downstream/votenet_det_new/models/backbone/sparseconv/models/res16unet.py [47:224]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        stride=1,
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)

    self.bn0 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)

    self.conv1p1s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn1 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block1 = self._make_layer(
        self.BLOCK,
        self.PLANES[0],
        self.LAYERS[0],
        dilation=dilations[0],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv2p2s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn2 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block2 = self._make_layer(
        self.BLOCK,
        self.PLANES[1],
        self.LAYERS[1],
        dilation=dilations[1],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv3p4s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn3 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block3 = self._make_layer(
        self.BLOCK,
        self.PLANES[2],
        self.LAYERS[2],
        dilation=dilations[2],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv4p8s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn4 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block4 = self._make_layer(
        self.BLOCK,
        self.PLANES[3],
        self.LAYERS[3],
        dilation=dilations[3],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr4p16s2 = conv_tr(
        self.inplanes,
        self.PLANES[4],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr4 = get_norm(self.NORM_TYPE, self.PLANES[4], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[4] + self.PLANES[2] * self.BLOCK.expansion
    self.block5 = self._make_layer(
        self.BLOCK,
        self.PLANES[4],
        self.LAYERS[4],
        dilation=dilations[4],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr5p8s2 = conv_tr(
        self.inplanes,
        self.PLANES[5],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr5 = get_norm(self.NORM_TYPE, self.PLANES[5], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[5] + self.PLANES[1] * self.BLOCK.expansion
    self.block6 = self._make_layer(
        self.BLOCK,
        self.PLANES[5],
        self.LAYERS[5],
        dilation=dilations[5],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr6p4s2 = conv_tr(
        self.inplanes,
        self.PLANES[6],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr6 = get_norm(self.NORM_TYPE, self.PLANES[6], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[6] + self.PLANES[0] * self.BLOCK.expansion
    self.block7 = self._make_layer(
        self.BLOCK,
        self.PLANES[6],
        self.LAYERS[6],
        dilation=dilations[6],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr7p2s2 = conv_tr(
        self.inplanes,
        self.PLANES[7],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr7 = get_norm(self.NORM_TYPE, self.PLANES[7], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[7] + self.INIT_DIM
    self.block8 = self._make_layer(
        self.BLOCK,
        self.PLANES[7],
        self.LAYERS[7],
        dilation=dilations[7],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.final = conv(self.PLANES[7], out_channels, kernel_size=1, stride=1, bias=True, D=D)
    self.relu = MinkowskiReLU(inplace=True)

  def forward(self, x):
    out = self.conv0p1s1(x)
    out = self.bn0(out)
    out_p1 = self.relu(out)

    out = self.conv1p1s2(out_p1)
    out = self.bn1(out)
    out = self.relu(out)
    out_b1p2 = self.block1(out)

    out = self.conv2p2s2(out_b1p2)
    out = self.bn2(out)
    out = self.relu(out)
    out_b2p4 = self.block2(out)

    out = self.conv3p4s2(out_b2p4)
    out = self.bn3(out)
    out = self.relu(out)
    out_b3p8 = self.block3(out)

    # pixel_dist=16
    out = self.conv4p8s2(out_b3p8)
    out = self.bn4(out)
    out = self.relu(out)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



pretrain/pointcontrast/model/res16unet.py [51:228]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        stride=1,
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)

    self.bn0 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)

    self.conv1p1s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn1 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block1 = self._make_layer(
        self.BLOCK,
        self.PLANES[0],
        self.LAYERS[0],
        dilation=dilations[0],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv2p2s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn2 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block2 = self._make_layer(
        self.BLOCK,
        self.PLANES[1],
        self.LAYERS[1],
        dilation=dilations[1],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv3p4s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn3 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block3 = self._make_layer(
        self.BLOCK,
        self.PLANES[2],
        self.LAYERS[2],
        dilation=dilations[2],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.conv4p8s2 = conv(
        self.inplanes,
        self.inplanes,
        kernel_size=space_n_time_m(2, 1),
        stride=space_n_time_m(2, 1),
        dilation=1,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bn4 = get_norm(self.NORM_TYPE, self.inplanes, D, bn_momentum=bn_momentum)
    self.block4 = self._make_layer(
        self.BLOCK,
        self.PLANES[3],
        self.LAYERS[3],
        dilation=dilations[3],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr4p16s2 = conv_tr(
        self.inplanes,
        self.PLANES[4],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr4 = get_norm(self.NORM_TYPE, self.PLANES[4], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[4] + self.PLANES[2] * self.BLOCK.expansion
    self.block5 = self._make_layer(
        self.BLOCK,
        self.PLANES[4],
        self.LAYERS[4],
        dilation=dilations[4],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr5p8s2 = conv_tr(
        self.inplanes,
        self.PLANES[5],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr5 = get_norm(self.NORM_TYPE, self.PLANES[5], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[5] + self.PLANES[1] * self.BLOCK.expansion
    self.block6 = self._make_layer(
        self.BLOCK,
        self.PLANES[5],
        self.LAYERS[5],
        dilation=dilations[5],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr6p4s2 = conv_tr(
        self.inplanes,
        self.PLANES[6],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr6 = get_norm(self.NORM_TYPE, self.PLANES[6], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[6] + self.PLANES[0] * self.BLOCK.expansion
    self.block7 = self._make_layer(
        self.BLOCK,
        self.PLANES[6],
        self.LAYERS[6],
        dilation=dilations[6],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)
    self.convtr7p2s2 = conv_tr(
        self.inplanes,
        self.PLANES[7],
        kernel_size=space_n_time_m(2, 1),
        upsample_stride=space_n_time_m(2, 1),
        dilation=1,
        bias=False,
        conv_type=self.NON_BLOCK_CONV_TYPE,
        D=D)
    self.bntr7 = get_norm(self.NORM_TYPE, self.PLANES[7], D, bn_momentum=bn_momentum)

    self.inplanes = self.PLANES[7] + self.INIT_DIM
    self.block8 = self._make_layer(
        self.BLOCK,
        self.PLANES[7],
        self.LAYERS[7],
        dilation=dilations[7],
        norm_type=self.NORM_TYPE,
        bn_momentum=bn_momentum)

    self.final = conv(self.PLANES[7], out_channels, kernel_size=1, stride=1, bias=True, D=D)
    self.relu = MinkowskiReLU(inplace=True)


  def forward(self, x):
    out = self.conv0p1s1(x)
    out = self.bn0(out)
    out_p1 = self.relu(out)

    out = self.conv1p1s2(out_p1)
    out = self.bn1(out)
    out = self.relu(out)
    out_b1p2 = self.block1(out)

    out = self.conv2p2s2(out_b1p2)
    out = self.bn2(out)
    out = self.relu(out)
    out_b2p4 = self.block2(out)

    out = self.conv3p4s2(out_b2p4)
    out = self.bn3(out)
    out = self.relu(out)
    out_b3p8 = self.block3(out)

    out = self.conv4p8s2(out_b3p8)
    out = self.bn4(out)
    out = self.relu(out)
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -