON/kernels/NELogicalKernel.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Validate.h" +#include "src/core/common/Validate.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" + +#include <arm_neon.h> + +namespace arm_compute +{ +namespace kernels +{ +namespace +{ +static const uint8x8_t c0_x8 = vdup_n_u8(0); +static const uint8x16_t c0_x16 = vdupq_n_u8(0); +static const uint8x8_t c1_x8 = vdup_n_u8(1); +static const uint8x16_t c1_x16 = vdupq_n_u8(1); +static const int step = 16; +static const int half_step = step / 2; + +void neon_logical_and(const uint8_t *src0, const uint8_t *src1, uint8_t *dst, int len) +{ + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src0); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src1); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(dst); + ARM_COMPUTE_ASSERT(len >= 0); + + for(; len >= step; len -= step) + { + vst1q_u8(dst, vandq_u8(vminq_u8(vld1q_u8(src0), c1_x16), vminq_u8(vld1q_u8(src1), c1_x16))); + src0 += step; + src1 += step; + dst += step; + } + + for(; len >= half_step; len -= half_step) + { + vst1_u8(dst, vand_u8(vmin_u8(vld1_u8(src0), c1_x8), vmin_u8(vld1_u8(src1), c1_x8))); + src0 += half_step; + src1 += half_step; + dst += half_step; + } + + for(; len > 0; --len) + { + *dst = (*src0) && (*src1); + ++src0; + ++src1; + ++dst; + } +} + +void neon_logical_and_broadcast(const uint8_t *src, uint8_t broadcast_val, uint8_t *dst, int len) +{ + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(dst); + ARM_COMPUTE_ASSERT(len >= 0); + + const auto broadcast_val_clamped_s = std::min<uint8_t>(broadcast_val, 1); + const auto broadcast_val_clamped_x16 = vdupq_n_u8(broadcast_val_clamped_s); + const auto broadcast_val_clamped_x8 = vdup_n_u8(broadcast_val_clamped_s); + + for(; len >= step; len -= step) + { + vst1q_u8(dst, vandq_u8(vminq_u8(vld1q_u8(src), c1_x16), broadcast_val_clamped_x16)); + src += step; + dst += step; + } + + for(; len >= half_step; len -= half_step) + { + vst1_u8(dst, vand_u8(vmin_u8(vld1_u8(src), c1_x8), broadcast_val_clamped_x8)); + src += half_step; + dst += half_step; + } + + for(; len > 0; --len) + { + *dst = (*src) && broadcast_val_clamped_s; + ++src; + ++dst; + } +} + +void neon_logical_or(const uint8_t *src0, const uint8_t *src1, uint8_t *dst, int len) +{ + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src0); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src1); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(dst); + ARM_COMPUTE_ASSERT(len >= 0); + + for(; len >= step; len -= step) + { + vst1q_u8(dst, vorrq_u8(vminq_u8(vld1q_u8(src0), c1_x16), vminq_u8(vld1q_u8(src1), c1_x16))); + src0 += step; + src1 += step; + dst += step; + } + + for(; len >= half_step; len -= half_step) + { + vst1_u8(dst, vorr_u8(vmin_u8(vld1_u8(src0), c1_x8), vmin_u8(vld1_u8(src1), c1_x8))); + src0 += half_step; + src1 += half_step; + dst += half_step; + } + + for(; len > 0; --len) + { + *dst = (*src0) || (*src1); + ++src0; + ++src1; + ++dst; + } +} + +void neon_logical_or_broadcast(const uint8_t *src, uint8_t broadcast_val, uint8_t *dst, int len) +{ + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(dst); + ARM_COMPUTE_ASSERT(len >= 0); + + const auto broadcast_val_clamped_s = std::min<uint8_t>(broadcast_val, 1); + const auto broadcast_val_clamped_x16 = vdupq_n_u8(broadcast_val_clamped_s); + const auto broadcast_val_clamped_x8 = vdup_n_u8(broadcast_val_clamped_s); + + for(; len >= step; len -= step) + { + vst1q_u8(dst, vorrq_u8(vminq_u8(vld1q_u8(src), c1_x16), broadcast_val_clamped_x16)); + src += step; + dst += step; + } + + for(; len >= half_step; len -= half_step) + { + vst1_u8(dst, vorr_u8(vmin_u8(vld1_u8(src), c1_x8), broadcast_val_clamped_x8)); + src += half_step; + dst += half_step; + } + + for(; len > 0; --len) + { + *dst = (*src) || broadcast_val_clamped_s; + ++src; + ++dst; + } +} + +void neon_logical_not(const uint8_t *src, uint8_t *dst, int len) +{ + ARM_COMPUTE_ASSERT_NOT_NULLPTR(src); + ARM_COMPUTE_ASSERT_NOT_NULLPTR(dst); + ARM_COMPUTE_ASSERT(len >= 0); + + for(; len >= step; len -= step) + { + vst1q_u8(dst, vbslq_u8(vceqq_u8(vld1q_u8(src), c0_x16), c1_x16, c0_x16)); + src += step; + dst += step; + } + + for(; len >= half_step; len -= half_step) + { + vst1_u8(dst, vbsl_u8(vceq_u8(vld1_u8(src), c0_x8), c1_x8, c0_x8)); + src += half_step; + dst += half_step; + } + + for(; len > 0; --len) + { + *dst = !(*src); + ++src; + ++dst; + } +} + +void run_unary(const Window &window, const ITensor *src, ITensor *dst) +{ + Window win{ window }; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + const auto len = static_cast<int>(window.x().end()) - static_cast<int>(window.x().start()); + + Iterator in(src, win); + Iterator out(dst, win); + + execute_window_loop(win, [&](const Coordinates &) + { + neon_logical_not(in.ptr(), out.ptr(), len); + }, + in, out); +} + +void run_binary(const Window &window, const ITensor *src0, const ITensor *src1, ITensor *dst, LogicalOperation op) +{ + Window src0_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape()); + Window src1_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape()); + + Window win{ window }; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x(); + const auto len = static_cast<int>(window.x().end()) - static_cast<int>(window.x().start()); + + if(is_broadcast_across_x) + { + using LogicalBroadcastUKernelPtr = std::add_pointer<void(const uint8_t *, uint8_t, uint8_t *, int)>::type; + LogicalBroadcastUKernelPtr logical_func = op == LogicalOperation::Or ? &neon_logical_or_broadcast : &neon_logical_and_broadcast; + + const bool is_broadcast_input_1 = src1_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_1 ? src1_win : src0_win; + Window non_broadcast_win = !is_broadcast_input_1 ? src1_win : src0_win; + const ITensor *broadcast_tensor = is_broadcast_input_1 ? src1 : src0; + const ITensor *non_broadcast_tensor = !is_broadcast_input_1 ? src1 : src0; + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_in(broadcast_tensor, broadcast_win); + Iterator non_broadcast_in(non_broadcast_tensor, non_broadcast_win); + Iterator out(dst, win); + + execute_window_loop(win, [&](const Coordinates &) + { + const uint8_t broadcast_value = *broadcast_in.ptr(); + logical_func(non_broadcast_in.ptr(), broadcast_value, out.ptr(), len); + + }, + broadcast_in, non_broadcast_in, out); + } + else + { + using LogicalUKernelPtr = std::add_pointer<void(const uint8_t *, const uint8_t *, uint8_t *, int)>::type; + LogicalUKernelPtr logical_func = op == LogicalOperation::Or ? &neon_logical_or : &neon_logical_and; + + src0_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + src1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator in0(src0, src0_win); + Iterator in1(src1, src1_win); + Iterator out(dst, win); + execute_window_loop(win, [&](const Coordinates &) + { + logical_func(in0.ptr(), in1.ptr(), out.ptr(), len); + }, + in0, in1, out); + } +} +} // namespace +const char *NELogicalKernel::name() const +{ + return "NELogicalKernel"; +} + +void NELogicalKernel::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, LogicalOperation op) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input1, output); + ARM_COMPUTE_ERROR_THROW_ON(validate(input1, input2, output, op)); + + _op = op; + + Window win = calculate_max_window(*input1, Steps()); + TensorShape out_shape = input1->tensor_shape(); + if(op != LogicalOperation::Not) + { + ARM_COMPUTE_ERROR_ON_NULLPTR(input2); + const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2); + out_shape = broadcast_pair.first; + win = calculate_max_window(broadcast_pair.second, Steps()); + } + ICPPKernel::configure(win); + + // Auto initialize if empty + set_shape_if_empty(*output, out_shape); + set_data_type_if_unknown(*output, input1->data_type()); +} + +Status NELogicalKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, LogicalOperation op) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8); + ARM_COMPUTE_RETURN_ERROR_ON(op == LogicalOperation::Unknown); + + TensorShape out_shape = input1->tensor_shape(); + if(op != LogicalOperation::Not) + { + out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape()); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2); + } + + // Checks performed when output is configured + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, output); + } + + return Status{}; +} + +void NELogicalKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + ARM_COMPUTE_ERROR_ON(tensors.empty()); + + const ITensor *src0 = tensors.get_const_tensor(TensorType::ACL_SRC_0); + const ITensor *src1 = tensors.get_const_tensor(TensorType::ACL_SRC_1); + ITensor *dst = tensors.get_tensor(TensorType::ACL_DST); + + if(_op == LogicalOperation::Not) + { + run_unary(window, src0, dst); + } + else + { + run_binary(window, src0, src1, dst, _op); + } +} +} // namespace kernels +} // namespace arm_compute |