| /* |
| * 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 "QLSTMLayerNormalization.h" |
| #include "ArithmeticOperations.h" |
| #include "MeanStdDevNormalizationLayer.h" |
| #include "PixelWiseMultiplication.h" |
| #include "arm_compute/core/utils/misc/Utility.h" |
| #include "src/core/utils/quantization/AsymmHelpers.cpp" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| SimpleTensor<int16_t> qlstm_layer_normalization(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &weight, const SimpleTensor<int32_t> &bias) |
| { |
| ARM_COMPUTE_ERROR_ON(src.shape().num_dimensions() > 2); |
| SimpleTensor<int16_t> output{ src.shape(), DataType::QSYMM16 }; |
| |
| const auto wq_info = weight.quantization_info().uniform(); |
| int output_multiplier{}; |
| int output_shift{}; |
| const auto s = quantization::calculate_quantized_multiplier(wq_info.scale, &output_multiplier, &output_shift); |
| output_shift *= -1; |
| |
| if(!bool(s)) |
| { |
| output_multiplier = 0; |
| output_shift = 0; |
| } |
| |
| const uint32_t num_batch = src.shape()[1]; |
| const uint32_t num_input = src.shape()[0]; |
| |
| for(uint32_t batch_idx = 0; batch_idx < num_batch; ++batch_idx) |
| { |
| int64_t sum{}; |
| int64_t sum_sq{}; |
| |
| for(uint32_t input_idx = 0; input_idx < num_input; ++input_idx) |
| { |
| const auto index = batch_idx * num_input + input_idx; |
| const auto val = static_cast<int32_t>(src[index]); |
| sum += val; |
| sum_sq += val * val; |
| } |
| |
| const auto temp = static_cast<int64_t>(0x100000) / num_input; |
| const auto mean = sum * 1024 / static_cast<int64_t>(num_input); |
| const auto variance = ((sum_sq * temp) - (mean * mean)) / 0x100000; |
| |
| int32_t stddev_invsqrt_mul{}; |
| int32_t stddev_invsqrt_shift{}; |
| quantization::get_invsqrt_quantized_multiplier_exp(variance, -1, stddev_invsqrt_mul, stddev_invsqrt_shift); |
| |
| for(uint32_t input_idx = 0; input_idx < num_input; ++input_idx) |
| { |
| const auto index = batch_idx * num_input + input_idx; |
| const auto val = static_cast<int32_t>(src[index]); |
| const auto shifted = (val << 10) - mean; |
| const auto rescaled = quantization::multiply_by_quantized_multiplier(shifted, stddev_invsqrt_mul, stddev_invsqrt_shift); |
| const int64_t weighted = rescaled * weight[input_idx] + bias[input_idx]; |
| const auto reverse_shifted = static_cast<int32_t>((weighted + 512) >> 10); |
| auto out_val = quantization::multiply_by_quantized_multiplier(reverse_shifted, output_multiplier, output_shift + 12); |
| out_val = arm_compute::utility::clamp<decltype(out_val), int16_t>(out_val, std::numeric_limits<int16_t>::min()); |
| output[index] = static_cast<int16_t>(out_val); |
| } |
| } |
| return output; |
| } |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |