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/*
* 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.
*/
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/Traits.h"
#include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
#include "src/core/helpers/WindowHelpers.h"
namespace arm_compute
{
namespace cpu
{
void sub_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
{
ARM_COMPUTE_UNUSED(policy);
// Create input windows
Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
Window input2_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
// Clear X Dimension on execution window as we handle manually
Window win = window;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
const int window_step_x = 8;
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
if(is_broadcast_across_x)
{
const bool is_broadcast_input_2 = input2_win.x().step() == 0;
Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win;
Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win;
const ITensor *broadcast_tensor = is_broadcast_input_2 ? src1 : src0;
const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
// Clear X Dimension on execution window as we handle manually
non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator broadcast_input(broadcast_tensor, broadcast_win);
Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
Iterator output(dst, win);
execute_window_loop(win, [&](const Coordinates &)
{
const auto non_broadcast_input_ptr = reinterpret_cast<const int16_t *>(non_broadcast_input.ptr());
const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
const int16_t broadcast_value = *reinterpret_cast<const int16_t *>(broadcast_input.ptr());
const int16x8_t broadcast_value_vec = vdupq_n_s16(broadcast_value);
const float32x4x2_t bf =
{
{
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(broadcast_value_vec))), vscale2),
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(broadcast_value_vec))), vscale2),
}
};
const float bfs = static_cast<int32_t>(broadcast_value) * broadcast_qinfo.scale;
// Compute S elements per iteration
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const int16x8_t a = vld1q_s16(non_broadcast_input_ptr + x);
const float32x4x2_t af =
{
{
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
}
};
const int32x4x4_t rf =
{
{
#ifdef __aarch64__
vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
#else //__aarch64__
vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
#endif //__aarch64__
}
};
const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
vst1q_s16(output_ptr + x, pa);
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x)) * non_broadcast_qinfo.scale;
*(output_ptr + x) = quantize_qsymm16(is_broadcast_input_2 ? (bfs - afs) : (afs - bfs), oq_info);
}
},
broadcast_input, non_broadcast_input, output);
}
else
{
// Clear X Dimension on execution window as we handle manually
input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator input1(src0, input1_win);
Iterator input2(src1, input2_win);
Iterator output(dst, win);
execute_window_loop(win, [&](const Coordinates &)
{
const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr());
const auto input2_ptr = reinterpret_cast<const int16_t *>(input2.ptr());
const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
// Compute S elements per iteration
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const int16x8_t a = vld1q_s16(input1_ptr + x);
const int16x8_t b = vld1q_s16(input2_ptr + x);
const float32x4x2_t af =
{
{
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
}
};
const float32x4x2_t bf =
{
{
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2),
vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2),
}
};
const int32x4x2_t rf =
{
{
#ifdef __aarch64__
vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
#else //__aarch64__
vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
#endif //__aarch64__
}
};
const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
vst1q_s16(output_ptr + x, pa);
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
const float afs = static_cast<int32_t>((*(input1_ptr + x))) * iq1_info.scale;
const float bfs = static_cast<int32_t>((*(input2_ptr + x))) * iq2_info.scale;
*(output_ptr + x) = quantize_qsymm16((afs - bfs), dst->info()->quantization_info());
}
},
input1, input2, output);
}
}
} // namespace cpu
} // namespace arm_compute
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