forked from FFmpeg/FFmpeg
avfilter/dnn/dnn_backend_tf: simplify the code with ff_hex_to_data
please use tools/python/tf_sess_config.py to get the sess_config after that. note the byte order of session config is in normal order. bump the MICRO version for the config change. Signed-off-by: Limin Wang <lance.lmwang@gmail.com>
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3 changed files with 54 additions and 35 deletions
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@ -28,6 +28,7 @@
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#include "dnn_backend_native_layer_conv2d.h"
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#include "dnn_backend_native_layer_conv2d.h"
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#include "dnn_backend_native_layer_depth2space.h"
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#include "dnn_backend_native_layer_depth2space.h"
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#include "libavformat/avio.h"
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#include "libavformat/avio.h"
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#include "libavformat/internal.h"
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#include "libavutil/avassert.h"
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#include "libavutil/avassert.h"
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#include "../internal.h"
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#include "../internal.h"
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#include "dnn_backend_native_layer_pad.h"
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#include "dnn_backend_native_layer_pad.h"
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@ -206,53 +207,26 @@ static DNNReturnType load_tf_model(TFModel *tf_model, const char *model_filename
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// prepare the sess config data
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// prepare the sess config data
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if (tf_model->ctx.options.sess_config != NULL) {
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if (tf_model->ctx.options.sess_config != NULL) {
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const char *config;
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/*
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/*
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tf_model->ctx.options.sess_config is hex to present the serialized proto
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tf_model->ctx.options.sess_config is hex to present the serialized proto
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required by TF_SetConfig below, so we need to first generate the serialized
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required by TF_SetConfig below, so we need to first generate the serialized
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proto in a python script, the following is a script example to generate
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proto in a python script, tools/python/tf_sess_config.py is a script example
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serialized proto which specifies one GPU, we can change the script to add
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to generate the configs of sess_config.
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more options.
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import tensorflow as tf
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gpu_options = tf.GPUOptions(visible_device_list='0')
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config = tf.ConfigProto(gpu_options=gpu_options)
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s = config.SerializeToString()
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b = ''.join("%02x" % int(ord(b)) for b in s[::-1])
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print('0x%s' % b)
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the script output looks like: 0xab...cd, and then pass 0xab...cd to sess_config.
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*/
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*/
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char tmp[3];
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tmp[2] = '\0';
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if (strncmp(tf_model->ctx.options.sess_config, "0x", 2) != 0) {
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if (strncmp(tf_model->ctx.options.sess_config, "0x", 2) != 0) {
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av_log(ctx, AV_LOG_ERROR, "sess_config should start with '0x'\n");
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av_log(ctx, AV_LOG_ERROR, "sess_config should start with '0x'\n");
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return DNN_ERROR;
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return DNN_ERROR;
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}
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}
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config = tf_model->ctx.options.sess_config + 2;
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sess_config_length = ff_hex_to_data(NULL, config);
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sess_config_length = strlen(tf_model->ctx.options.sess_config);
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sess_config = av_mallocz(sess_config_length + AV_INPUT_BUFFER_PADDING_SIZE);
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if (sess_config_length % 2 != 0) {
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av_log(ctx, AV_LOG_ERROR, "the length of sess_config is not even (%s), "
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"please re-generate the config.\n",
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tf_model->ctx.options.sess_config);
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return DNN_ERROR;
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}
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sess_config_length -= 2; //ignore the first '0x'
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sess_config_length /= 2; //get the data length in byte
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sess_config = av_malloc(sess_config_length);
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if (!sess_config) {
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if (!sess_config) {
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av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
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av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
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return DNN_ERROR;
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return DNN_ERROR;
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}
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}
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ff_hex_to_data(sess_config, config);
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for (int i = 0; i < sess_config_length; i++) {
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int index = 2 + (sess_config_length - 1 - i) * 2;
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tmp[0] = tf_model->ctx.options.sess_config[index];
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tmp[1] = tf_model->ctx.options.sess_config[index + 1];
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sess_config[i] = strtol(tmp, NULL, 16);
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}
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}
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}
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graph_def = read_graph(model_filename);
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graph_def = read_graph(model_filename);
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@ -31,7 +31,7 @@
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#define LIBAVFILTER_VERSION_MAJOR 8
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#define LIBAVFILTER_VERSION_MAJOR 8
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#define LIBAVFILTER_VERSION_MINOR 0
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#define LIBAVFILTER_VERSION_MINOR 0
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#define LIBAVFILTER_VERSION_MICRO 100
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#define LIBAVFILTER_VERSION_MICRO 101
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#define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \
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#define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \
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45
tools/python/tf_sess_config.py
Normal file
45
tools/python/tf_sess_config.py
Normal file
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@ -0,0 +1,45 @@
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# Copyright (c) 2021
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#
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# This file is part of FFmpeg.
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#
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# FFmpeg is free software; you can redistribute it and/or
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# modify it under the terms of the GNU Lesser General Public
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# License as published by the Free Software Foundation; either
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# version 2.1 of the License, or (at your option) any later version.
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#
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# FFmpeg is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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# Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with FFmpeg; if not, write to the Free Software
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# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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# ==============================================================================
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# verified with Python 3.6.8 on CentOS 7.2
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import tensorflow as tf
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visible_device_list = '0' # use , separator for more GPUs like '0, 1'
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per_process_gpu_memory_fraction = 0.9 # avoid out of memory
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intra_op_parallelism_threads = 2 # default in tensorflow
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inter_op_parallelism_threads = 5 # default in tensorflow
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gpu_options = tf.compat.v1.GPUOptions(
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per_process_gpu_memory_fraction = per_process_gpu_memory_fraction,
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visible_device_list = visible_device_list,
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allow_growth = True)
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config = tf.compat.v1.ConfigProto(
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allow_soft_placement = True,
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log_device_placement = False,
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intra_op_parallelism_threads = intra_op_parallelism_threads,
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inter_op_parallelism_threads = inter_op_parallelism_threads,
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gpu_options = gpu_options)
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s = config.SerializeToString()
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# print(list(map(hex, s))) # print by json if need
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print('a serialized protobuf string for TF_SetConfig, note the byte order is in normal order.')
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b = ''.join(format(b,'02x') for b in s)
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print('0x%s' % b) # print by hex format
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