| 1 | from .Strategy import Strategy |
| 2 | |
| 3 | class NegativeSampling(Strategy): |
| 4 | |
| 5 | def __init__(self, model = None, loss = None, batch_size = 256, regul_rate = 0.0, l3_regul_rate = 0.0): |
| 6 | super(NegativeSampling, self).__init__() |
| 7 | self.model = model |
| 8 | self.loss = loss |
| 9 | self.batch_size = batch_size |
| 10 | self.regul_rate = regul_rate |
| 11 | self.l3_regul_rate = l3_regul_rate |
| 12 | |
| 13 | def _get_positive_score(self, score): |
| 14 | positive_score = score[:self.batch_size] |
| 15 | positive_score = positive_score.view(-1, self.batch_size).permute(1, 0) |
| 16 | return positive_score |
| 17 | |
| 18 | def _get_negative_score(self, score): |
| 19 | negative_score = score[self.batch_size:] |
| 20 | negative_score = negative_score.view(-1, self.batch_size).permute(1, 0) |
| 21 | return negative_score |
| 22 | |
| 23 | def forward(self, data): |
| 24 | score = self.model(data) |
| 25 | p_score = self._get_positive_score(score) |
| 26 | n_score = self._get_negative_score(score) |
| 27 | loss_res = self.loss(p_score, n_score) |
| 28 | if self.regul_rate != 0: |
| 29 | loss_res += self.regul_rate * self.model.regularization(data) |
| 30 | if self.l3_regul_rate != 0: |
| 31 | loss_res += self.l3_regul_rate * self.model.l3_regularization() |
| 32 | return loss_res |
no outgoing calls
no test coverage detected