def adapt_model_from_string()

in timesformer/models/helpers.py [0:0]

• 45 lines of code
• 12 McCabe index (conditional complexity)

def adapt_model_from_string(parent_module, model_string):
    separator = '***'
    state_dict = {}
    lst_shape = model_string.split(separator)
    for k in lst_shape:
        k = k.split(':')
        key = k[0]
        shape = k[1][1:-1].split(',')
        if shape[0] != '':
            state_dict[key] = [int(i) for i in shape]

    new_module = deepcopy(parent_module)
    for n, m in parent_module.named_modules():
        old_module = extract_layer(parent_module, n)
        if isinstance(old_module, nn.Conv2d) or isinstance(old_module, Conv2dSame):
            if isinstance(old_module, Conv2dSame):
                conv = Conv2dSame
            else:
                conv = nn.Conv2d
            s = state_dict[n + '.weight']
            in_channels = s[1]
            out_channels = s[0]
            g = 1
            if old_module.groups > 1:
                in_channels = out_channels
                g = in_channels
            new_conv = conv(
                in_channels=in_channels, out_channels=out_channels, kernel_size=old_module.kernel_size,
                bias=old_module.bias is not None, padding=old_module.padding, dilation=old_module.dilation,
                groups=g, stride=old_module.stride)
            set_layer(new_module, n, new_conv)
        if isinstance(old_module, nn.BatchNorm2d):
            new_bn = nn.BatchNorm2d(
                num_features=state_dict[n + '.weight'][0], eps=old_module.eps, momentum=old_module.momentum,
                affine=old_module.affine, track_running_stats=True)
            set_layer(new_module, n, new_bn)
        if isinstance(old_module, nn.Linear):
            num_features = state_dict[n + '.weight'][1]
            new_fc = Linear(
                in_features=num_features, out_features=old_module.out_features, bias=old_module.bias is not None)
            set_layer(new_module, n, new_fc)
            if hasattr(new_module, 'num_features'):
                new_module.num_features = num_features
    new_module.eval()
    parent_module.eval()

    return new_module