def _write_dummy_files(self):
plugin_dir = '/tmp/beholder-test/plugins/beholder'
tf.gfile.MakeDirs(plugin_dir)
info_path = plugin_dir + '/section-info.pkl'
config_path = plugin_dir + '/config.pkl'
write_pickle([{
'shape': '(3, 3, 3, 64)',
'mean': '1.131e-07',
'min': '2.022e-11',
'range': '3.949e-07',
'name': 'conv1_1/weights:0',
'max': '3.949e-07'
}], info_path)
write_pickle({
'values': 'trainable_variables',
'mode': 'variance',
'scaling': 'layer',
'window_size': 10,
'FPS': 10,
'is_recording': False,
'show_all': False,
'colormap': 'grayscale'
}, config_path)
def __init__(self, context):
self._MULTIPLEXER = context.multiplexer
self.PLUGIN_LOGDIR = pau.PluginDirectory(context.logdir, PLUGIN_NAME)
self.FPS = 10
self.most_recent_frame = get_image_relative_to_script('no-data.png')
self.most_recent_info = [{
'name': 'Waiting for data...',
}]
if not tf.gfile.Exists(self.PLUGIN_LOGDIR):
tf.gfile.MakeDirs(self.PLUGIN_LOGDIR)
write_pickle(DEFAULT_CONFIG,
'{}/{}'.format(self.PLUGIN_LOGDIR, CONFIG_FILENAME))
def _serve_change_config(self, request):
config = {}
for key, value in request.form.items():
try:
config[key] = int(value)
except ValueError:
if value == 'false':
config[key] = False
elif value == 'true':
config[key] = True
else:
config[key] = value
self.FPS = config['FPS']
write_pickle(config, '{}/{}'.format(self.PLUGIN_LOGDIR, CONFIG_FILENAME))
return http_util.Respond(request, {'config': config}, 'application/json')
def __init__(self, session, logdir):
self.video_writer = None
self.PLUGIN_LOGDIR = logdir + '/plugins/' + PLUGIN_NAME
self.SESSION = session
self.frame_placeholder = None
self.summary_op = None
self.last_image_shape = []
self.last_update_time = time.time()
self.config_last_modified_time = -1
self.previous_config = dict(DEFAULT_CONFIG)
if not tf.gfile.Exists(self.PLUGIN_LOGDIR + '/config.pkl'):
tf.gfile.MakeDirs(self.PLUGIN_LOGDIR)
write_pickle(DEFAULT_CONFIG,
'{}/{}'.format(self.PLUGIN_LOGDIR, CONFIG_FILENAME))
self.visualizer = Visualizer(self.PLUGIN_LOGDIR)
def _save_section_info(self, arrays, sections):
infos = []
if self.config['values'] == 'trainable_variables':
names = [x.name for x in tf.trainable_variables()]
else:
names = range(len(arrays))
for array, section, name in zip(arrays, sections, names):
info = {}
info['name'] = name
info['shape'] = str(array.shape)
info['min'] = '{:.3e}'.format(section.min())
info['mean'] = '{:.3e}'.format(section.mean())
info['max'] = '{:.3e}'.format(section.max())
info['range'] = '{:.3e}'.format(section.max() - section.min())
info['height'] = section.shape[0]
infos.append(info)
write_pickle(infos, '{}/{}'.format(self.logdir, SECTION_INFO_FILENAME))
def _write_config(self): write_pickle(self.config, '/tmp/beholder-test/plugins/beholder/config.pkl')