(
self,
num_layers: int,
num_input_features: int,
bn_size: int,
growth_rate: int,
drop_rate: float,
memory_efficient: bool = False
)
| 98 | _version = 2 |
| 99 | |
| 100 | def __init__( |
| 101 | self, |
| 102 | num_layers: int, |
| 103 | num_input_features: int, |
| 104 | bn_size: int, |
| 105 | growth_rate: int, |
| 106 | drop_rate: float, |
| 107 | memory_efficient: bool = False |
| 108 | ) -> None: |
| 109 | super(_DenseBlock, self).__init__() |
| 110 | for i in range(num_layers): |
| 111 | layer = _DenseLayer( |
| 112 | num_input_features + i * growth_rate, |
| 113 | growth_rate=growth_rate, |
| 114 | bn_size=bn_size, |
| 115 | drop_rate=drop_rate, |
| 116 | memory_efficient=memory_efficient, |
| 117 | ) |
| 118 | self.add_module('denselayer%d' % (i + 1), layer) |
| 119 | |
| 120 | def forward(self, init_features: Tensor) -> Tensor: |
| 121 | features = [init_features] |
nothing calls this directly
no test coverage detected