(self, x, y, synflow_flag, dist_option, spars)
| 101 | return y |
| 102 | |
| 103 | def train_one_batch(self, x, y, synflow_flag, dist_option, spars): |
| 104 | out = self.forward(x) |
| 105 | if synflow_flag: |
| 106 | loss = self.sum_error(out) |
| 107 | else: # normal training |
| 108 | loss = self.softmax_cross_entropy(out, y) |
| 109 | |
| 110 | if dist_option == 'plain': |
| 111 | pn_p_g_list = self.optimizer(loss) |
| 112 | elif dist_option == 'half': |
| 113 | self.optimizer.backward_and_update_half(loss) |
| 114 | elif dist_option == 'partialUpdate': |
| 115 | self.optimizer.backward_and_partial_update(loss) |
| 116 | elif dist_option == 'sparseTopK': |
| 117 | self.optimizer.backward_and_sparse_update(loss, |
| 118 | topK=True, |
| 119 | spars=spars) |
| 120 | elif dist_option == 'sparseThreshold': |
| 121 | self.optimizer.backward_and_sparse_update(loss, |
| 122 | topK=False, |
| 123 | spars=spars) |
| 124 | return pn_p_g_list, out, loss |
| 125 | |
| 126 | def set_optimizer(self, optimizer): |
| 127 | self.optimizer = optimizer |
nothing calls this directly
no test coverage detected