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()