How can I convert mutiple arrays with different length to 2d-tensor

[Eta_C]

Nested list of variable length to a tensor

This code might work: target = [[[1,2,3], [2,4,5,6]], [[1,2,3], [2,4,5,6], [2,4,6,7,8]]] max_cols = max([len(row) for batch in target for row in batch]) max_rows = max([len(batch) for batch in target]) padded = [batch + [[0] * (max_cols)] * (max_rows - len(batch)) for batch in target] padded = torch.tensor([row + [0] * (max_length - len(row)) for batch in padded for row in batch]) padded = padded.view(-1, max_rows, max_cols)