dnn_backend_native_layer_mathbinary.c

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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);
 
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 = ff_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 = ff_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 ff_dnn_load_layer_math_binary(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
{
    DnnLayerMathBinaryParams params = { 0 };
    int dnn_size = 0;
    int input_index = 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;
 
    if (layer->output_operand_index >= operands_num) {
        return 0;
    }
    layer->params = av_memdup(&params, sizeof(params));
    if (!layer->params)
        return 0;
 
    return dnn_size;
}
 
int ff_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 = parameters;
 
    for (int i = 0; i < 4; ++i)
        output->dims[i] = input->dims[i];
 
    output->data_type = input->data_type;
    output->length = ff_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;
    }
}