Encode the input BEV features. Args: x (tensor): the input BEV features. Returns: A list that contains all the encoded layers.
(self, x)
| 100 | self.bn_decompress = nn.BatchNorm2d(256) |
| 101 | |
| 102 | def encode(self, x): |
| 103 | """Encode the input BEV features. |
| 104 | |
| 105 | Args: |
| 106 | x (tensor): the input BEV features. |
| 107 | |
| 108 | Returns: |
| 109 | A list that contains all the encoded layers. |
| 110 | """ |
| 111 | batch, seq, z, h, w = x.size() |
| 112 | |
| 113 | x = x.view(-1, x.size(-3), x.size(-2), x.size(-1)) |
| 114 | x = x.to(torch.float) |
| 115 | x = F.relu(self.bn_pre_1(self.conv_pre_1(x))) |
| 116 | x = F.relu(self.bn_pre_2(self.conv_pre_2(x))) |
| 117 | |
| 118 | # -------------------------------- Encoder Path -------------------------------- |
| 119 | # -- STC block 1 |
| 120 | x_1 = F.relu(self.bn1_1(self.conv1_1(x))) |
| 121 | x_1 = F.relu(self.bn1_2(self.conv1_2(x_1))) |
| 122 | |
| 123 | x_1 = x_1.view( |
| 124 | batch, -1, x_1.size(1), x_1.size(2), x_1.size(3) |
| 125 | ).contiguous() # (batch, seq, c, h, w) |
| 126 | x_1 = self.conv3d_1(x_1) |
| 127 | x_1 = x_1.view( |
| 128 | -1, x_1.size(2), x_1.size(3), x_1.size(4) |
| 129 | ).contiguous() # (batch * seq, c, h, w) |
| 130 | |
| 131 | # -- STC block 2 |
| 132 | x_2 = F.relu(self.bn2_1(self.conv2_1(x_1))) |
| 133 | x_2 = F.relu(self.bn2_2(self.conv2_2(x_2))) |
| 134 | |
| 135 | x_2 = x_2.view( |
| 136 | batch, -1, x_2.size(1), x_2.size(2), x_2.size(3) |
| 137 | ).contiguous() # (batch, seq, c, h, w) |
| 138 | x_2 = self.conv3d_2(x_2) |
| 139 | x_2 = x_2.view( |
| 140 | -1, x_2.size(2), x_2.size(3), x_2.size(4) |
| 141 | ).contiguous() # (batch * seq, c, h, w), seq = 1 |
| 142 | |
| 143 | # -- STC block 3 |
| 144 | x_3 = F.relu(self.bn3_1(self.conv3_1(x_2))) |
| 145 | x_3 = F.relu(self.bn3_2(self.conv3_2(x_3))) |
| 146 | |
| 147 | # -- STC block 4 |
| 148 | x_4 = F.relu(self.bn4_1(self.conv4_1(x_3))) |
| 149 | x_4 = F.relu(self.bn4_2(self.conv4_2(x_4))) |
| 150 | |
| 151 | # compress x_3 (the layer that agents communicates on) |
| 152 | if self.compress_level > 0: |
| 153 | x_3 = F.relu(self.bn_compress(self.com_compresser(x_3))) |
| 154 | x_3 = F.relu(self.bn_decompress(self.com_decompresser(x_3))) |
| 155 | |
| 156 | return [x, x_1, x_2, x_3, x_4] |
| 157 | |
| 158 | def decode( |
| 159 | self, |