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[Example] Training offloading service example
- This app uses ml service APIs - You must run the receiver first with receiver.conf for the sender to work Signed-off-by: hyunil park <[email protected]>
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Tizen.platform/training_offloading_service/gen_training_offloading_service_rpm.sh
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#!/usr/bin/env bash | ||
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git init | ||
git add * | ||
git commit -m 'Initial commit' | ||
#gbs build -A armv7l --include-all --clean | ||
gbs build --include-all -A armv7l -P public_9.0_arm | ||
rm -rf .git |
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/** | ||
* @file main.c | ||
* @date 2 May 2024 | ||
* @brief Training offloading service app. | ||
* @see https://github.com/nnstreamer/nnstreamer | ||
* @author <[email protected]> | ||
* @bug No known bugs. | ||
*/ | ||
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#include <stdio.h> | ||
#include <stdlib.h> | ||
#include <unistd.h> | ||
#include <glib.h> | ||
#include <ml-api-service.h> | ||
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#define MAX_STRING_LEN 2048 | ||
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enum { | ||
CURRENT_STATUS_MAINMENU, | ||
CURRENT_STATUS_INPUT_FILENAME, | ||
CURRENT_STATUS_INPUT_RW_PATH, | ||
}; | ||
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int g_menu_state = CURRENT_STATUS_MAINMENU; | ||
GMainLoop *loop; | ||
static gchar g_config_path[MAX_STRING_LEN]; | ||
static gchar g_path[MAX_STRING_LEN]; | ||
ml_service_h service_h; | ||
#define ML_SERVICE_EVENT_REPLY 4 | ||
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/** | ||
* @brief Callback function for reply test. | ||
*/ | ||
static void | ||
_receive_trained_model_cb (ml_service_event_e event, ml_information_h event_data, void *user_data) | ||
{ | ||
switch ((int) event) { | ||
case ML_SERVICE_EVENT_REPLY: | ||
{ | ||
g_warning ("Get ML_SERVICE_EVENT_REPLY and received trained model"); | ||
break; | ||
} | ||
default: | ||
break; | ||
} | ||
} | ||
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/** | ||
* @brief Callback function for sink node. | ||
*/ | ||
static void | ||
_sink_register_cb (ml_service_event_e event, ml_information_h event_data, void *user_data) | ||
{ | ||
ml_tensors_data_h data = NULL; | ||
double *output = NULL; | ||
size_t data_size = 0; | ||
int status, i; | ||
double result_data[4]; | ||
char *output_node_name = NULL; | ||
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switch (event) { | ||
case ML_SERVICE_EVENT_NEW_DATA: | ||
g_return_if_fail (event_data != NULL); | ||
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status = ml_information_get (event_data, "name", (void **) &output_node_name); | ||
if (status != ML_ERROR_NONE) | ||
return; | ||
if (!output_node_name) | ||
return; | ||
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status = ml_information_get (event_data, "data", &data); | ||
if (status != ML_ERROR_NONE) | ||
return; | ||
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status = ml_tensors_data_get_tensor_data (data, 0, (void **) &output, &data_size); | ||
if (status != ML_ERROR_NONE) | ||
return; | ||
break; | ||
default: | ||
break; | ||
} | ||
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if (output) { | ||
for (i = 0; i < 4; i++) | ||
result_data[i] = output[i]; | ||
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g_print ("name:%s >> [training_loss: %f, training_accuracy: %f, validation_loss: %f, validation_accuracy: %f]", | ||
output_node_name, result_data[0], result_data[1], result_data[2], | ||
result_data[3]); | ||
} | ||
} | ||
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/** | ||
* @brief menu interface function | ||
*/ | ||
static void | ||
input_filepath (gchar *src, gchar *path) | ||
{ | ||
gint len = 0; | ||
gsize size = 0; | ||
g_return_if_fail (path != NULL); | ||
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len = strlen(path); | ||
if (len < 0 || len > MAX_STRING_LEN -1) | ||
return; | ||
size = g_strlcpy(src, path, MAX_STRING_LEN); | ||
if (len != size) | ||
return; | ||
} | ||
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/** | ||
* @brief menu interface function | ||
*/ | ||
void | ||
main_menu () | ||
{ | ||
g_print("\n"); | ||
g_print("============================================================================\n"); | ||
g_print(" Training Offloading Services Test (press q to quit) \n"); | ||
g_print("----------------------------------------------------------------------------\n"); | ||
g_print("a. Create \n"); | ||
g_print("b. Set R/W path \n"); | ||
g_print("c. Set callback for receiver \n"); | ||
g_print("d. Set callback for sender \n"); | ||
g_print("e. Start \n"); | ||
g_print("f. Stop \n"); | ||
g_print("g. End \n"); | ||
g_print("q. Quit \n"); | ||
g_print("============================================================================\n"); | ||
} | ||
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/** | ||
* @brief menu interface function | ||
*/ | ||
static void | ||
quit_program () | ||
{ | ||
g_main_loop_quit (loop); | ||
} | ||
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/** | ||
* @brief menu interface function | ||
*/ | ||
void | ||
reset_menu_status (void) | ||
{ | ||
g_menu_state = CURRENT_STATUS_MAINMENU; | ||
} | ||
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/** | ||
* @brief menu interface function | ||
*/ | ||
static void | ||
display_menu () | ||
{ | ||
if (g_menu_state == CURRENT_STATUS_MAINMENU) { | ||
main_menu(); | ||
} else if (g_menu_state == CURRENT_STATUS_INPUT_FILENAME) { | ||
g_print("*** input config file path.\n"); | ||
} else if (g_menu_state == CURRENT_STATUS_INPUT_RW_PATH) { | ||
g_print("*** input path for reading or writing. e.g. /opt \n"); | ||
} else { | ||
g_print("*** Unknown status. \n"); | ||
} | ||
g_print(" >>> "); | ||
} | ||
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/** | ||
* @brief interpret main menu | ||
*/ | ||
static void | ||
interpret_main_menu (char *cmd) | ||
{ | ||
int ret = ML_ERROR_NONE; | ||
if (!g_strcmp0 (cmd, "a")) { | ||
g_menu_state = CURRENT_STATUS_INPUT_FILENAME; | ||
} else if (!g_strcmp0 (cmd, "b")) { | ||
g_menu_state = CURRENT_STATUS_INPUT_RW_PATH; | ||
} else if (!g_strcmp0 (cmd, "c")) { | ||
ret = ml_service_set_event_cb (service_h, _sink_register_cb, NULL); | ||
} else if (!g_strcmp0 (cmd, "d")) { | ||
ret = ml_service_set_event_cb (service_h, _receive_trained_model_cb, NULL); | ||
} else if (!g_strcmp0 (cmd, "e")) { | ||
ret = ml_service_start (service_h); | ||
} else if (!g_strcmp0 (cmd, "f")) { | ||
ret = ml_service_stop (service_h); | ||
} else if (!g_strcmp0 (cmd, "g")) { | ||
ret = ml_service_destroy (service_h); | ||
} else if (!g_strcmp0 (cmd, "q")) { | ||
quit_program(); | ||
return; | ||
} | ||
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if (ret == ML_ERROR_NONE) | ||
g_print("*** Success *** \n"); | ||
else | ||
g_print("*** Failed *** \n"); | ||
} | ||
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/** | ||
* @brief timeout for menu display | ||
*/ | ||
gboolean | ||
timeout_menu_display (void *data) | ||
{ | ||
display_menu (); | ||
return FALSE; | ||
} | ||
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/** | ||
* @brief interpret function | ||
*/ | ||
static void | ||
interpret (gchar *cmd) | ||
{ | ||
switch (g_menu_state) { | ||
case CURRENT_STATUS_MAINMENU: | ||
interpret_main_menu (cmd); | ||
break; | ||
case CURRENT_STATUS_INPUT_FILENAME: | ||
input_filepath (g_config_path, cmd); | ||
reset_menu_status (); | ||
g_print("config path=%s\n", g_config_path); | ||
if (ML_ERROR_NONE == ml_service_new (g_config_path, &service_h)) | ||
g_print("Success to create service(handle=%p)\n", service_h); | ||
else | ||
g_print("Failed to create service \n"); | ||
break; | ||
case CURRENT_STATUS_INPUT_RW_PATH: | ||
input_filepath (g_path, cmd); | ||
reset_menu_status (); | ||
if (ML_ERROR_NONE == ml_service_set_information (service_h, "path", g_path)) | ||
g_print ("Success to set path \n"); | ||
else | ||
g_print ("Failed to set path \n"); | ||
break; | ||
default: | ||
break; | ||
} | ||
g_timeout_add (100, timeout_menu_display, 0); | ||
} | ||
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/** | ||
* @brief input function | ||
*/ | ||
gboolean | ||
input (GIOChannel *channel) | ||
{ | ||
gchar buf[MAX_STRING_LEN]; | ||
ssize_t cnt; | ||
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memset (buf, 0, MAX_STRING_LEN); | ||
cnt = read (0, (void *)buf, MAX_STRING_LEN); | ||
if (cnt == 0) return TRUE; | ||
buf[cnt - 1] = 0; | ||
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interpret (buf); | ||
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return TRUE; | ||
} | ||
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/** | ||
* @brief Main function. | ||
*/ | ||
int | ||
main (int argc, char **argv) | ||
{ | ||
GIOChannel *stdin_channel; | ||
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stdin_channel = g_io_channel_unix_new (0); | ||
g_io_channel_set_flags (stdin_channel, G_IO_FLAG_NONBLOCK, NULL); | ||
g_io_add_watch (stdin_channel, G_IO_IN, (GIOFunc)input, NULL); | ||
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loop = g_main_loop_new (NULL, FALSE); | ||
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g_print("running\n"); | ||
display_menu (); | ||
g_main_loop_run (loop); | ||
g_print("exit training offloading services\n"); | ||
g_main_loop_unref (loop); | ||
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return 0; | ||
} |
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project('nnstreamer-example', 'c', 'cpp', | ||
version: '0.1.0', | ||
license: ['LGPL-2.1'], | ||
meson_version: '>=0.50.0', | ||
default_options: [ | ||
'werror=true', | ||
'warning_level=1', | ||
'c_std=gnu89', | ||
'cpp_std=c++11' | ||
] | ||
) | ||
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# Set install path | ||
nnst_exam_prefix = get_option('prefix') | ||
nnst_exam_bindir = join_paths(nnst_exam_prefix, get_option('bindir')) | ||
examples_install_dir = nnst_exam_bindir | ||
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# Dependencies | ||
glib_dep = dependency('glib-2.0') | ||
nns_edge_dep = dependency('nnstreamer-edge', required: false) | ||
nns_capi_common_dep = dependency('capi-ml-common', required: false) | ||
ml_service_dep = dependency('capi-ml-service', required: false) | ||
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executable('training_offloadinge_service', | ||
'main.c', | ||
dependencies: [glib_dep, nns_edge_dep, nns_capi_common_dep, ml_service_dep], | ||
install: true, | ||
install_dir: examples_install_dir | ||
) | ||
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Tizen.platform/training_offloading_service/packaging/training_offloading_service.manifest
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<manifest> | ||
<request> | ||
<domain name="_"/> | ||
</request> | ||
</manifest> |
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Tizen.platform/training_offloading_service/packaging/training_offloading_service.spec
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%define nnstexampledir /usr/lib/nnstreamer/bin | ||
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Name: training_offloading_service | ||
Summary: training_offloadingi_service app | ||
Version: 1.0.0 | ||
Release: 0 | ||
Group: Machine Learning/ML Framework | ||
Packager: Hyunil Park <[email protected]> | ||
License: LGPL-2.1 | ||
Source0: %{name}-%{version}.tar.gz | ||
Source1001: %{name}.manifest | ||
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Requires: nnstreamer | ||
Requires: nnstreamer-edge | ||
BuildRequires: meson | ||
BuildRequires: pkgconfig(glib-2.0) | ||
BuildRequires: pkgconfig(capi-ml-service) | ||
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%description | ||
training offloading service sample app with Tizen IoT platform | ||
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%prep | ||
%setup -q | ||
cp %{SOURCE1001} . | ||
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%build | ||
mkdir -p build | ||
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meson --buildtype=plain --prefix=%{_prefix} --libdir=%{_libdir} --bindir=%{nnstexampledir} --includedir=%{_includedir} build | ||
ninja -C build %{?_smp_mflags} | ||
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%install | ||
DESTDIR=%{buildroot} ninja -C build install | ||
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%files | ||
%manifest %{name}.manifest | ||
%defattr(-,root,root,-) | ||
%{nnstexampledir}/* | ||
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