blob: e83d1ebca6535bde42de740317d42b5b5deeccff [file] [log] [blame]
/*
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "crt/kelvin.h"
#include "tflm/opt/opt.h"
namespace kelvin::opt {
void ElementwiseAddS32(const tflite::ArithmeticParams& params,
const tflite::RuntimeShape& input1_shape,
const int32_t* input1,
const tflite::RuntimeShape& input2_shape,
const int32_t* input2,
const tflite::RuntimeShape& output_shape,
int32_t* output) {
const int32_t output_activation_min = params.quantized_activation_min;
const int32_t output_activation_max = params.quantized_activation_max;
const int block_size =
MatchingElementsSize(input1_shape, input2_shape, output_shape);
int blocks = block_size;
int vl;
getmaxvl_w_m(vl);
while (blocks) {
int count = std::min(blocks, vl);
vld_w_p_xx_m(vm0, input1, count);
vld_w_p_xx_m(vm1, input2, count);
vadd_w_vv_m(vm0, vm0, vm1);
vmin_w_vx_m(vm0, vm0, output_activation_max);
vmax_w_vx_m(vm0, vm0, output_activation_min);
vst_w_p_xx_m(vm0, output, count);
blocks -= count;
}
}
} // namespace kelvin::opt