(self, x, y)
| 71 | return self.dense(x) |
| 72 | |
| 73 | def train_one_batch(self, x, y): |
| 74 | out = self.forward(x) |
| 75 | y = self.reshape2(y, (-1, 1)) |
| 76 | loss = self.softmax_cross_entropy(out, y) |
| 77 | self.optimizer(loss) |
| 78 | return out, loss |
| 79 | |
| 80 | def get_states(self): |
| 81 | ret = super().get_states() |