yes, the problem appears during `load_state_dict(), I have looked at the structure of my model instantiation and the model constructor below from the model class and cannot seem to notice the issue

class ConvLSTM(nn.Module):
def __init__(self, input_size, input_dim, hidden_dim, kernel_size, num_layers,
             batch_first=False, bias=True, return_all_layers=False):
    super(ConvLSTM, self).__init__()

    self._check_kernel_size_consistency(kernel_size)

    # Make sure that both `kernel_size` and `hidden_dim` are lists having len == num_layers
    kernel_size = self._extend_for_multilayer(kernel_size, num_layers)
    hidden_dim  = self._extend_for_multilayer(hidden_dim, num_layers)
    if not len(kernel_size) == len(hidden_dim) == num_layers:
        raise ValueError('Inconsistent list length.')

    self.height, self.width = input_size

    self.input_dim  = input_dim
    self.hidden_dim = hidden_dim
    self.kernel_size = kernel_size
    self.num_layers = num_layers
    self.batch_first = batch_first
    self.bias = bias
    self.return_all_layers = return_all_layers

    cell_list = []
    for i in range(0, self.num_layers):
        cur_input_dim = self.input_dim if i == 0 else self.hidden_dim[i-1]

        cell_list.append(ConvLSTMCell(input_size=(self.height, self.width),
                                      input_dim=cur_input_dim,
                                      hidden_dim=self.hidden_dim[i],
                                      kernel_size=self.kernel_size[i],
                                      bias=self.bias))

    self.cell_list = nn.ModuleList(cell_list)