(self, n_dim, n_data, K=65536, T=0.07, m=0.5)
| 93 | class CMCMem(BaseMem): |
| 94 | """Memory bank for two modalities, e.g. in CMC""" |
| 95 | def __init__(self, n_dim, n_data, K=65536, T=0.07, m=0.5): |
| 96 | super(CMCMem, self).__init__(K, T, m) |
| 97 | # create sampler |
| 98 | self.multinomial = AliasMethod(torch.ones(n_data)) |
| 99 | self.multinomial.cuda() |
| 100 | |
| 101 | # create memory bank |
| 102 | self.register_buffer('memory_1', torch.randn(n_data, n_dim)) |
| 103 | self.register_buffer('memory_2', torch.randn(n_data, n_dim)) |
| 104 | self.memory_1 = F.normalize(self.memory_1) |
| 105 | self.memory_2 = F.normalize(self.memory_2) |
| 106 | |
| 107 | def forward(self, x1, x2, y, x1_jig=None, x2_jig=None, |
| 108 | all_x1=None, all_x2=None, all_y=None): |
nothing calls this directly
no test coverage detected