| 32 | expansion = 1 |
| 33 | |
| 34 | def __init__(self, inplanes, planes, stride=1, downsample=None, dcn=None): |
| 35 | super(BasicBlock, self).__init__() |
| 36 | self.with_dcn = dcn is not None |
| 37 | self.conv1 = conv3x3(inplanes, planes, stride) |
| 38 | self.bn1 = BatchNorm2d(planes) |
| 39 | self.relu = nn.ReLU(inplace=True) |
| 40 | self.with_modulated_dcn = False |
| 41 | if self.with_dcn: |
| 42 | fallback_on_stride = dcn.get('fallback_on_stride', False) |
| 43 | self.with_modulated_dcn = dcn.get('modulated', False) |
| 44 | # self.conv2 = conv3x3(planes, planes) |
| 45 | if not self.with_dcn or fallback_on_stride: |
| 46 | self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, |
| 47 | padding=1, bias=False) |
| 48 | else: |
| 49 | deformable_groups = dcn.get('deformable_groups', 1) |
| 50 | if not self.with_modulated_dcn: |
| 51 | #from assets.ops.dcn import DeformConv |
| 52 | from ..assets.ops.dcn import DeformConv |
| 53 | conv_op = DeformConv |
| 54 | offset_channels = 18 |
| 55 | else: |
| 56 | #from assets.ops.dcn import ModulatedDeformConv |
| 57 | from ..assets.ops.dcn import ModulatedDeformConv |
| 58 | conv_op = ModulatedDeformConv |
| 59 | offset_channels = 27 |
| 60 | self.conv2_offset = nn.Conv2d( |
| 61 | planes, |
| 62 | deformable_groups * offset_channels, |
| 63 | kernel_size=3, |
| 64 | padding=1) |
| 65 | self.conv2 = conv_op( |
| 66 | planes, |
| 67 | planes, |
| 68 | kernel_size=3, |
| 69 | padding=1, |
| 70 | deformable_groups=deformable_groups, |
| 71 | bias=False) |
| 72 | self.bn2 = BatchNorm2d(planes) |
| 73 | self.downsample = downsample |
| 74 | self.stride = stride |
| 75 | |
| 76 | def forward(self, x): |
| 77 | residual = x |