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/*
* Copyright (c) 2020
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file
* DNN native backend implementation.
*/
#include "dnn_backend_native.h"
#include "libavutil/avassert.h"
#include "dnn_backend_native_layer_mathbinary.h"
typedef float (*FunType)(float src0, float src1);
FunType pfun;
static float sub(float src0, float src1)
{
return src0 - src1;
}
static float add(float src0, float src1)
{
return src0 + src1;
}
static float mul(float src0, float src1)
{
return src0 * src1;
}
static float realdiv(float src0, float src1)
{
return src0 / src1;
}
static float minimum(float src0, float src1)
{
return FFMIN(src0, src1);
}
static float floormod(float src0, float src1)
{
return (float)((int)(src0) % (int)(src1));
}
static void math_binary_commutative(FunType pfun, const DnnLayerMathBinaryParams *params, const DnnOperand *input, DnnOperand *output, DnnOperand *operands, const int32_t *input_operand_indexes)
{
int dims_count;
const float *src;
float *dst;
dims_count = calculate_operand_dims_count(output);
src = input->data;
dst = output->data;
if (params->input0_broadcast || params->input1_broadcast) {
for (int i = 0; i < dims_count; ++i) {
dst[i] = pfun(params->v, src[i]);
}
} else {
const DnnOperand *input1 = &operands[input_operand_indexes[1]];
const float *src1 = input1->data;
for (int i = 0; i < dims_count; ++i) {
dst[i] = pfun(src[i], src1[i]);
}
}
}
static void math_binary_not_commutative(FunType pfun, const DnnLayerMathBinaryParams *params, const DnnOperand *input, DnnOperand *output, DnnOperand *operands, const int32_t *input_operand_indexes)
{
int dims_count;
const float *src;
float *dst;
dims_count = calculate_operand_dims_count(output);
src = input->data;
dst = output->data;
if (params->input0_broadcast) {
for (int i = 0; i < dims_count; ++i) {
dst[i] = pfun(params->v, src[i]);
}
} else if (params->input1_broadcast) {
for (int i = 0; i < dims_count; ++i) {
dst[i] = pfun(src[i], params->v);
}
} else {
const DnnOperand *input1 = &operands[input_operand_indexes[1]];
const float *src1 = input1->data;
for (int i = 0; i < dims_count; ++i) {
dst[i] = pfun(src[i], src1[i]);
}
}
}
int dnn_load_layer_math_binary(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
{
DnnLayerMathBinaryParams *params;
int dnn_size = 0;
int input_index = 0;
params = av_malloc(sizeof(*params));
if (!params)
return 0;
params->bin_op = (int32_t)avio_rl32(model_file_context);
dnn_size += 4;
params->input0_broadcast = (int32_t)avio_rl32(model_file_context);
dnn_size += 4;
if (params->input0_broadcast) {
params->v = av_int2float(avio_rl32(model_file_context));
} else {
layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context);
if (layer->input_operand_indexes[input_index] >= operands_num) {
return 0;
}
input_index++;
}
dnn_size += 4;
params->input1_broadcast = (int32_t)avio_rl32(model_file_context);
dnn_size += 4;
if (params->input1_broadcast) {
params->v = av_int2float(avio_rl32(model_file_context));
} else {
layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context);
if (layer->input_operand_indexes[input_index] >= operands_num) {
return 0;
}
input_index++;
}
dnn_size += 4;
layer->output_operand_index = (int32_t)avio_rl32(model_file_context);
dnn_size += 4;
layer->params = params;
if (layer->output_operand_index >= operands_num) {
return 0;
}
return dnn_size;
}
int dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_operand_indexes,
int32_t output_operand_index, const void *parameters, NativeContext *ctx)
{
const DnnOperand *input = &operands[input_operand_indexes[0]];
DnnOperand *output = &operands[output_operand_index];
const DnnLayerMathBinaryParams *params = (const DnnLayerMathBinaryParams *)parameters;
for (int i = 0; i < 4; ++i)
output->dims[i] = input->dims[i];
output->data_type = input->data_type;
output->length = calculate_operand_data_length(output);
if (output->length <= 0) {
av_log(ctx, AV_LOG_ERROR, "The output data length overflow\n");
return DNN_ERROR;
}
output->data = av_realloc(output->data, output->length);
if (!output->data) {
av_log(ctx, AV_LOG_ERROR, "Failed to reallocate memory for output\n");
return DNN_ERROR;
}
switch (params->bin_op) {
case DMBO_SUB:
math_binary_not_commutative(sub, params, input, output, operands, input_operand_indexes);
return 0;
case DMBO_ADD:
math_binary_commutative(add, params, input, output, operands, input_operand_indexes);
return 0;
case DMBO_MUL:
math_binary_commutative(mul, params, input, output, operands, input_operand_indexes);
return 0;
case DMBO_REALDIV:
math_binary_not_commutative(realdiv, params, input, output, operands, input_operand_indexes);
return 0;
case DMBO_MINIMUM:
math_binary_commutative(minimum, params, input, output, operands, input_operand_indexes);
return 0;
case DMBO_FLOORMOD:
math_binary_not_commutative(floormod, params, input, output, operands, input_operand_indexes);
return 0;
default:
av_log(ctx, AV_LOG_ERROR, "Unmatch math binary operator\n");
return DNN_ERROR;
}
}