From 60247d3deca3c822da0ef8d7390cda08db958830 Mon Sep 17 00:00:00 2001
From: Sergey Lavrushkin <dualfal@gmail.com>
Date: Thu, 24 May 2018 22:05:54 +0300
Subject: [PATCH] Adds dnn inference module for simple convolutional networks.
Reimplements srcnn filter based on it.
---
Changelog | 2 +
libavfilter/vf_srcnn.c | 300 +++------------
libavfilter/vf_srcnn.h | 855 -----------------------------------------
libavutil/Makefile | 3 +
libavutil/dnn_backend_native.c | 382 ++++++++++++++++++
libavutil/dnn_backend_native.h | 40 ++
libavutil/dnn_interface.c | 48 +++
libavutil/dnn_interface.h | 64 +++
libavutil/dnn_srcnn.h | 854 ++++++++++++++++++++++++++++++++++++++++
9 files changed, 1455 insertions(+), 1093 deletions(-)
delete mode 100644 libavfilter/vf_srcnn.h
create mode 100644 libavutil/dnn_backend_native.c
create mode 100644 libavutil/dnn_backend_native.h
create mode 100644 libavutil/dnn_interface.c
create mode 100644 libavutil/dnn_interface.h
create mode 100644 libavutil/dnn_srcnn.h
@@ -9,6 +9,8 @@ version <next>:
- aderivative and aintegral audio filters
- pal75bars and pal100bars video filter sources
- support mbedTLS based TLS
+- DNN inference interface
+- Reimplemented SRCNN filter using DNN inference interface
version 4.0:
@@ -28,164 +28,47 @@
#include "formats.h"
#include "internal.h"
#include "libavutil/opt.h"
-#include "vf_srcnn.h"
#include "libavformat/avio.h"
-
-typedef struct Convolution
-{
- double* kernel;
- double* biases;
- int32_t size, input_channels, output_channels;
-} Convolution;
+#include "libavutil/dnn_interface.h"
typedef struct SRCNNContext {
const AVClass *class;
- /// SRCNN convolutions
- struct Convolution conv1, conv2, conv3;
- /// Path to binary file with kernels specifications
- char* config_file_path;
- /// Buffers for network input/output and feature maps
- double* input_output_buf;
- double* conv1_buf;
- double* conv2_buf;
+ char* model_filename;
+ float* input_output_buf;
+ DNNModule* dnn_module;
+ DNNModel* model;
+ DNNData input_output;
} SRCNNContext;
#define OFFSET(x) offsetof(SRCNNContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
static const AVOption srcnn_options[] = {
- { "config_file", "path to configuration file with network parameters", OFFSET(config_file_path), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
+ { "model_filename", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
{ NULL }
};
AVFILTER_DEFINE_CLASS(srcnn);
-#define CHECK_FILE_SIZE(file_size, srcnn_size, avio_context) if (srcnn_size > file_size){ \
- av_log(context, AV_LOG_ERROR, "error reading configuration file\n");\
- avio_closep(&avio_context); \
- return AVERROR(EIO); \
- }
-
-#define CHECK_ALLOCATION(call, end_call) if (call){ \
- av_log(context, AV_LOG_ERROR, "could not allocate memory for convolutions\n"); \
- end_call; \
- return AVERROR(ENOMEM); \
- }
-
-static int allocate_read_conv_data(Convolution* conv, AVIOContext* config_file_context)
-{
- int32_t kernel_size = conv->output_channels * conv->size * conv->size * conv->input_channels;
- int32_t i;
-
- conv->kernel = av_malloc(kernel_size * sizeof(double));
- if (!conv->kernel){
- return AVERROR(ENOMEM);
- }
- for (i = 0; i < kernel_size; ++i){
- conv->kernel[i] = av_int2double(avio_rl64(config_file_context));
- }
-
- conv->biases = av_malloc(conv->output_channels * sizeof(double));
- if (!conv->biases){
- return AVERROR(ENOMEM);
- }
- for (i = 0; i < conv->output_channels; ++i){
- conv->biases[i] = av_int2double(avio_rl64(config_file_context));
- }
-
- return 0;
-}
-
-static int allocate_copy_conv_data(Convolution* conv, const double* kernel, const double* biases)
+static av_cold int init(AVFilterContext* context)
{
- int32_t kernel_size = conv->output_channels * conv->size * conv->size * conv->input_channels;
+ SRCNNContext* srcnn_context = context->priv;
- conv->kernel = av_malloc(kernel_size * sizeof(double));
- if (!conv->kernel){
+ srcnn_context->dnn_module = ff_get_dnn_module(DNN_NATIVE);
+ if (!srcnn_context->dnn_module){
+ av_log(context, AV_LOG_ERROR, "could not create dnn module\n");
return AVERROR(ENOMEM);
}
- memcpy(conv->kernel, kernel, kernel_size * sizeof(double));
-
- conv->biases = av_malloc(conv->output_channels * sizeof(double));
- if (!conv->kernel){
- return AVERROR(ENOMEM);
- }
- memcpy(conv->biases, biases, conv->output_channels * sizeof(double));
-
- return 0;
-}
-
-static av_cold int init(AVFilterContext* context)
-{
- SRCNNContext *srcnn_context = context->priv;
- AVIOContext* config_file_context;
- int64_t file_size, srcnn_size;
-
- /// Check specified confguration file name and read network weights from it
- if (!srcnn_context->config_file_path){
- av_log(context, AV_LOG_INFO, "configuration file for network was not specified, using default weights for x2 upsampling\n");
-
- /// Create convolution kernels and copy default weights
- srcnn_context->conv1.input_channels = 1;
- srcnn_context->conv1.output_channels = 64;
- srcnn_context->conv1.size = 9;
- CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv1, conv1_kernel, conv1_biases), )
-
- srcnn_context->conv2.input_channels = 64;
- srcnn_context->conv2.output_channels = 32;
- srcnn_context->conv2.size = 1;
- CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv2, conv2_kernel, conv2_biases), )
-
- srcnn_context->conv3.input_channels = 32;
- srcnn_context->conv3.output_channels = 1;
- srcnn_context->conv3.size = 5;
- CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv3, conv3_kernel, conv3_biases), )
- }
- else if (avio_check(srcnn_context->config_file_path, AVIO_FLAG_READ) > 0){
- if (avio_open(&config_file_context, srcnn_context->config_file_path, AVIO_FLAG_READ) < 0){
- av_log(context, AV_LOG_ERROR, "failed to open configuration file\n");
- return AVERROR(EIO);
- }
-
- file_size = avio_size(config_file_context);
-
- /// Create convolution kernels and read weights from file
- srcnn_context->conv1.input_channels = 1;
- srcnn_context->conv1.size = (int32_t)avio_rl32(config_file_context);
- srcnn_context->conv1.output_channels = (int32_t)avio_rl32(config_file_context);
- srcnn_size = 8 + (srcnn_context->conv1.output_channels * srcnn_context->conv1.size *
- srcnn_context->conv1.size * srcnn_context->conv1.input_channels +
- srcnn_context->conv1.output_channels << 3);
- CHECK_FILE_SIZE(file_size, srcnn_size, config_file_context)
- CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv1, config_file_context), avio_closep(&config_file_context))
-
- srcnn_context->conv2.input_channels = (int32_t)avio_rl32(config_file_context);
- srcnn_context->conv2.size = (int32_t)avio_rl32(config_file_context);
- srcnn_context->conv2.output_channels = (int32_t)avio_rl32(config_file_context);
- srcnn_size += 12 + (srcnn_context->conv2.output_channels * srcnn_context->conv2.size *
- srcnn_context->conv2.size * srcnn_context->conv2.input_channels +
- srcnn_context->conv2.output_channels << 3);
- CHECK_FILE_SIZE(file_size, srcnn_size, config_file_context)
- CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv2, config_file_context), avio_closep(&config_file_context))
-
- srcnn_context->conv3.input_channels = (int32_t)avio_rl32(config_file_context);
- srcnn_context->conv3.size = (int32_t)avio_rl32(config_file_context);
- srcnn_context->conv3.output_channels = 1;
- srcnn_size += 8 + (srcnn_context->conv3.output_channels * srcnn_context->conv3.size *
- srcnn_context->conv3.size * srcnn_context->conv3.input_channels
- + srcnn_context->conv3.output_channels << 3);
- if (file_size != srcnn_size){
- av_log(context, AV_LOG_ERROR, "error reading configuration file\n");
- avio_closep(&config_file_context);
- return AVERROR(EIO);
- }
- CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv3, config_file_context), avio_closep(&config_file_context))
-
- avio_closep(&config_file_context);
+ if (!srcnn_context->model_filename){
+ av_log(context, AV_LOG_INFO, "model file for network was not specified, using default network for x2 upsampling\n");
+ srcnn_context->model = (srcnn_context->dnn_module->load_default_model)(DNN_SRCNN);
}
else{
- av_log(context, AV_LOG_ERROR, "specified configuration file does not exist or not readable\n");
+ srcnn_context->model = (srcnn_context->dnn_module->load_model)(srcnn_context->model_filename);
+ }
+ if (!srcnn_context->model){
+ av_log(context, AV_LOG_ERROR, "could not load dnn model\n");
return AVERROR(EIO);
}
@@ -197,7 +80,7 @@ static int query_formats(AVFilterContext* context)
const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
AV_PIX_FMT_NONE};
- AVFilterFormats *formats_list;
+ AVFilterFormats* formats_list;
formats_list = ff_make_format_list(pixel_formats);
if (!formats_list){
@@ -209,28 +92,29 @@ static int query_formats(AVFilterContext* context)
static int config_props(AVFilterLink* inlink)
{
- AVFilterContext *context = inlink->dst;
- SRCNNContext *srcnn_context = context->priv;
- int min_dim;
-
- /// Check if input data width or height is too low
- min_dim = FFMIN(inlink->w, inlink->h);
- if (min_dim <= srcnn_context->conv1.size >> 1 || min_dim <= srcnn_context->conv2.size >> 1 || min_dim <= srcnn_context->conv3.size >> 1){
- av_log(context, AV_LOG_ERROR, "input width or height is too low\n");
- return AVERROR(EIO);
- }
-
- /// Allocate network buffers
- srcnn_context->input_output_buf = av_malloc(inlink->h * inlink->w * sizeof(double));
- srcnn_context->conv1_buf = av_malloc(inlink->h * inlink->w * srcnn_context->conv1.output_channels * sizeof(double));
- srcnn_context->conv2_buf = av_malloc(inlink->h * inlink->w * srcnn_context->conv2.output_channels * sizeof(double));
+ AVFilterContext* context = inlink->dst;
+ SRCNNContext* srcnn_context = context->priv;
+ DNNReturnType result;
- if (!srcnn_context->input_output_buf || !srcnn_context->conv1_buf || !srcnn_context->conv2_buf){
- av_log(context, AV_LOG_ERROR, "could not allocate memory for srcnn buffers\n");
+ srcnn_context->input_output_buf = av_malloc(inlink->h * inlink->w * sizeof(float));
+ if (!srcnn_context->input_output_buf){
+ av_log(context, AV_LOG_ERROR, "could not allocate memory for input/output buffer\n");
return AVERROR(ENOMEM);
}
- return 0;
+ srcnn_context->input_output.data = srcnn_context->input_output_buf;
+ srcnn_context->input_output.width = inlink->w;
+ srcnn_context->input_output.height = inlink->h;
+ srcnn_context->input_output.channels = 1;
+
+ result = (srcnn_context->model->set_input_output)(srcnn_context->model->model, &srcnn_context->input_output, &srcnn_context->input_output);
+ if (result != DNN_SUCCESS){
+ av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
+ return AVERROR(EIO);
+ }
+ else{
+ return 0;
+ }
}
typedef struct ThreadData{
@@ -238,28 +122,19 @@ typedef struct ThreadData{
int out_linesize, height, width;
} ThreadData;
-typedef struct ConvThreadData
-{
- const Convolution* conv;
- const double* input;
- double* output;
- int height, width;
-} ConvThreadData;
-
-/// Convert uint8 data to double and scale it to use in network
-static int uint8_to_double(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
+static int uint8_to_float(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
{
SRCNNContext* srcnn_context = context->priv;
const ThreadData* td = arg;
const int slice_start = (td->height * jobnr ) / nb_jobs;
const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
const uint8_t* src = td->out + slice_start * td->out_linesize;
- double* dst = srcnn_context->input_output_buf + slice_start * td->width;
+ float* dst = srcnn_context->input_output_buf + slice_start * td->width;
int y, x;
for (y = slice_start; y < slice_end; ++y){
for (x = 0; x < td->width; ++x){
- dst[x] = (double)src[x] / 255.0;
+ dst[x] = (float)src[x] / 255.0f;
}
src += td->out_linesize;
dst += td->width;
@@ -268,20 +143,19 @@ static int uint8_to_double(AVFilterContext* context, void* arg, int jobnr, int n
return 0;
}
-/// Convert double data from network to uint8 and scale it to output as filter result
-static int double_to_uint8(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
+static int float_to_uint8(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
{
SRCNNContext* srcnn_context = context->priv;
const ThreadData* td = arg;
const int slice_start = (td->height * jobnr ) / nb_jobs;
const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
- const double* src = srcnn_context->input_output_buf + slice_start * td->width;
+ const float* src = srcnn_context->input_output_buf + slice_start * td->width;
uint8_t* dst = td->out + slice_start * td->out_linesize;
int y, x;
for (y = slice_start; y < slice_end; ++y){
for (x = 0; x < td->width; ++x){
- dst[x] = (uint8_t)(255.0 * FFMIN(src[x], 1.0));
+ dst[x] = (uint8_t)(255.0f * FFMIN(src[x], 1.0f));
}
src += td->width;
dst += td->out_linesize;
@@ -290,45 +164,6 @@ static int double_to_uint8(AVFilterContext* context, void* arg, int jobnr, int n
return 0;
}
-#define CLAMP_TO_EDGE(x, w) ((x) < 0 ? 0 : ((x) >= (w) ? (w - 1) : (x)))
-
-static int convolve(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
-{
- const ConvThreadData* td = arg;
- const int slice_start = (td->height * jobnr ) / nb_jobs;
- const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
- const double* src = td->input;
- double* dst = td->output + slice_start * td->width * td->conv->output_channels;
- int y, x;
- int32_t n_filter, ch, kernel_y, kernel_x;
- int32_t radius = td->conv->size >> 1;
- int src_linesize = td->width * td->conv->input_channels;
- int filter_linesize = td->conv->size * td->conv->input_channels;
- int filter_size = td->conv->size * filter_linesize;
-
- for (y = slice_start; y < slice_end; ++y){
- for (x = 0; x < td->width; ++x){
- for (n_filter = 0; n_filter < td->conv->output_channels; ++n_filter){
- dst[n_filter] = td->conv->biases[n_filter];
- for (ch = 0; ch < td->conv->input_channels; ++ch){
- for (kernel_y = 0; kernel_y < td->conv->size; ++kernel_y){
- for (kernel_x = 0; kernel_x < td->conv->size; ++kernel_x){
- dst[n_filter] += src[CLAMP_TO_EDGE(y + kernel_y - radius, td->height) * src_linesize +
- CLAMP_TO_EDGE(x + kernel_x - radius, td->width) * td->conv->input_channels + ch] *
- td->conv->kernel[n_filter * filter_size + kernel_y * filter_linesize +
- kernel_x * td->conv->input_channels + ch];
- }
- }
- }
- dst[n_filter] = FFMAX(dst[n_filter], 0.0);
- }
- dst += td->conv->output_channels;
- }
- }
-
- return 0;
-}
-
static int filter_frame(AVFilterLink* inlink, AVFrame* in)
{
AVFilterContext* context = inlink->dst;
@@ -336,8 +171,8 @@ static int filter_frame(AVFilterLink* inlink, AVFrame* in)
AVFilterLink* outlink = context->outputs[0];
AVFrame* out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
ThreadData td;
- ConvThreadData ctd;
int nb_threads;
+ DNNReturnType dnn_result;
if (!out){
av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
@@ -349,24 +184,19 @@ static int filter_frame(AVFilterLink* inlink, AVFrame* in)
av_frame_free(&in);
td.out = out->data[0];
td.out_linesize = out->linesize[0];
- td.height = ctd.height = out->height;
- td.width = ctd.width = out->width;
+ td.height = out->height;
+ td.width = out->width;
nb_threads = ff_filter_get_nb_threads(context);
- context->internal->execute(context, uint8_to_double, &td, NULL, FFMIN(td.height, nb_threads));
- ctd.conv = &srcnn_context->conv1;
- ctd.input = srcnn_context->input_output_buf;
- ctd.output = srcnn_context->conv1_buf;
- context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, nb_threads));
- ctd.conv = &srcnn_context->conv2;
- ctd.input = srcnn_context->conv1_buf;
- ctd.output = srcnn_context->conv2_buf;
- context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, nb_threads));
- ctd.conv = &srcnn_context->conv3;
- ctd.input = srcnn_context->conv2_buf;
- ctd.output = srcnn_context->input_output_buf;
- context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, nb_threads));
- context->internal->execute(context, double_to_uint8, &td, NULL, FFMIN(td.height, nb_threads));
+ context->internal->execute(context, uint8_to_float, &td, NULL, FFMIN(td.height, nb_threads));
+
+ dnn_result = (srcnn_context->dnn_module->execute_model)(srcnn_context->model);
+ if (dnn_result != DNN_SUCCESS){
+ av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
+ return AVERROR(EIO);
+ }
+
+ context->internal->execute(context, float_to_uint8, &td, NULL, FFMIN(td.height, nb_threads));
return ff_filter_frame(outlink, out);
}
@@ -375,18 +205,11 @@ static av_cold void uninit(AVFilterContext* context)
{
SRCNNContext* srcnn_context = context->priv;
- /// Free convolution data
- av_freep(&srcnn_context->conv1.kernel);
- av_freep(&srcnn_context->conv1.biases);
- av_freep(&srcnn_context->conv2.kernel);
- av_freep(&srcnn_context->conv2.biases);
- av_freep(&srcnn_context->conv3.kernel);
- av_freep(&srcnn_context->conv3.kernel);
-
- /// Free network buffers
+ if (srcnn_context->dnn_module){
+ (srcnn_context->dnn_module->free_model)(&srcnn_context->model);
+ av_freep(&srcnn_context->dnn_module);
+ }
av_freep(&srcnn_context->input_output_buf);
- av_freep(&srcnn_context->conv1_buf);
- av_freep(&srcnn_context->conv2_buf);
}
static const AVFilterPad srcnn_inputs[] = {
@@ -419,3 +242,4 @@ AVFilter ff_vf_srcnn = {
.priv_class = &srcnn_class,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
};
+
deleted file mode 100644
@@ -1,855 +0,0 @@
-/*
- * Copyright (c) 2018 Sergey Lavrushkin
- *
- * 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
- * Default cnn weights for x2 upsampling with srcnn filter.
- */
-#ifndef AVFILTER_SRCNN_H
-#define AVFILTER_SRCNN_H
-
-/// First convolution kernel
-static const double conv1_kernel[] = {
--0.08866337686777115, 0.055409565567970276, 0.037196505814790726, -0.11961404234170914, -0.12341991066932678, 0.2996342182159424, -0.09118170291185379, -0.00013613555347546935, -0.049023594707250595,
-0.038421183824539185, -0.07726779580116272, 0.027273094281554222, 0.45762088894844055, 0.023581644520163536, -0.20363852381706238, -0.07738441973924637, 0.07288403809070587, 0.06679897010326385,
--0.07315085083246231, 0.2665306031703949, 0.07836370915174484, -0.2898528277873993, -0.506912887096405, 0.0446651317179203, -0.06246858835220337, -0.024424826726317406, -0.029072929173707962,
--0.16884787380695343, 0.20686236023902893, -0.2536700665950775, -0.38499701023101807, -0.12601901590824127, 0.7257882356643677, 0.09588377922773361, -0.04487278312444687, -0.011251595802605152,
--0.02955852635204792, 0.2211706042289734, -0.3845316469669342, -0.053509537130594254, 0.10955915600061417, 0.3725738823413849, -0.28968045115470886, -0.10883618891239166, 0.19628790020942688,
-0.09746792912483215, -0.005647096782922745, -0.13035884499549866, 0.6254252195358276, 0.19104234874248505, -0.011692332103848457, -0.27067890763282776, -0.030754156410694122, 0.029875505715608597,
-0.016808750107884407, -0.1831790804862976, -0.16016070544719696, 0.3598291277885437, -0.1889011114835739, -0.22343340516090393, -0.11111768335103989, 0.3221142590045929, -0.18514074385166168,
--0.06647012382745743, 0.1800554096698761, -0.0356597937643528, -0.25352174043655396, -0.18370479345321655, 0.2839542329311371, 0.0030237233731895685, 0.24072711169719696, -0.1435547173023224,
-0.0474187433719635, -0.03221237286925316, -0.08801338076591492, 0.2959175109863281, 0.04108741134405136, -0.103544220328331, -0.11681117117404938, -0.010267493315041065, 0.023703521117568016,
-
--0.043954458087682724, 0.0953388437628746, 0.12233797460794449, -0.0521148182451725, 0.068812295794487, 0.0576486811041832, 0.08686650544404984, -0.12001238018274307, 0.02353638783097267,
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--0.1187233105301857, 0.06795468926429749, -0.19596466422080994, 0.09043551236391068, -0.07781103998422623, 0.06362947076559067, -0.04456653818488121, -0.13828079402446747, 0.1451389342546463,
-
-0.002784173935651779, 0.01319826114922762, 0.03299565985798836, -0.009061452932655811, -0.03782084956765175, 0.05905524268746376, 0.03665812313556671, -0.03293836489319801, 0.007655598223209381,
--0.02654659003019333, -0.051362812519073486, -0.019685762003064156, -0.04363385960459709, -0.033689528703689575, -0.04015159234404564, -0.030751371756196022, -0.02246842533349991, 0.018601812422275543,
-0.012158050201833248, 0.015349633991718292, 0.03493561968207359, -0.01330295018851757, 0.03794550150632858, -0.003826811444014311, -0.044383760541677475, -0.07613663375377655, 0.014979931525886059,
-0.0436096116900444, 0.06885120272636414, 0.09881002455949783, 0.031302209943532944, 0.12420085072517395, 0.15065008401870728, 0.07978155463933945, -0.027734771370887756, -0.05383369326591492,
--0.0678027868270874, 0.002182385651394725, 0.13103488087654114, 0.05609790235757828, 0.05619135499000549, 0.08134319633245468, 0.10918274521827698, 0.10301676392555237, -0.02375829964876175,
--0.08856120705604553, -0.03078402765095234, 0.08737516403198242, 0.013652728870511055, 0.01163883414119482, -0.00604214845225215, 0.056429434567689896, 0.10691829025745392, 0.041128937155008316,
--0.04340420290827751, -0.002507368801161647, 0.012957162223756313, 0.012340170331299305, 0.11861597746610641, 0.09244049340486526, 0.034744489938020706, -0.024895809590816498, 0.035870663821697235,
--0.040758680552244186, 0.013552304357290268, -0.009587780572474003, 0.01752828061580658, 0.07450903207063675, 0.0692441463470459, 0.0011354148155078292, -0.06966304779052734, 0.008092116564512253,
-0.02915072999894619, 0.04350604489445686, -0.03975748270750046, 0.014310178346931934, 0.0008435412310063839, -0.013759381137788296, 0.02635800465941429, 0.08823874592781067, 0.0821344256401062
-};
-
-/// First convolution biases
-static const double conv1_biases[] = {
--0.01660689152777195,
--0.011107334867119789,
--0.00483096856623888,
--0.048673778772354126,
--0.030040957033634186,
--0.07297247648239136,
--0.01945866458117962,
--0.009738028049468994,
-0.6951230764389038,
--0.07369442284107208,
--0.01354204025119543,
-0.010336088016629219,
--0.02956176921725273,
-0.018691286444664,
--0.02167515829205513,
-0.004088825546205044,
--0.08033090084791183,
--0.02080247923731804,
--0.00025044166250154376,
-0.015665635466575623,
--0.024439847096800804,
--0.00014609392383135855,
--5.004818376619369e-05,
--0.0011854040203616023,
--8.353819430340081e-05,
-0.0,
--0.00037626884295605123,
-0.02971580997109413,
--9.940328891389072e-05,
--0.020136557519435883,
--0.00029498152434825897,
-0.019285818561911583,
-0.005577716510742903,
--0.0700315311551094,
--0.024398552253842354,
--1.7726930309436284e-05,
-0.0050997124053537846,
--0.011211924254894257,
-0.004536128137260675,
--0.024612177163362503,
--0.0225357823073864,
--0.00016232267080340534,
--0.00017362962535116822,
--1.552602043375373e-05,
--0.06559696048498154,
--0.0065806107595562935,
-6.683926585537847e-06,
-0.0252289529889822,
--0.0013730665668845177,
-0.030351819470524788,
-0.0,
-0.003285621991381049,
-0.0055278814397752285,
-0.020766519010066986,
--0.00849062204360962,
-0.026332268491387367,
--0.04678987339138985,
-0.010329566895961761,
--0.023649320006370544,
-0.027851572260260582,
-0.05440746247768402,
--0.08068252354860306,
--0.009446502663195133,
--0.04663233831524849
-};
-
-/// Second convolution kernel
-static const double conv2_kernel[] = {
--0.24004751443862915, 0.10371380299329758, 0.11173403263092041, 0.04352091997861862, -0.2372848093509674, 0.1215374693274498, -0.23676058650016785, -0.28548064827919006, -0.6127380132675171, -0.12218937277793884, -0.06005159020423889, 0.18506519496440887, 0.16014674305915833, 0.13922938704490662, 0.2135942578315735, 0.10787945240736008, -0.26999104022979736, -0.14241325855255127, -0.0013871012488380075, -0.004951587878167629, 0.3402169644832611, 0.0005581695586442947, 4.7351106331916526e-05, 0.0037513396237045527, 0.0011569701600819826, 0.001654176157899201, -0.0011876021744683385, 0.049887992441654205, -7.201619882835075e-05, -0.17735491693019867, 0.0011244657216593623, -0.22381487488746643, 0.0035836962051689625, -0.3210694193840027, -0.16167263686656952, -0.0007922835648059845, 0.05056063085794449, 0.21074672043323517, 0.07716237753629684, -0.3315621614456177, 0.06265880912542343, 0.0002542850561439991, -0.0012989661190658808, 0.0004486947145778686, -0.41594547033309937, -0.019950004294514656, 0.0002566903131082654, 0.17913155257701874, -0.5950504541397095, 0.3259836733341217, 0.0013792524114251137, -0.08931709825992584, -0.13066786527633667, 0.21108511090278625, -0.05854453891515732, -0.11937838047742844, 0.08559372276067734, -0.11413642764091492, 0.28384047746658325, -0.011619674041867256, 0.32102328538894653, -0.20085231959819794, -0.34134379029273987, -0.029155191034078598,
-
--0.15286806225776672, -0.45100340247154236, -0.07077684253454208, 0.14408659934997559, 0.05953073874115944, -0.03657171502709389, 0.3870140314102173, -0.12762507796287537, 0.059950776398181915, 0.00540902791544795, 0.16427578032016754, -0.042501527816057205, 0.032962359488010406, -0.19972456991672516, -0.2558594048023224, -0.05479712411761284, -0.1335245817899704, 0.051931269466876984, -0.0005906695732846856, 0.14123854041099548, -0.06595169752836227, 0.0002593870449345559, 0.0004935731994919479, 0.0018757024081423879, -0.0004157331713940948, 0.0006128620007075369, -0.0008253702544607222, 0.00875023566186428, 0.000315613579005003, -0.031592708081007004, -0.0011055622017011046, 0.5397407412528992, 0.16837793588638306, 0.10016077756881714, -0.04458073899149895, -0.0008208212675526738, 0.14558495581150055, 0.05370355769991875, 0.3998671770095825, 0.3651335835456848, -6.220484647201374e-05, -0.0015507896896451712, 0.00019759316637646407, 0.001477571902796626, 0.17199119925498962, 0.20428548753261566, 0.0007169281598180532, -0.15589089691638947, 0.13173037767410278, 0.0430227592587471, 0.0005358970374800265, -0.14488573372364044, -0.056273844093084335, 0.04060659557580948, 0.12327120453119278, -0.0687263160943985, 0.1168481707572937, 0.20592212677001953, -0.07642778009176254, -0.10591034591197968, -0.2585831880569458, -0.234173983335495, 0.1204083263874054, -0.09154298901557922,
-
-0.1729278564453125, 0.12093151360750198, 0.12173106521368027, -0.17765463888645172, -0.03842559829354286, 0.1379096508026123, -0.018014583736658096, -0.00353326671756804, 0.052375391125679016, -0.013713608495891094, -0.023778876289725304, 0.08754374086856842, 0.009544276632368565, 0.002218334935605526, 0.005476833321154118, 0.14335989952087402, -0.30521509051322937, -0.027671312913298607, 0.0002961017016787082, -0.09087705612182617, 0.08001929521560669, 0.000289166287984699, 8.447665459243581e-05, 0.0032733778934925795, -0.0009773650672286749, 0.000969415414147079, 0.0023891173768788576, 0.1590563803911209, 0.00069234031252563, -0.23975391685962677, 0.0003552400739863515, -0.15277449786663055, 0.09689000993967056, -0.13403186202049255, -0.10830442607402802, -0.0011496500810608268, -0.0791272521018982, -0.04548552632331848, 0.07143749296665192, -0.11953869462013245, 0.06519463658332825, 0.0004770815430674702, -0.0012068727519363165, 0.00023571185010951012, -0.02185177616775036, -0.10972553491592407, -0.0004428153915796429, -0.06199837476015091, -0.02185823768377304, 0.13159608840942383, 0.0011464811395853758, -0.12141252309083939, -0.06273757666349411, 0.2553664743900299, 0.1002097874879837, 0.13120368123054504, 0.16516226530075073, -0.14927655458450317, 0.14413973689079285, 0.039363794028759, 0.19443942606449127, -0.01614764891564846, -0.0876186192035675, 0.08571985363960266,
-
--0.034732215106487274, 0.08880914747714996, 0.115323506295681, -0.2509199380874634, -0.18177348375320435, 0.11170994490385056, -0.06447608023881912, -0.04730312153697014, -0.13159127533435822, 0.01896033063530922, -0.2969268262386322, 0.31513679027557373, 0.016690406948328018, 0.0855814516544342, 0.01695072464644909, 0.1360795795917511, -0.008597755804657936, -0.15839214622974396, -0.0006356500089168549, 0.14604529738426208, 0.029391299933195114, -0.0021237179171293974, -0.0021662425715476274, 0.0011421579401940107, 0.00031981870415620506, -0.00031888089142739773, -0.0013892676215618849, 0.4037177860736847, 0.0010367054492235184, -0.08923333138227463, 0.001726223505102098, 0.04937814548611641, 0.03052854910492897, -0.10994968563318253, 0.041772034019231796, -0.0003509650705382228, -0.09172547608613968, -0.1121240183711052, 0.018248941749334335, -0.1032114252448082, 0.03656036779284477, -0.0008534444496035576, 0.0005108112818561494, 0.001955348066985607, -0.17280977964401245, -0.15745718777179718, 0.0016406632494181395, 0.10295743495225906, -0.056333065032958984, 0.12174493074417114, -0.00029968394665047526, -0.046295735985040665, -0.05203622952103615, 0.17915867269039154, 0.17138905823230743, 0.20149874687194824, 0.14662422239780426, -0.06499027460813522, 0.0864318460226059, 0.026575079187750816, -0.26568517088890076, -0.10079117864370346, -0.20195038616657257, 0.07289135456085205,
-
-0.20596843957901, 0.1484273374080658, 0.11689981073141098, -0.292439341545105, 0.02092818170785904, 0.14047744870185852, -0.032774657011032104, 0.013994990848004818, 0.04893071949481964, -0.0856017917394638, 0.07281561940908432, 0.0699431449174881, -0.006538144778460264, 0.08474163711071014, 0.013837413862347603, 0.10437792539596558, -0.32318544387817383, -0.033461928367614746, -0.0006234075990505517, -0.25232645869255066, 0.08134997636079788, -0.0012573037529364228, -0.00025874844868667424, 0.002164048608392477, 0.000704825681168586, 0.0008626107592135668, -0.0004994627670384943, 0.1802779585123062, 0.0005355331813916564, -0.3850158154964447, -0.000660755904391408, -0.15524353086948395, 0.0770384892821312, -0.1990944892168045, -0.04059717804193497, 0.00019839264859911054, -0.08954143524169922, -0.1745176762342453, 0.19342899322509766, -0.039949242025613785, -0.05351455509662628, 0.0010188281303271651, 0.0012863714946433902, -4.699235432781279e-05, 0.04647690802812576, -0.1538148671388626, -0.0009432003716938198, 0.06832418590784073, -0.07473438233137131, 0.19692155718803406, -0.00023191161744762212, -0.07189866900444031, -0.08010462671518326, 0.22581109404563904, 0.11592476069927216, 0.17914976179599762, 0.13195598125457764, -0.1110662892460823, 0.12462127208709717, 0.006350248120725155, 0.09321404248476028, 0.032797329127788544, 0.0406208336353302, 0.07625015079975128,
-
-0.26654642820358276, 0.006987582892179489, 0.056940462440252304, -0.21681314706802368, 0.07780187577009201, 0.0550677552819252, -0.07760556042194366, 0.03872932121157646, -0.7930355668067932, -0.1105983555316925, 0.11750592291355133, 0.13262803852558136, -0.06422358006238937, 0.02154429443180561, 0.10654937475919724, 0.05221962183713913, -0.48878803849220276, -0.22840070724487305, 0.0011379553470760584, 0.15314219892024994, 0.07926332950592041, 0.0003804231819231063, 0.0017872434109449387, 0.0007042611250653863, 0.0002458576636854559, -0.001502114930190146, 0.00033512181835249066, 0.1798011213541031, -0.00030350624001584947, -0.09183648973703384, -0.00031797270639799535, -0.17676876485347748, 0.05354951694607735, -0.30156299471855164, 0.019367441534996033, -0.00010185350402025506, -0.03712425008416176, -0.07796591520309448, -0.1688132882118225, -0.5796422958374023, 0.15654867887496948, -0.0013217078521847725, -0.001091445330530405, 0.0011883607367053628, 0.10660554468631744, -0.12484317272901535, 0.0004226503078825772, 0.09296494722366333, -0.38826271891593933, 0.2994518280029297, 0.0007777059799991548, -0.2824214696884155, -0.09771981835365295, 0.30562764406204224, 0.21152275800704956, 0.07008504122495651, 0.08235848695039749, -0.009461170062422752, 0.14994531869888306, 0.025700503960251808, 0.2208600640296936, 0.016543129459023476, -0.04067225754261017, 0.012883936055004597,
-
-0.00617796229198575, -0.013291561044752598, 0.1916685402393341, -0.017105795443058014, -0.07506846636533737, 0.18045775592327118, -0.30787673592567444, 0.04832560196518898, 0.05962129309773445, 0.1261044591665268, -0.2459549754858017, 0.12365790456533432, 0.028636902570724487, -0.006177236791700125, -0.04891420155763626, 0.16809219121932983, -0.10486529022455215, -0.10494883358478546, -0.0004520704969763756, 0.23579229414463043, 0.05076323449611664, -0.001182716921903193, -0.0001052700899890624, 0.0018256279872730374, 0.0008991276263259351, -0.001528103486634791, -0.0005336360190995038, 0.16323579847812653, 0.0020393324084579945, 0.015845002606511116, 0.0016316768014803529, -0.06386037170886993, 0.0540936253964901, -0.14962895214557648, -0.014346976764500141, 0.0012925119372084737, -0.12354017049074173, 0.016353895887732506, -0.2519243061542511, -0.042811259627342224, 0.19090451300144196, -0.00022991615696810186, 0.0018943509785458446, -0.0005430503515526652, -0.11097119003534317, -0.05055755749344826, -0.001144487177953124, -0.002318614162504673, -0.11912520974874496, -0.022436127066612244, 0.00014450220623984933, -0.1372481733560562, -0.02418547123670578, 0.24273015558719635, 0.1387740820646286, 0.1362992823123932, 0.15725626051425934, -0.157984659075737, 0.10887137055397034, 0.07719193398952484, 0.09739567339420319, -0.09165967255830765, -0.2062297910451889, 0.11893536150455475,
-
--0.09508167952299118, -0.07543941587209702, 0.2706283628940582, 0.08787128329277039, 0.10140055418014526, 0.26852965354919434, -0.5909307599067688, 0.19821986556053162, 0.08937512338161469, 0.05567803606390953, -0.11613370478153229, 0.03911638632416725, 0.06315726786851883, 0.10782184451818466, -0.01980738714337349, 0.1451241374015808, -0.060943953692913055, -0.07014007121324539, 0.00016978045459836721, 0.17468222975730896, 0.06063257157802582, -7.286974141607061e-05, 0.0005939672118984163, 0.0018404772272333503, 0.001129048760049045, 0.00019233254715800285, 0.0019600382074713707, 0.07629802823066711, 0.0003428335185162723, -0.0005339051713235676, -0.00011325302330078557, -0.03201869875192642, 0.04179591313004494, -0.3185126781463623, 0.08271040767431259, 0.0021725951228290796, -0.16681934893131256, -0.031819552183151245, -0.3288743495941162, 0.0464513823390007, 0.17611919343471527, 0.000690086861141026, 7.961438677739352e-05, -0.00019473303109407425, -0.0969485193490982, -0.03324940800666809, -0.0008172128000296652, 0.22586534917354584, -0.2223370373249054, -0.05459794029593468, -9.828664769884199e-05, -0.14924103021621704, -0.03904952108860016, 0.2069503366947174, 0.07704979181289673, 0.1661059856414795, 0.14414143562316895, -0.23807625472545624, 0.10244176536798477, 0.09765428304672241, 0.08840622752904892, -0.024117084220051765, 0.0006691144080832601, 0.1786615550518036,
-
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-
-0.0005521097918972373, 0.017729170620441437, -0.1722581833600998, 0.0037039422895759344, 0.001567360362969339, -0.10055038332939148, 0.021108632907271385, 0.020772647112607956, 0.14595064520835876, -0.04253007844090462, 0.013751122169196606, 0.0076897949911653996, 0.04191797226667404, 0.01694018393754959, 0.002107905922457576, -0.06683442741632462, 0.020539015531539917, 0.02914385125041008, -7.801321044098586e-05, 0.00048368109855800867, -0.01766815409064293, -0.0005448150914162397, 0.0010524365352466702, -0.0007671643979847431, -0.00012459020945243537, 0.0008768694824539125, -0.0005135779501870275, -0.0037997858598828316, 0.00038613981450907886, 0.014108768664300442, 0.0006932157557457685, -0.0067222160287201405, -0.0209006667137146, 0.026551542803645134, -0.0011496779043227434, -0.0007507435511797667, 0.02834414131939411, 0.009201196022331715, 0.0057718404568731785, 0.02169930189847946, -0.014502635225653648, -3.491714596748352e-05, -0.0003578605828806758, -0.001178428647108376, 0.06057244539260864, 0.020316433161497116, -0.0011969138868153095, -0.04873412102460861, 0.023842258378863335, -0.023542333394289017, 0.0017061911057680845, 0.021966224536299706, 0.0003367953177075833, -0.1909828633069992, 0.06507214158773422, -0.02517489530146122, -0.04564562439918518, 0.030473219230771065, -0.035557761788368225, 0.0190313421189785, 0.025006592273712158, 0.0028738449327647686, 0.013087435625493526, -0.017678551375865936,
-
-0.5722816586494446, 0.44931724667549133, 0.033467985689640045, -0.05215294659137726, -0.1651076078414917, 0.09514902532100677, -0.2535097599029541, -0.31727728247642517, 0.020857004448771477, 0.01630846969783306, -0.09314350038766861, 0.1957118958234787, -0.39591383934020996, 0.26922011375427246, 0.3317633271217346, 0.11175347119569778, -0.2671031951904297, -0.056412164121866226, -0.0015118089504539967, 0.2937302589416504, 0.1793442815542221, -0.001025194302201271, 0.0010095476172864437, 0.0035850228741765022, 0.0006587953539565206, 0.000939257733989507, 0.0003379232657607645, 0.3479364216327667, -0.0004258739354554564, -0.0808158591389656, 0.00038307232898660004, -0.011362356133759022, -0.0033058011904358864, -0.08819703757762909, -0.32478445768356323, -0.0011537037789821625, -0.273912638425827, -0.11553899198770523, 0.17199908196926117, -0.0041303266771137714, 0.41343948245048523, 0.0003570480039343238, 0.0014987858012318611, 0.0013575225602835417, -0.55711829662323, -0.28808870911598206, -0.002448621904477477, 0.17940248548984528, -0.20062221586704254, 0.31715089082717896, 0.0008355412282980978, -0.07066480815410614, -0.13722951710224152, -0.10970398038625717, 0.05873332545161247, 0.24034948647022247, 0.182510644197464, 0.11015398055315018, 0.24339579045772552, -0.04150482639670372, 0.19960984587669373, -0.15185965597629547, -0.27342841029167175, 0.13767993450164795,
-
-0.22348885238170624, -0.008877726271748543, -0.171895369887352, -0.43331223726272583, 0.20232950150966644, 0.043170031160116196, -0.36004438996315, -0.006740920711308718, 0.18264558911323547, -0.11805032193660736, -0.07412461191415787, 0.032417088747024536, 0.051556725054979324, 0.08561589568853378, 0.4091699719429016, -0.0786430686712265, -0.22887086868286133, -0.2439272403717041, 0.00014124371227808297, 0.6468839049339294, -0.036077044904232025, -0.0014531002379953861, -0.0011161002330482006, 0.003305896883830428, 0.0017938324017450213, -3.7506528315134346e-05, -0.0016759017016738653, 0.40134409070014954, -0.0007333348621614277, -0.2809791564941406, -0.001019181334413588, 0.019602011889219284, 0.09314858913421631, -0.5306268334388733, 0.17580009996891022, -1.5525150956818834e-05, -0.2091640830039978, -0.6634456515312195, -0.14848995208740234, -0.06595541536808014, -0.034880805760622025, -1.1966582178501994e-06, 0.00036120228469371796, -0.0012568037491291761, -0.10609765350818634, -0.5816946625709534, -0.0006648825947195292, 0.4456590414047241, -0.512170672416687, 0.24637466669082642, 0.0010917421896010637, -0.23795755207538605, -0.2328575998544693, -0.07656370103359222, 0.33030301332473755, 0.2731899917125702, 0.09424741566181183, -0.1698189079761505, 0.01702292636036873, -0.10659436136484146, 0.11089695990085602, -0.08941251039505005, -0.35293179750442505, 0.06545879691839218
-};
-
-/// Second convolution biases
-static const double conv2_biases[] = {
-0.12326373159885406,
-0.13270756602287292,
-0.07082673907279968,
-0.051456157118082047,
-0.05844561755657196,
-0.1315319687128067,
-0.08097290247678757,
-0.10153213143348694,
-0.055915363132953644,
-0.052281659096479416,
--0.11212895810604095,
-0.07462140917778015,
--0.10300768911838531,
-0.108175128698349,
-0.15686865150928497,
-0.18225829303264618,
-0.06780990958213806,
--0.027867194265127182,
-0.10957542806863785,
-0.03425288572907448,
-0.05988423153758049,
--0.04818560183048248,
-0.07478125393390656,
--0.07338137924671173,
--0.022100606933236122,
--0.04947621747851372,
-0.00016185229469556361,
-0.16787314414978027,
--0.08640440553426743,
-0.060469429939985275,
--0.17337509989738464,
-0.26549988985061646
-};
-
-/// Third convolution kernel
-static const double conv3_kernel[] = {
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--0.00812589656561613, 0.023091308772563934, 0.013341490179300308, -0.0017570563359186053, 0.011543834581971169, 0.004988478496670723, 0.02247282676398754, 0.03653952479362488, 0.007683734409511089, 0.0037880358286201954, 0.007956952787935734, 0.015365968458354473, 0.012251682579517365, -0.011300078593194485, 0.018807940185070038, -0.0016539369244128466, 0.01070421189069748, 0.011612690053880215, 0.03027413971722126, 0.004591582342982292, -0.0243303794413805, -0.014095880091190338, 0.01868494786322117, 0.008858193643391132, -0.04804064705967903, 0.016877762973308563, -5.198307917453349e-06, 0.007284262217581272, 0.005965469870716333, 0.005185986869037151, 0.0015474684769287705, 0.0014243163168430328, 0.014486664906144142, -0.0007930672145448625, -0.014664226211607456, -0.016457712277770042, -0.017403796315193176, 0.012685011141002178, -0.0038839769549667835, -2.389050496276468e-05, -0.0160866379737854, -0.01904400624334812, 0.004156769253313541, -0.008070499636232853, -0.0033578418660908937, -0.00516103021800518, 0.014172150753438473, 0.00791727751493454, -0.010331041179597378, -0.008183060213923454, -0.0030316549818962812, -0.018925121054053307, -0.025037286803126335, -0.018173744902014732, -0.008901157416403294, -0.006475025787949562, -0.045409832149744034, 0.007166015915572643, -7.585635557916248e-06, 0.0012800301192328334, 0.0006912891403771937, 0.0059029520489275455, -0.004367201589047909, -0.024956075474619865, 0.022586409002542496, 0.03446779027581215, -0.012960361316800117, -0.0014372625155374408, -0.014426053501665592, 0.01776641421020031, -0.00538691645488143, -0.005508242174983025, -0.008251170627772808, -0.006693737115710974, -0.00424883421510458, -0.0030098704155534506, 0.0014789323322474957, -8.246497600339353e-05, -0.012845523655414581, 0.025194581598043442, 0.0025184480473399162, -0.00496160052716732, -0.010554589331150055, -0.010357110761106014, 0.005486670881509781, -0.021662171930074692, -0.011405641213059425, -0.0068052071146667, -0.004323462024331093, -0.007439297158271074, -7.72375915403245e-06, -0.021758737042546272, 0.008226223289966583, 0.006653657183051109, -0.008580118417739868, 0.03419283404946327, -0.0004065808025188744, 0.002096658106893301, -0.007829351350665092, 0.01040695235133171, 0.004781882278621197, 0.005034750793129206, -0.016704533249139786, -0.016410555690526962, 0.0011981577845290303, 0.009445485658943653, -0.005858719814568758, -0.007212047465145588, -0.02453439123928547, -0.0071554724127054214, -0.014008383266627789, 0.005001842509955168, 0.00020401524670887738, -0.008169618435204029, -0.021851185709238052, 0.008030191995203495, -0.0050564780831336975, -0.02414780668914318, -0.013633708469569683, 0.006448823027312756, -0.029981538653373718, -0.03735398128628731, -6.921254680491984e-06, 0.03399209678173065, -0.004451010841876268, 0.004246181342750788, -0.032517194747924805, -0.01074709091335535, -0.004061675630509853, 0.0025288749020546675, 0.012356824241578579, 0.00828587356954813, 0.02730046585202217, -0.007290054112672806, 0.0016192658804357052, 0.00967408251017332, 0.014147035777568817, 0.01511610671877861, 0.01129476260393858, 0.005221985280513763, 0.013473305851221085, -0.007084429729729891, 0.01748768240213394, -0.018865350633859634, 0.00915855448693037, -0.011141966097056866, 0.005098120309412479, 0.012889760546386242, -0.019689016044139862, 0.0028594080358743668, 0.0053698960691690445, -0.004294142127037048, -0.014502201229333878, 0.014149459078907967, -4.726254246634198e-06, 0.00383391254581511, 0.01293114572763443, 0.004694880452007055, 0.013098621740937233, -0.01542270090430975
-};
-
-/// Third convolution biases
-static const double conv3_biases[] = {
-0.05037664
-};
-#endif
@@ -23,6 +23,7 @@ HEADERS = adler32.h \
des.h \
dict.h \
display.h \
+ dnn_interface.h \
downmix_info.h \
encryption_info.h \
error.h \
@@ -107,6 +108,8 @@ OBJS = adler32.o \
des.o \
dict.o \
display.o \
+ dnn_interface.o \
+ dnn_backend_native.o \
downmix_info.o \
encryption_info.o \
error.o \
new file mode 100644
@@ -0,0 +1,382 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * 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 "dnn_srcnn.h"
+#include "libavformat/avio.h"
+
+typedef enum {INPUT, CONV} LayerType;
+
+typedef struct Layer{
+ LayerType type;
+ float* output;
+ void* params;
+} Layer;
+
+typedef struct ConvolutionalParams{
+ int32_t input_num, output_num, kernel_size;
+ float* kernel;
+ float* biases;
+} ConvolutionalParams;
+
+typedef struct InputParams{
+ int height, width, channels;
+} InputParams;
+
+// Represents simple feed-forward convolutional network.
+typedef struct ConvolutionalNetwork{
+ Layer* layers;
+ int32_t layers_num;
+} ConvolutionalNetwork;
+
+static DNNReturnType set_input_output_native(void* model, const DNNData* input, const DNNData* output)
+{
+ ConvolutionalNetwork* network = (ConvolutionalNetwork*)model;
+ InputParams* input_params;
+ ConvolutionalParams* conv_params;
+ int cur_width, cur_height, cur_channels;
+ int32_t layer;
+
+ if (network->layers_num <= 0 || network->layers[0].type != INPUT){
+ return DNN_ERROR;
+ }
+ else{
+ network->layers[0].output = input->data;
+ input_params = (InputParams*)network->layers[0].params;
+ input_params->width = cur_width = input->width;
+ input_params->height = cur_height = input->height;
+ input_params->channels = cur_channels = input->channels;
+ }
+
+ for (layer = 1; layer < network->layers_num; ++layer){
+ switch (network->layers[layer].type){
+ case CONV:
+ conv_params = (ConvolutionalParams*)network->layers[layer].params;
+ if (conv_params->input_num != cur_channels){
+ return DNN_ERROR;
+ }
+ cur_channels = conv_params->output_num;
+ if (layer < network->layers_num - 1){
+ if (!network->layers[layer].output){
+ av_freep(&network->layers[layer].output);
+ }
+ network->layers[layer].output = av_malloc(cur_height * cur_width * cur_channels * sizeof(float));
+ if (!network->layers[layer].output){
+ return DNN_ERROR;
+ }
+ }
+ else{
+ network->layers[layer].output = output->data;
+ if (output->width != cur_width || output->height != cur_height || output->channels != cur_channels){
+ return DNN_ERROR;
+ }
+ }
+ break;
+ default:
+ return DNN_ERROR;
+ }
+ }
+
+ return DNN_SUCCESS;
+}
+
+// Loads model and its parameters that are stored in a binary file with following structure:
+// layers_num,conv_input_num,conv_output_num,conv_kernel_size,conv_kernel,conv_biases,conv_input_num...
+DNNModel* ff_dnn_load_model_native(const char* model_filename)
+{
+ DNNModel* model = NULL;
+ ConvolutionalNetwork* network = NULL;
+ AVIOContext* model_file_context;
+ int file_size, dnn_size, kernel_size, i;
+ int32_t layer;
+ ConvolutionalParams* conv_params;
+
+ model = av_malloc(sizeof(DNNModel));
+ if (!model){
+ return NULL;
+ }
+
+ if (avio_open(&model_file_context, model_filename, AVIO_FLAG_READ) < 0){
+ av_freep(&model);
+ return NULL;
+ }
+ file_size = avio_size(model_file_context);
+
+ network = av_malloc(sizeof(ConvolutionalNetwork));
+ if (!network){
+ avio_closep(&model_file_context);
+ av_freep(&model);
+ return NULL;
+ }
+ model->model = (void*)network;
+
+ network->layers_num = 1 + (int32_t)avio_rl32(model_file_context);
+ dnn_size = 4;
+
+ network->layers = av_malloc(network->layers_num * sizeof(Layer));
+ if (!network->layers){
+ av_freep(&network);
+ avio_closep(&model_file_context);
+ av_freep(&model);
+ return NULL;
+ }
+
+ for (layer = 0; layer < network->layers_num; ++layer){
+ network->layers[layer].output = NULL;
+ network->layers[layer].params = NULL;
+ }
+ network->layers[0].type = INPUT;
+ network->layers[0].params = av_malloc(sizeof(InputParams));
+ if (!network->layers[0].params){
+ avio_closep(&model_file_context);
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+
+ for (layer = 1; layer < network->layers_num; ++layer){
+ conv_params = av_malloc(sizeof(ConvolutionalParams));
+ if (!conv_params){
+ avio_closep(&model_file_context);
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+ conv_params->input_num = (int32_t)avio_rl32(model_file_context);
+ conv_params->output_num = (int32_t)avio_rl32(model_file_context);
+ conv_params->kernel_size = (int32_t)avio_rl32(model_file_context);
+ kernel_size = conv_params->input_num * conv_params->output_num *
+ conv_params->kernel_size * conv_params->kernel_size;
+ dnn_size += 12 + (kernel_size + conv_params->output_num << 2);
+ if (dnn_size > file_size || conv_params->input_num <= 0 ||
+ conv_params->output_num <= 0 || conv_params->kernel_size <= 0){
+ avio_closep(&model_file_context);
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+ conv_params->kernel = av_malloc(kernel_size * sizeof(float));
+ conv_params->biases = av_malloc(conv_params->output_num * sizeof(float));
+ if (!conv_params->kernel || !conv_params->biases){
+ avio_closep(&model_file_context);
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+ for (i = 0; i < kernel_size; ++i){
+ conv_params->kernel[i] = av_int2float(avio_rl32(model_file_context));
+ }
+ for (i = 0; i < conv_params->output_num; ++i){
+ conv_params->biases[i] = av_int2float(avio_rl32(model_file_context));
+ }
+ network->layers[layer].type = CONV;
+ network->layers[layer].params = conv_params;
+ }
+
+ avio_closep(&model_file_context);
+
+ if (dnn_size != file_size){
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+
+ model->set_input_output = &set_input_output_native;
+
+ return model;
+}
+
+static int set_up_conv_layer(Layer* layer, const float* kernel, const float* biases, int32_t input_num, int32_t output_num, int32_t size)
+{
+ ConvolutionalParams* conv_params;
+ int kernel_size;
+
+ conv_params = av_malloc(sizeof(ConvolutionalParams));
+ if (!conv_params){
+ return DNN_ERROR;
+ }
+ conv_params->input_num = input_num;
+ conv_params->output_num = output_num;
+ conv_params->kernel_size = size;
+ kernel_size = input_num * output_num * size * size;
+ conv_params->kernel = av_malloc(kernel_size * sizeof(float));
+ conv_params->biases = av_malloc(conv_params->output_num * sizeof(float));
+ if (!conv_params->kernel || !conv_params->biases){
+ av_freep(&conv_params->kernel);
+ av_freep(&conv_params->biases);
+ av_freep(&conv_params);
+ return DNN_ERROR;
+ }
+ memcpy(conv_params->kernel, kernel, kernel_size * sizeof(float));
+ memcpy(conv_params->biases, biases, output_num * sizeof(float));
+ layer->type = CONV;
+ layer->params = conv_params;
+
+ return DNN_SUCCESS;
+}
+
+DNNModel* ff_dnn_load_default_model_native(DNNDefaultModel model_type)
+{
+ DNNModel* model = NULL;
+ ConvolutionalNetwork* network = NULL;
+ int32_t layer;
+
+ model = av_malloc(sizeof(DNNModel));
+ if (!model){
+ return NULL;
+ }
+
+ network = av_malloc(sizeof(ConvolutionalNetwork));
+ if (!network){
+ av_freep(&model);
+ return NULL;
+ }
+ model->model = (void*)network;
+
+ switch (model_type){
+ case DNN_SRCNN:
+ network->layers_num = 4;
+
+ network->layers = av_malloc(network->layers_num * sizeof(Layer));
+ if (!network->layers){
+ av_freep(&network);
+ av_freep(&model);
+ return NULL;
+ }
+
+ for (layer = 0; layer < network->layers_num; ++layer){
+ network->layers[layer].output = NULL;
+ network->layers[layer].params = NULL;
+ }
+ network->layers[0].type = INPUT;
+ network->layers[0].params = av_malloc(sizeof(InputParams));
+ if (!network->layers[0].params){
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+
+ if (set_up_conv_layer(network->layers + 1, conv1_kernel, conv1_biases, 1, 64, 9) != DNN_SUCCESS ||
+ set_up_conv_layer(network->layers + 2, conv2_kernel, conv2_biases, 64, 32, 1) != DNN_SUCCESS ||
+ set_up_conv_layer(network->layers + 3, conv3_kernel, conv3_biases, 32, 1, 5) != DNN_SUCCESS){
+ ff_dnn_free_model_native(&model);
+ return NULL;
+ }
+
+ model->set_input_output = &set_input_output_native;
+
+ return model;
+ default:
+ av_freep(&network);
+ av_freep(&model);
+ return NULL;
+ }
+}
+
+#define CLAMP_TO_EDGE(x, w) ((x) < 0 ? 0 : ((x) >= (w) ? (w - 1) : (x)))
+
+static void convolve(const float* input, float* output, const ConvolutionalParams* conv_params, int32_t width, int32_t height)
+{
+ int y, x, n_filter, ch, kernel_y, kernel_x;
+ int radius = conv_params->kernel_size >> 1;
+ int src_linesize = width * conv_params->input_num;
+ int filter_linesize = conv_params->kernel_size * conv_params->input_num;
+ int filter_size = conv_params->kernel_size * filter_linesize;
+
+ for (y = 0; y < height; ++y){
+ for (x = 0; x < width; ++x){
+ for (n_filter = 0; n_filter < conv_params->output_num; ++n_filter){
+ output[n_filter] = conv_params->biases[n_filter];
+ for (ch = 0; ch < conv_params->input_num; ++ch){
+ for (kernel_y = 0; kernel_y < conv_params->kernel_size; ++kernel_y){
+ for (kernel_x = 0; kernel_x < conv_params->kernel_size; ++kernel_x){
+ output[n_filter] += input[CLAMP_TO_EDGE(y + kernel_y - radius, height) * src_linesize +
+ CLAMP_TO_EDGE(x + kernel_x - radius, width) * conv_params->input_num + ch] *
+ conv_params->kernel[n_filter * filter_size + kernel_y * filter_linesize +
+ kernel_x * conv_params->input_num + ch];
+ }
+ }
+ }
+ output[n_filter] = FFMAX(output[n_filter], 0.0);
+ }
+ output += conv_params->output_num;
+ }
+ }
+}
+
+DNNReturnType ff_dnn_execute_model_native(const DNNModel* model)
+{
+ ConvolutionalNetwork* network = (ConvolutionalNetwork*)model->model;
+ InputParams* input_params;
+ int cur_width, cur_height;
+ int32_t layer;
+
+ if (network->layers_num <= 0 || network->layers[0].type != INPUT || !network->layers[0].output){
+ return DNN_ERROR;
+ }
+ else{
+ input_params = (InputParams*)network->layers[0].params;
+ cur_width = input_params->width;
+ cur_height = input_params->height;
+ }
+
+ for (layer = 1; layer < network->layers_num; ++layer){
+ if (!network->layers[layer].output){
+ return DNN_ERROR;
+ }
+ switch (network->layers[layer].type){
+ case CONV:
+ convolve(network->layers[layer - 1].output, network->layers[layer].output, (ConvolutionalParams*)network->layers[layer].params, cur_width, cur_height);
+ break;
+ case INPUT:
+ return DNN_ERROR;
+ }
+ }
+
+ return DNN_SUCCESS;
+}
+
+void ff_dnn_free_model_native(DNNModel** model)
+{
+ ConvolutionalNetwork* network;
+ ConvolutionalParams* conv_params;
+ int32_t layer;
+
+ if (*model)
+ {
+ network = (ConvolutionalNetwork*)(*model)->model;
+ for (layer = 0; layer < network->layers_num; ++layer){
+ switch (network->layers[layer].type){
+ case CONV:
+ if (layer < network->layers_num - 1){
+ av_freep(&network->layers[layer].output);
+ }
+ conv_params = (ConvolutionalParams*)network->layers[layer].params;
+ av_freep(&conv_params->kernel);
+ av_freep(&conv_params->biases);
+ av_freep(&conv_params);
+ break;
+ case INPUT:
+ av_freep(&network->layers[layer].params);
+ }
+ }
+ av_freep(network);
+ av_freep(model);
+ }
+}
new file mode 100644
@@ -0,0 +1,40 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * 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 inference functions interface for native backend.
+ */
+
+
+#ifndef AVUTIL_DNN_BACKEND_NATIVE_H
+#define AVUTIL_DNN_BACKEND_NATIVE_H
+
+#include "dnn_interface.h"
+
+DNNModel* ff_dnn_load_model_native(const char* model_filename);
+
+DNNModel* ff_dnn_load_default_model_native(DNNDefaultModel model_type);
+
+DNNReturnType ff_dnn_execute_model_native(const DNNModel* model);
+
+void ff_dnn_free_model_native(DNNModel** model);
+
+#endif
new file mode 100644
@@ -0,0 +1,48 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * 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
+ * Implements DNN module initialization with specified backend.
+ */
+
+#include "dnn_interface.h"
+#include "dnn_backend_native.h"
+#include "libavutil/mem.h"
+
+DNNModule* ff_get_dnn_module(DNNBackendType backend_type)
+{
+ DNNModule* dnn_module;
+
+ dnn_module = av_malloc(sizeof(DNNModule));
+ if(!dnn_module){
+ return NULL;
+ }
+
+ switch(backend_type){
+ case DNN_NATIVE:
+ dnn_module->load_model = &ff_dnn_load_model_native;
+ dnn_module->load_default_model = &ff_dnn_load_default_model_native;
+ dnn_module->execute_model = &ff_dnn_execute_model_native;
+ dnn_module->free_model = &ff_dnn_free_model_native;
+ }
+
+ return dnn_module;
+}
new file mode 100644
@@ -0,0 +1,64 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * 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 inference engine interface.
+ */
+
+#ifndef AVUTIL_DNN_INTERFACE_H
+#define AVUTIL_DNN_INTERFACE_H
+
+typedef enum {DNN_SUCCESS, DNN_ERROR} DNNReturnType;
+
+typedef enum {DNN_NATIVE} DNNBackendType;
+
+typedef enum {DNN_SRCNN} DNNDefaultModel;
+
+typedef struct DNNData{
+ float* data;
+ int width, height, channels;
+} DNNData;
+
+
+typedef struct DNNModel{
+ // Stores model that can be different for different backends.
+ void* model;
+ // Sets model input and output, while allocating additional memory for intermediate calculations.
+ // Should be called at least once before model execution.
+ DNNReturnType (*set_input_output)(void* model, const DNNData* input, const DNNData* output);
+} DNNModel;
+
+// Stores pointers to functions for loading, executing, freeing DNN models for one of the backends.
+typedef struct DNNModule{
+ // Loads model and parameters from given file. Returns NULL if it is not possible.
+ DNNModel* (*load_model)(const char* model_filename);
+ // Loads one of the default models
+ DNNModel* (*load_default_model)(DNNDefaultModel model_type);
+ // Executes model with specified input and output. Returns DNN_ERROR otherwise.
+ DNNReturnType (*execute_model)(const DNNModel* model);
+ // Frees memory allocated for model.
+ void (*free_model)(DNNModel** model);
+} DNNModule;
+
+// Initializes DNNModule depending on chosen backend.
+DNNModule* ff_get_dnn_module(DNNBackendType backend_type);
+
+#endif
new file mode 100644
@@ -0,0 +1,854 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * 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
+ * Default cnn weights for x2 upsampling with srcnn filter.
+ */
+
+#ifndef AVUTIL_DNN_SRCNN_H
+#define AVUTIL_DNN_SRCNN_H
+
+static const float conv1_kernel[] = {
+-0.08866338f, 0.055409566f, 0.037196506f, -0.11961404f, -0.12341991f, 0.29963422f, -0.0911817f, -0.00013613555f, -0.049023595f,
+0.038421184f, -0.077267796f, 0.027273094f, 0.4576209f, 0.023581645f, -0.20363852f, -0.07738442f, 0.07288404f, 0.06679897f,
+-0.07315085f, 0.2665306f, 0.07836371f, -0.28985283f, -0.5069129f, 0.04466513f, -0.06246859f, -0.024424827f, -0.02907293f,
+-0.16884787f, 0.20686236f, -0.25367007f, -0.384997f, -0.12601902f, 0.72578824f, 0.09588378f, -0.044872783f, -0.011251596f,
+-0.029558526f, 0.2211706f, -0.38453165f, -0.053509537f, 0.109559156f, 0.37257388f, -0.28968045f, -0.10883619f, 0.1962879f,
+0.09746793f, -0.005647097f, -0.13035884f, 0.6254252f, 0.19104235f, -0.011692332f, -0.2706789f, -0.030754156f, 0.029875506f,
+0.01680875f, -0.18317908f, -0.1601607f, 0.35982913f, -0.18890111f, -0.2234334f, -0.11111768f, 0.32211426f, -0.18514074f,
+-0.066470124f, 0.18005541f, -0.035659794f, -0.25352174f, -0.1837048f, 0.28395423f, 0.0030237234f, 0.24072711f, -0.14355472f,
+0.047418743f, -0.032212373f, -0.08801338f, 0.2959175f, 0.04108741f, -0.10354422f, -0.11681117f, -0.010267493f, 0.023703521f,
+
+-0.043954458f, 0.095338844f, 0.122337975f, -0.05211482f, 0.068812296f, 0.05764868f, 0.086866505f, -0.12001238f, 0.023536388f,
+-0.022270674f, -0.06377912f, 0.010644146f, -0.27824146f, -0.23719865f, -0.21418367f, -0.096650206f, 0.10458535f, 0.06599419f,
+-0.031174282f, -0.034653533f, 0.022143817f, -0.24322355f, -0.089235984f, -0.027248107f, -0.09314897f, -0.037409738f, 0.07819665f,
+0.12521376f, 0.11189836f, 0.34981978f, 0.24303557f, 0.21350804f, 0.37120733f, 0.12192775f, -0.15492134f, 0.018840319f,
+-0.08351074f, -0.3054998f, -0.114621654f, -0.11833595f, -0.3502763f, -0.0077491426f, -0.051849455f, -0.14423956f, -0.040475942f,
+0.18357797f, 0.16708122f, 0.07486253f, 0.17892863f, 0.12331069f, 0.16825254f, -0.040668704f, 0.12498869f, 0.12445469f,
+-0.08529795f, -0.23087382f, -0.242645f, -0.0033642692f, -0.019013511f, 0.007406716f, -0.0976248f, 0.09727376f, -0.1430845f,
+0.20924512f, 0.04731563f, 0.17839451f, 0.2014277f, -0.21384318f, -0.16858183f, 0.07769212f, 0.114782944f, 0.0022495266f,
+-0.095246606f, -0.11904185f, -0.119040586f, 0.119354986f, 0.040786922f, -0.07873279f, 0.19328512f, -0.06008545f, -0.03619225f,
+
+-0.03508937f, -0.021296037f, 0.04467616f, 0.035148017f, 0.047732554f, -0.036008984f, -0.09819481f, -0.07464613f, 0.16331302f,
+0.05766148f, -0.060683597f, 0.023710888f, 0.040778793f, 0.01952822f, -0.047095288f, -0.0026468062f, 0.013081373f, -0.048433363f,
+-0.05547124f, -0.007511544f, -0.0018498366f, 0.0063248295f, 0.08334494f, -0.03534594f, -0.058733407f, -0.11714734f, -0.0496851f,
+-0.010657697f, 0.08840381f, 0.068287104f, 0.020970112f, 0.2620501f, 0.11938151f, 0.042141f, -0.064056866f, -0.04790669f,
+0.054825947f, 0.07402177f, 0.21512434f, 0.25780582f, 0.4271634f, 0.18216214f, 0.12531154f, 0.103901714f, -0.0104828905f,
+-0.07587306f, -0.01289812f, 0.100657016f, 0.073730744f, 0.1594899f, -0.08611099f, 0.0066837906f, 0.107562296f, -0.10216449f,
+-0.121009395f, 0.00951384f, 0.04604567f, 0.067058936f, 0.21903297f, 0.026905395f, 0.0053238617f, 0.00067650457f, -0.042836767f,
+-0.025259271f, -0.009707702f, -0.0009789661f, 0.043257646f, 0.088092126f, 0.018156063f, -0.012795507f, -0.10799489f, 0.044633016f,
+0.13564141f, 0.033341955f, -0.12862708f, -0.13122201f, -0.009230303f, -0.019398134f, -0.005852208f, -0.05510853f, -0.039392535f,
+
+0.036042538f, -0.017754223f, 0.012287495f, 0.08819248f, -0.04256459f, -0.08412625f, 0.003404226f, 0.095139764f, -0.01955163f,
+-0.09674753f, 0.18024282f, -0.08090512f, -0.24444069f, 0.006856921f, 0.1304172f, 0.025669439f, -0.23943077f, 0.044755235f,
+-0.016099237f, -0.18014333f, -0.119650446f, 0.15631895f, 0.23565492f, -0.016446924f, 0.088609904f, 0.030303521f, 0.037084505f,
+0.20704922f, -0.30848193f, 0.2985248f, 0.51717925f, 0.008160744f, -0.3112909f, -0.12307852f, 0.23214605f, -0.034601245f,
+-0.053407326f, 0.10225691f, 0.21641655f, -0.006494026f, -0.2507584f, -0.20448849f, 0.050536312f, 0.12135548f, -0.24142836f,
+-0.28441224f, 0.33926067f, -0.18576817f, -0.49420735f, -0.097031295f, 0.0031086628f, 0.15142952f, -0.08352979f, 0.11525617f,
+0.1575496f, 0.11142445f, 0.0034580992f, -0.17606017f, 0.16817984f, 0.09105344f, 0.039175604f, -0.09479037f, 0.056350756f,
+0.02523156f, -0.2455007f, 0.063366f, 0.16318576f, 0.21757606f, -0.10586289f, -0.08236702f, 0.06969914f, -0.024705412f,
+-0.053974763f, 0.17869812f, -0.027807202f, -0.19675265f, -0.1037345f, 0.008513543f, 0.13250032f, -0.045926444f, -0.0030838586f,
+
+-0.040477958f, 0.049372006f, -0.1366689f, 0.13786657f, -0.13875751f, 0.29655218f, 0.17230958f, -0.13066995f, -0.048650246f,
+0.04459606f, -0.03141404f, 0.031236706f, 0.14699893f, -0.4883143f, -0.44782618f, -0.32052815f, 0.22293234f, 0.11625721f,
+0.030552648f, -0.13195507f, -0.0958492f, 0.070505545f, -0.14855938f, 0.10478757f, -0.16068053f, -0.12290131f, -0.13379076f,
+0.024233105f, 0.23596089f, -0.021006849f, 0.1890502f, 0.5085715f, 0.63729393f, 0.21577123f, 0.011278441f, 0.18822116f,
+-0.1545927f, -0.040722325f, -0.103782505f, -0.20680243f, -0.0048381016f, -0.08054019f, -0.20550838f, -0.16877042f, -0.13454553f,
+0.24716504f, -0.055626824f, 0.26783165f, -0.060780562f, -0.30375552f, -0.16147833f, 0.13623716f, 0.2936753f, 0.047969237f,
+-0.030661728f, -0.3058367f, -0.08003057f, 0.10655708f, -0.018742286f, 0.03587923f, -0.025629207f, -0.11310985f, -0.14455995f,
+0.040501814f, 0.281208f, -0.05849621f, 0.09595922f, -0.004120929f, 0.14832601f, 0.05187895f, -0.02497972f, 0.12018023f,
+-0.059710164f, -0.027000621f, -0.15200919f, 0.17205532f, -0.10738909f, -0.042039443f, -0.051565733f, 0.04735837f, -0.020336714f,
+
+0.07923563f, 0.019853497f, 0.048436765f, -0.002480322f, -0.030445646f, 0.043048497f, -0.020503692f, -0.066097535f, 0.120975174f,
+0.007324902f, -0.12224785f, -0.05323218f, -0.057645664f, -0.02026738f, -0.024209453f, -0.0054551987f, 0.009971959f, 0.023965936f,
+-0.00814846f, -0.005118968f, 0.021225877f, -0.007966008f, 0.08807613f, 0.014100072f, -0.025872009f, -0.077255875f, 0.03290955f,
+0.034313247f, 0.09776207f, 0.13437991f, 0.05204649f, 0.23554459f, 0.18288168f, 0.09693129f, -0.050400723f, -0.04832229f,
+-0.09905002f, -0.0074814707f, 0.19846895f, 0.14758876f, 0.23091012f, 0.13733757f, 0.13091283f, 0.092882596f, -0.05274213f,
+-0.17166649f, -0.04306709f, 0.14391254f, 0.038292434f, 0.087384045f, -0.029237974f, 0.063960664f, 0.12762053f, -0.028018195f,
+-0.12651931f, 0.024751775f, 0.105892144f, 0.09887335f, 0.24562614f, 0.12530468f, 0.061612073f, -0.02412554f, 0.007247811f,
+-0.047855668f, 0.013432898f, 0.03482811f, 0.077229805f, 0.10088468f, 0.044684406f, -0.020415774f, -0.15163109f, -0.003470435f,
+0.122444995f, 0.03920309f, -0.06930789f, -0.015424877f, -0.016137347f, -0.045813974f, 0.013485563f, 0.024088666f, 0.016876703f,
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+
+};
+
+static const float conv1_biases[] = {
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+6.6839266e-06f,
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+-0.0013730666f,
+0.03035182f,
+0.0f,
+0.003285622f,
+0.0055278814f,
+0.020766519f,
+-0.008490622f,
+0.026332268f,
+-0.046789873f,
+0.010329567f,
+-0.02364932f,
+0.027851572f,
+0.054407462f,
+-0.08068252f,
+-0.009446503f,
+-0.04663234f
+};
+
+static const float conv2_kernel[] = {
+-0.24004751f, 0.1037138f, 0.11173403f, 0.04352092f, -0.23728481f, 0.12153747f, -0.23676059f, -0.28548065f, -0.612738f, -0.12218937f, -0.06005159f, 0.1850652f, 0.16014674f, 0.13922939f, 0.21359426f, 0.10787945f, -0.26999104f, -0.14241326f, -0.0013871012f, -0.004951588f, 0.34021696f, 0.00055816956f, 4.7351106e-05f, 0.0037513396f, 0.0011569702f, 0.0016541762f, -0.0011876022f, 0.049887992f, -7.20162e-05f, -0.17735492f, 0.0011244657f, -0.22381487f, 0.0035836962f, -0.32106942f, -0.16167264f, -0.00079228356f, 0.05056063f, 0.21074672f, 0.07716238f, -0.33156216f, 0.06265881f, 0.00025428506f, -0.0012989661f, 0.00044869471f, -0.41594547f, -0.019950004f, 0.0002566903f, 0.17913155f, -0.59505045f, 0.32598367f, 0.0013792524f, -0.0893171f, -0.13066787f, 0.21108511f, -0.05854454f, -0.11937838f, 0.08559372f, -0.11413643f, 0.28384048f, -0.011619674f, 0.3210233f, -0.20085232f, -0.3413438f, -0.029155191f,
+
+-0.15286806f, -0.4510034f, -0.07077684f, 0.1440866f, 0.05953074f, -0.036571715f, 0.38701403f, -0.12762508f, 0.059950776f, 0.005409028f, 0.16427578f, -0.042501528f, 0.03296236f, -0.19972457f, -0.2558594f, -0.054797124f, -0.13352458f, 0.05193127f, -0.0005906696f, 0.14123854f, -0.0659517f, 0.00025938704f, 0.0004935732f, 0.0018757024f, -0.00041573317f, 0.000612862f, -0.00082537025f, 0.008750236f, 0.00031561358f, -0.031592708f, -0.0011055622f, 0.53974074f, 0.16837794f, 0.10016078f, -0.04458074f, -0.00082082127f, 0.14558496f, 0.053703558f, 0.39986718f, 0.36513358f, -6.220485e-05f, -0.0015507897f, 0.00019759317f, 0.0014775719f, 0.1719912f, 0.20428549f, 0.00071692816f, -0.1558909f, 0.13173038f, 0.04302276f, 0.00053589704f, -0.14488573f, -0.056273844f, 0.040606596f, 0.123271205f, -0.068726316f, 0.11684817f, 0.20592213f, -0.07642778f, -0.105910346f, -0.2585832f, -0.23417398f, 0.12040833f, -0.09154299f,
+
+0.17292786f, 0.12093151f, 0.121731065f, -0.17765464f, -0.0384256f, 0.13790965f, -0.018014584f, -0.0035332667f, 0.05237539f, -0.0137136085f, -0.023778876f, 0.08754374f, 0.009544277f, 0.002218335f, 0.0054768333f, 0.1433599f, -0.3052151f, -0.027671313f, 0.0002961017f, -0.090877056f, 0.080019295f, 0.0002891663f, 8.4476655e-05f, 0.003273378f, -0.0009773651f, 0.0009694154f, 0.0023891174f, 0.15905638f, 0.0006923403f, -0.23975392f, 0.00035524007f, -0.1527745f, 0.09689001f, -0.13403186f, -0.108304426f, -0.0011496501f, -0.07912725f, -0.045485526f, 0.07143749f, -0.119538695f, 0.06519464f, 0.00047708154f, -0.0012068728f, 0.00023571185f, -0.021851776f, -0.109725535f, -0.0004428154f, -0.061998375f, -0.021858238f, 0.13159609f, 0.0011464811f, -0.12141252f, -0.06273758f, 0.25536647f, 0.10020979f, 0.13120368f, 0.16516227f, -0.14927655f, 0.14413974f, 0.039363794f, 0.19443943f, -0.016147649f, -0.08761862f, 0.08571985f,
+
+-0.034732215f, 0.08880915f, 0.11532351f, -0.25091994f, -0.18177348f, 0.111709945f, -0.06447608f, -0.04730312f, -0.13159128f, 0.01896033f, -0.29692683f, 0.3151368f, 0.016690407f, 0.08558145f, 0.016950725f, 0.13607958f, -0.008597756f, -0.15839215f, -0.00063565f, 0.1460453f, 0.0293913f, -0.002123718f, -0.0021662426f, 0.0011421579f, 0.0003198187f, -0.0003188809f, -0.0013892676f, 0.4037178f, 0.0010367054f, -0.08923333f, 0.0017262235f, 0.049378145f, 0.03052855f, -0.109949686f, 0.041772034f, -0.00035096507f, -0.091725476f, -0.11212402f, 0.018248942f, -0.103211425f, 0.036560368f, -0.00085344445f, 0.0005108113f, 0.001955348f, -0.17280978f, -0.15745719f, 0.0016406632f, 0.102957435f, -0.056333065f, 0.12174493f, -0.00029968395f, -0.046295736f, -0.05203623f, 0.17915867f, 0.17138906f, 0.20149875f, 0.14662422f, -0.064990275f, 0.086431846f, 0.02657508f, -0.26568517f, -0.10079118f, -0.20195039f, 0.072891355f,
+
+0.20596844f, 0.14842734f, 0.11689981f, -0.29243934f, 0.020928182f, 0.14047745f, -0.032774657f, 0.013994991f, 0.04893072f, -0.08560179f, 0.07281562f, 0.069943145f, -0.006538145f, 0.08474164f, 0.013837414f, 0.104377925f, -0.32318544f, -0.03346193f, -0.0006234076f, -0.25232646f, 0.08134998f, -0.0012573038f, -0.00025874845f, 0.0021640486f, 0.0007048257f, 0.00086261076f, -0.00049946277f, 0.18027796f, 0.0005355332f, -0.38501582f, -0.0006607559f, -0.15524353f, 0.07703849f, -0.19909449f, -0.040597178f, 0.00019839265f, -0.089541435f, -0.17451768f, 0.193429f, -0.039949242f, -0.053514555f, 0.0010188281f, 0.0012863715f, -4.6992354e-05f, 0.046476908f, -0.15381487f, -0.0009432004f, 0.068324186f, -0.07473438f, 0.19692156f, -0.00023191162f, -0.07189867f, -0.08010463f, 0.2258111f, 0.11592476f, 0.17914976f, 0.13195598f, -0.11106629f, 0.12462127f, 0.006350248f, 0.09321404f, 0.03279733f, 0.040620834f, 0.07625015f,
+
+0.26654643f, 0.006987583f, 0.056940462f, -0.21681315f, 0.077801876f, 0.055067755f, -0.07760556f, 0.03872932f, -0.79303557f, -0.110598356f, 0.11750592f, 0.13262804f, -0.06422358f, 0.021544294f, 0.106549375f, 0.05221962f, -0.48878804f, -0.2284007f, 0.0011379553f, 0.1531422f, 0.07926333f, 0.00038042318f, 0.0017872434f, 0.0007042611f, 0.00024585766f, -0.0015021149f, 0.00033512182f, 0.17980112f, -0.00030350624f, -0.09183649f, -0.0003179727f, -0.17676876f, 0.053549517f, -0.301563f, 0.019367442f, -0.000101853504f, -0.03712425f, -0.077965915f, -0.16881329f, -0.5796423f, 0.15654868f, -0.0013217079f, -0.0010914453f, 0.0011883607f, 0.106605545f, -0.12484317f, 0.0004226503f, 0.09296495f, -0.38826272f, 0.29945183f, 0.000777706f, -0.28242147f, -0.09771982f, 0.30562764f, 0.21152276f, 0.07008504f, 0.08235849f, -0.00946117f, 0.14994532f, 0.025700504f, 0.22086006f, 0.01654313f, -0.040672258f, 0.012883936f,
+
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+
+-0.09508168f, -0.075439416f, 0.27062836f, 0.08787128f, 0.101400554f, 0.26852965f, -0.59093076f, 0.19821987f, 0.08937512f, 0.055678036f, -0.116133705f, 0.039116386f, 0.06315727f, 0.107821845f, -0.019807387f, 0.14512414f, -0.060943954f, -0.07014007f, 0.00016978045f, 0.17468223f, 0.06063257f, -7.286974e-05f, 0.0005939672f, 0.0018404772f, 0.0011290488f, 0.00019233255f, 0.0019600382f, 0.07629803f, 0.00034283352f, -0.0005339052f, -0.00011325302f, -0.0320187f, 0.041795913f, -0.31851268f, 0.08271041f, 0.0021725951f, -0.16681935f, -0.031819552f, -0.32887435f, 0.046451382f, 0.1761192f, 0.00069008686f, 7.961439e-05f, -0.00019473303f, -0.09694852f, -0.033249408f, -0.0008172128f, 0.22586535f, -0.22233704f, -0.05459794f, -9.828665e-05f, -0.14924103f, -0.03904952f, 0.20695034f, 0.07704979f, 0.16610599f, 0.14414144f, -0.23807625f, 0.102441765f, 0.09765428f, 0.08840623f, -0.024117084f, 0.0006691144f, 0.17866156f,
+
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+
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+
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+
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+
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+
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+
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+0.0005521098f, 0.01772917f, -0.17225818f, 0.0037039423f, 0.0015673604f, -0.10055038f, 0.021108633f, 0.020772647f, 0.14595065f, -0.04253008f, 0.013751122f, 0.007689795f, 0.041917972f, 0.016940184f, 0.002107906f, -0.06683443f, 0.020539016f, 0.029143851f, -7.801321e-05f, 0.0004836811f, -0.017668154f, -0.0005448151f, 0.0010524365f, -0.0007671644f, -0.00012459021f, 0.0008768695f, -0.00051357795f, -0.0037997859f, 0.0003861398f, 0.014108769f, 0.00069321576f, -0.006722216f, -0.020900667f, 0.026551543f, -0.0011496779f, -0.00075074355f, 0.028344141f, 0.009201196f, 0.0057718405f, 0.021699302f, -0.014502635f, -3.4917146e-05f, -0.00035786058f, -0.0011784286f, 0.060572445f, 0.020316433f, -0.0011969139f, -0.04873412f, 0.023842258f, -0.023542333f, 0.0017061911f, 0.021966225f, 0.00033679532f, -0.19098286f, 0.06507214f, -0.025174895f, -0.045645624f, 0.03047322f, -0.03555776f, 0.019031342f, 0.025006592f, 0.002873845f, 0.013087436f, -0.017678551f,
+
+0.57228166f, 0.44931725f, 0.033467986f, -0.052152947f, -0.16510761f, 0.095149025f, -0.25350976f, -0.31727728f, 0.020857004f, 0.01630847f, -0.0931435f, 0.1957119f, -0.39591384f, 0.2692201f, 0.33176333f, 0.11175347f, -0.2671032f, -0.056412164f, -0.001511809f, 0.29373026f, 0.17934428f, -0.0010251943f, 0.0010095476f, 0.0035850229f, 0.00065879535f, 0.00093925773f, 0.00033792327f, 0.34793642f, -0.00042587394f, -0.08081586f, 0.00038307233f, -0.011362356f, -0.0033058012f, -0.08819704f, -0.32478446f, -0.0011537038f, -0.27391264f, -0.11553899f, 0.17199908f, -0.0041303267f, 0.41343948f, 0.000357048f, 0.0014987858f, 0.0013575226f, -0.5571183f, -0.2880887f, -0.002448622f, 0.17940249f, -0.20062222f, 0.3171509f, 0.0008355412f, -0.07066481f, -0.13722952f, -0.10970398f, 0.058733325f, 0.24034949f, 0.18251064f, 0.11015398f, 0.24339579f, -0.041504826f, 0.19960985f, -0.15185966f, -0.2734284f, 0.13767993f,
+
+0.22348885f, -0.008877726f, -0.17189537f, -0.43331224f, 0.2023295f, 0.04317003f, -0.3600444f, -0.0067409207f, 0.18264559f, -0.11805032f, -0.07412461f, 0.03241709f, 0.051556725f, 0.085615896f, 0.40916997f, -0.07864307f, -0.22887087f, -0.24392724f, 0.00014124371f, 0.6468839f, -0.036077045f, -0.0014531002f, -0.0011161002f, 0.003305897f, 0.0017938324f, -3.750653e-05f, -0.0016759017f, 0.4013441f, -0.00073333486f, -0.28097916f, -0.0010191813f, 0.019602012f, 0.09314859f, -0.53062683f, 0.1758001f, -1.5525151e-05f, -0.20916408f, -0.66344565f, -0.14848995f, -0.065955415f, -0.034880806f, -1.1966582e-06f, 0.00036120228f, -0.0012568037f, -0.10609765f, -0.58169466f, -0.0006648826f, 0.44565904f, -0.5121707f, 0.24637467f, 0.0010917422f, -0.23795755f, -0.2328576f, -0.0765637f, 0.330303f, 0.27319f, 0.094247416f, -0.16981891f, 0.017022926f, -0.10659436f, 0.11089696f, -0.08941251f, -0.3529318f, 0.0654588f
+
+};
+
+static const float conv2_biases[] = {
+0.12326373f,
+0.13270757f,
+0.07082674f,
+0.051456157f,
+0.058445618f,
+0.13153197f,
+0.0809729f,
+0.10153213f,
+0.055915363f,
+0.05228166f,
+-0.11212896f,
+0.07462141f,
+-0.10300769f,
+0.10817513f,
+0.15686865f,
+0.1822583f,
+0.06780991f,
+-0.027867194f,
+0.10957543f,
+0.034252886f,
+0.05988423f,
+-0.0481856f,
+0.074781254f,
+-0.07338138f,
+-0.022100607f,
+-0.049476217f,
+0.0001618523f,
+0.16787314f,
+-0.086404406f,
+0.06046943f,
+-0.1733751f,
+0.2654999f
+};
+
+static const float conv3_kernel[] = {
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+
+};
+
+static const float conv3_biases[] = {
+0.05037664f
+};
+
+#endif
--
2.14.1