| 353 | |
| 354 | # compute acc & auc |
| 355 | def _create_metrics(self): |
| 356 | self.auc1, self.auc_op1 = tf.metrics.auc(labels=self._label[:,0], |
| 357 | predictions=self.probability[:,0], |
| 358 | num_thresholds=1000) |
| 359 | self.auc2, self.auc_op2 = tf.metrics.auc(labels=self._label[:,1], |
| 360 | predictions=self.probability[:, 1], |
| 361 | num_thresholds=1000) |
| 362 | self.acc1, self.acc_op1 = tf.metrics.accuracy(labels=self._label[:,0], |
| 363 | predictions=self.output[:,0]) |
| 364 | self.acc2, self.acc_op2 = tf.metrics.accuracy(labels=self._label[:,1], |
| 365 | predictions=self.output[:,1]) |
| 366 | |
| 367 | tf.summary.scalar('eval_auc1', self.auc1) |
| 368 | tf.summary.scalar('eval_auc2', self.auc2) |
| 369 | tf.summary.scalar('eval_acc1', self.acc1) |
| 370 | tf.summary.scalar('eval_acc2', self.acc2) |
| 371 | |
| 372 | # generate dataset pipline |
| 373 | def build_model_input(filename, batch_size, num_epochs): |