def _inner_forward(x):
    identity = x
    out = self.conv1(x)
    out = self.norm1(out)
    out = self.relu(out)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv1_plugin_names)
    spx = torch.split(out, self.width, 1)
    sp = self.convs[0](spx[0].contiguous())
    sp = self.relu(self.bns[0](sp))
    out = sp
    for i in range(1, (self.scales - 1)):
        if (self.stage_type == 'stage'):
            sp = spx[i]
        else:
            sp = (sp + spx[i])
        sp = self.convs[i](sp.contiguous())
        sp = self.relu(self.bns[i](sp))
        out = torch.cat((out, sp), 1)
    if ((self.stage_type == 'normal') or (self.conv2_stride == 1)):
        out = torch.cat((out, spx[(self.scales - 1)]), 1)
    elif (self.stage_type == 'stage'):
        out = torch.cat((out, self.pool(spx[(self.scales - 1)])), 1)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv2_plugin_names)
    out = self.conv3(out)
    out = self.norm3(out)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv3_plugin_names)
    if (self.downsample is not None):
        identity = self.downsample(x)
    out += identity
    return out
def _inner_forward(x):
    identity = x
    out = self.conv1(x)
    out = self.norm1(out)
    out = self.relu(out)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv1_plugin_names)
    spx = torch.split(out, self.width, 1)
    sp = self.convs[0](spx[0].contiguous())
    sp = self.relu(self.bns[0](sp))
    out = sp
    for i in range(1, (self.scales - 1)):
        if (self.stage_type == 'stage'):
            sp = spx[i]
        else:
            sp = (sp + spx[i])
        sp = self.convs[i](sp.contiguous())
        sp = self.relu(self.bns[i](sp))
        out = torch.cat((out, sp), 1)
    if ((self.stage_type == 'normal') or (self.conv2_stride == 1)):
        out = torch.cat((out, spx[(self.scales - 1)]), 1)
    elif (self.stage_type == 'stage'):
        out = torch.cat((out, self.pool(spx[(self.scales - 1)])), 1)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv2_plugin_names)
    out = self.conv3(out)
    out = self.norm3(out)
    if self.with_plugins:
        out = self.forward_plugin(out, self.after_conv3_plugin_names)
    if (self.downsample is not None):
        identity = self.downsample(x)
    out += identity
    return out