I want each linear layer weights/biases to be initialized with the constant values. Following is the weight_init() method the way you suggested:
def weight_init(m):
    if isinstance(m, torch.nn.Linear):
        torch.manual_seed(786)
        torch.nn.init.xavier_uniform_(m.weight.data)
        torch.nn.init.xavier_uniform_(m.bias.data)

Applying above to the linear layers in the classifier parts of the VGG19.
model = VGG19()
model.apply(weight_init)

Following error is generated each time I call model.apply(weight_init):
ValueError: Fan in and fan out can not be computed for tensor with fewer than 2 dimensions
Where am I making a mistake?