Hi!
With proto files they can be serialised to many different formats, is there
a reason for it to use hex? The reason I ask is that it's not trivially
readable for those debugging the command line. Perhaps something like json
is better?
Even if not using json, maybe a file is a little easier? In cases where
people have a large system using this, it just seems like it would be
easier to chase down issues.
Thanks,
Chris
On Tue, Oct 13, 2020, 7:19 PM Guo, Yejun <yejun....@intel.com> wrote:
> TensorFlow C library accepts config for session options to
> set different parameters for the inference. This patch exports
> this interface.
>
> The config is a serialized tensorflow.ConfigProto proto, so we need
> two steps to use it:
> 1. generate the serialized proto with python (see script example below)
> the output looks like: 0xab...cd
> where 0xcd is the least significant byte and 0xab is the most significant
> byte.
>
> 2. pass the python script output into ffmpeg with
> dnn_processing=options=sess_config=0xab...cd
>
> The following script is an example to specify one GPU. If the system
> contains
> 3 GPU cards, the visible_device_list could be '0', '1', '2', '0,1' etc.
> '0' does not mean physical GPU card 0, we need to try and see.
> And we can also add more opitions here to generate more serialized proto.
>
> script example to generate serialized proto which specifies one GPU:
> import tensorflow as tf
> gpu_options = tf.GPUOptions(visible_device_list='0')
> config = tf.ConfigProto(gpu_options=gpu_options)
> s = config.SerializeToString()
> b = ''.join("%02x" % int(ord(b)) for b in s[::-1])
> print('0x%s' % b)
>
> Signed-off-by: Guo, Yejun <yejun....@intel.com>
> ---
> libavfilter/dnn/dnn_backend_tf.c | 78 +++++++++++++++++++++++++++++---
> 1 file changed, 72 insertions(+), 6 deletions(-)
>
> diff --git a/libavfilter/dnn/dnn_backend_tf.c
> b/libavfilter/dnn/dnn_backend_tf.c
> index be860b11b5..7f1b8f0097 100644
> --- a/libavfilter/dnn/dnn_backend_tf.c
> +++ b/libavfilter/dnn/dnn_backend_tf.c
> @@ -29,14 +29,20 @@
> #include "dnn_backend_native_layer_depth2space.h"
> #include "libavformat/avio.h"
> #include "libavutil/avassert.h"
> +#include "../internal.h"
> #include "dnn_backend_native_layer_pad.h"
> #include "dnn_backend_native_layer_maximum.h"
> #include "dnn_io_proc.h"
>
> #include <tensorflow/c/c_api.h>
>
> +typedef struct TFOptions{
> + char *sess_config;
> +} TFOptions;
> +
> typedef struct TFContext {
> const AVClass *class;
> + TFOptions options;
> } TFContext;
>
> typedef struct TFModel{
> @@ -47,14 +53,15 @@ typedef struct TFModel{
> TF_Status *status;
> } TFModel;
>
> -static const AVClass dnn_tensorflow_class = {
> - .class_name = "dnn_tensorflow",
> - .item_name = av_default_item_name,
> - .option = NULL,
> - .version = LIBAVUTIL_VERSION_INT,
> - .category = AV_CLASS_CATEGORY_FILTER,
> +#define OFFSET(x) offsetof(TFContext, x)
> +#define FLAGS AV_OPT_FLAG_FILTERING_PARAM
> +static const AVOption dnn_tensorflow_options[] = {
> + { "sess_config", "config for SessionOptions",
> OFFSET(options.sess_config), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0,
> FLAGS },
> + { NULL }
> };
>
> +AVFILTER_DEFINE_CLASS(dnn_tensorflow);
> +
> static DNNReturnType execute_model_tf(const DNNModel *model, const char
> *input_name, AVFrame *in_frame,
> const char **output_names, uint32_t
> nb_output, AVFrame *out_frame,
> int do_ioproc);
> @@ -180,10 +187,48 @@ static DNNReturnType load_tf_model(TFModel
> *tf_model, const char *model_filename
> TF_ImportGraphDefOptions *graph_opts;
> TF_SessionOptions *sess_opts;
> const TF_Operation *init_op;
> + uint8_t *sess_config = NULL;
> + int sess_config_length = 0;
> +
> + // prepare the sess config data
> + if (tf_model->ctx.options.sess_config != NULL) {
> + char tmp[3];
> + tmp[2] = '\0';
> +
> + if (strncmp(tf_model->ctx.options.sess_config, "0x", 2) != 0) {
> + av_log(ctx, AV_LOG_ERROR, "sess_config should start with
> '0x'\n");
> + return DNN_ERROR;
> + }
> +
> + sess_config_length = strlen(tf_model->ctx.options.sess_config);
> + if (sess_config_length % 2 != 0) {
> + av_log(ctx, AV_LOG_ERROR, "the length of sess_config is not
> even (%s), "
> + "please re-generate the config.\n",
> + tf_model->ctx.options.sess_config);
> + return DNN_ERROR;
> + }
> +
> + sess_config_length -= 2; //ignore the first '0x'
> + sess_config_length /= 2; //get the data length in byte
> +
> + sess_config = av_malloc(sess_config_length);
> + if (!sess_config) {
> + av_log(ctx, AV_LOG_ERROR, "failed to allocate memory\n");
> + return DNN_ERROR;
> + }
> +
> + for (int i = 0; i < sess_config_length; i++) {
> + int index = 2 + (sess_config_length - 1 - i) * 2;
> + tmp[0] = tf_model->ctx.options.sess_config[index];
> + tmp[1] = tf_model->ctx.options.sess_config[index + 1];
> + sess_config[i] = strtol(tmp, NULL, 16);
> + }
> + }
>
> graph_def = read_graph(model_filename);
> if (!graph_def){
> av_log(ctx, AV_LOG_ERROR, "Failed to read model \"%s\" graph\n",
> model_filename);
> + av_freep(&sess_config);
> return DNN_ERROR;
> }
> tf_model->graph = TF_NewGraph();
> @@ -196,11 +241,23 @@ static DNNReturnType load_tf_model(TFModel
> *tf_model, const char *model_filename
> TF_DeleteGraph(tf_model->graph);
> TF_DeleteStatus(tf_model->status);
> av_log(ctx, AV_LOG_ERROR, "Failed to import serialized graph to
> model graph\n");
> + av_freep(&sess_config);
> return DNN_ERROR;
> }
>
> init_op = TF_GraphOperationByName(tf_model->graph, "init");
> sess_opts = TF_NewSessionOptions();
> +
> + if (sess_config) {
> + TF_SetConfig(sess_opts, sess_config,
> sess_config_length,tf_model->status);
> + av_freep(&sess_config);
> + if (TF_GetCode(tf_model->status) != TF_OK) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to set config for sess
> options with %s\n",
> + tf_model->ctx.options.sess_config);
> + return DNN_ERROR;
> + }
> + }
> +
> tf_model->session = TF_NewSession(tf_model->graph, sess_opts,
> tf_model->status);
> TF_DeleteSessionOptions(sess_opts);
> if (TF_GetCode(tf_model->status) != TF_OK)
> @@ -595,6 +652,15 @@ DNNModel *ff_dnn_load_model_tf(const char
> *model_filename, const char *options,
> tf_model->ctx.class = &dnn_tensorflow_class;
> tf_model->model = model;
>
> + //parse options
> + av_opt_set_defaults(&tf_model->ctx);
> + if (av_opt_set_from_string(&tf_model->ctx, options, NULL, "=", "&") <
> 0) {
> + av_log(&tf_model->ctx, AV_LOG_ERROR, "Failed to parse options
> \"%s\"\n", options);
> + av_freep(&tf_model);
> + av_freep(&model);
> + return NULL;
> + }
> +
> if (load_tf_model(tf_model, model_filename) != DNN_SUCCESS){
> if (load_native_model(tf_model, model_filename) != DNN_SUCCESS){
> av_freep(&tf_model);
> --
> 2.17.1
>
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