Add mask_tensor util

Utility to create a boolean tensor mask on the tensors device
based on sequence lengths.

i6_models/util/mask.py

@@ -0,0 +1,16 @@
+import torch
+
+
+def mask_tensor(tensor: torch.Tensor, seq_len: torch.Tensor) -> torch.Tensor:
+    """
+    Create a "positive" mask for a tensor (boolean true means position is used)
+    on the same device as the tensor.
+
+    :param tensor: [B,T,....]
+    :param seq_len: [B]
+    :return: Mask of [B,T]
+    """
+    seq_len = seq_len.to(device=tensor.device)
+    r = torch.arange(tensor.shape[1], device=tensor.device)  # [T]
+    seq_mask = torch.less(r[None, :], seq_len[:, None])  # broadcast to [B,T]
+    return seq_mask