Update forced_align document (#3357)

Summary:
- Fix latex formula rendering issue
- Add `devices` and `properties` tags
- Fix grammar

Pull Request resolved: https://github.com/pytorch/audio/pull/3357

Reviewed By: mthrok

Differential Revision: D46068633

Pulled By: nateanl

fbshipit-source-id: 80cb84508396fbcaf81c068228d46a24bb63b975

torchaudio/functional/functional.py

@@ -2610,25 +2610,33 @@ def forced_align(
 ) -> Tuple[torch.Tensor, torch.Tensor]:
     """Computes forced alignment given the emissions from a CTC-trained model and a target label.
 
+    .. devices:: CPU CUDA
+
+    .. properties:: TorchScript
+
     Args:
         log_probs (torch.Tensor): log probability of CTC emission output.
-            Tensor with dimensions `(T, C)`. where `T` is the input length,
-            vocabulary is the number of characters in alphabet including blank.
-        targets (torch.Tensor): Target sequence. Tensor with dimension `(L,)`,
+            Tensor of shape `(T, C)`. where `T` is the input length,
+            `C` is the number of characters in alphabet including blank.
+        targets (torch.Tensor): Target sequence. Tensor of shape `(L,)`,
             where `L` is the target length.
-        input_lengths (torch.Tensor): Lengths of the inputs (max value must each be <= `T`). Tensor with dimension `()`.
-        target_lengths (torch.Tensor): Lengths of the targets. Tensor with dimension `()`.
+        input_lengths (torch.Tensor): Lengths of the inputs (max value must each be <= `T`). 0-D Tensor (scalar).
+        target_lengths (torch.Tensor): Lengths of the targets. 0-D Tensor (scalar).
         blank_id (int, optional): The index of blank symbol in CTC emission. (Default: 0)
 
     Returns:
         Tuple(torch.Tensor, torch.Tensor):
-            torch.Tensor: Label for each time step in the alignemnt path computed using forced alignment.
+            torch.Tensor: Label for each time step in the alignment path computed using forced alignment.
+
             torch.Tensor: Log probability scores of the labels for each time step.
 
     Note:
         The sequence length of `log_probs` must satisfy:
+
+
         .. math::
-            L_{\\text{log_probs}} \\ge L_{\\text{label}} + N_{\\text{repeat}}
+            L_{\\text{log\_probs}} \ge L_{\\text{label}} + N_{\\text{repeat}}
+
         where :math:`N_{\\text{repeat}}` is the number of consecutively repeated tokens.
         For example, in str `"aabbc"`, the number of repeats are `2`.
     """