def setUp(self): super(PluginTest, self).setUp() # Log dir to save temp events into. self._log_dir = self.get_temp_dir() self._eval_result_output_dir = os.path.join(self.get_temp_dir(), "eval_result") if not os.path.isdir(self._eval_result_output_dir): os.mkdir(self._eval_result_output_dir) writer = tf.summary.create_file_writer(self._log_dir) with writer.as_default(): summary_v2.FairnessIndicators(self._eval_result_output_dir, step=1) writer.close() # Start a server that will receive requests. self._multiplexer = event_multiplexer.EventMultiplexer({ ".": self._log_dir, }) self._context = base_plugin.TBContext(logdir=self._log_dir, multiplexer=self._multiplexer) self._plugin = plugin.FairnessIndicatorsPlugin(self._context) self._multiplexer.Reload() wsgi_app = application.TensorBoardWSGI([self._plugin]) self._server = werkzeug_test.Client(wsgi_app, wrappers.BaseResponse) self._routes = self._plugin.get_plugin_apps()
def main(unused_argv): writer = tf.summary.create_file_writer(FLAGS.logdir) with writer.as_default(): summary_v2.FairnessIndicators(FLAGS.eval_result_output_dir, step=1) writer.close()
def _write_summary(self, eval_result_output_dir): writer = tf2.summary.create_file_writer(self.get_temp_dir()) with writer.as_default(): summary_v2.FairnessIndicators(eval_result_output_dir, step=1) writer.close()