Fix incorrect doc.

This commit is contained in:
Fangjun Kuang 2021-11-15 12:18:16 +08:00
parent e3d7f21372
commit 57b9c8868b

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@ -39,8 +39,8 @@ The following shows the steps:
(iv) Use "b" as "src" and its shifted version as "tgt".
We can get another likelihood value, denoted as "ab_other"
So for the path pair (a, b), (a, c), we can get the following log-likelihood
values, viewed as two tensors:
So for the path pair (a, b), (a, c), (b, a), (b, c), (c, a), and (c, b),
we can get the following log-likelihood values, viewed as two tensors:
self = [ab_self, ac_self, ba_self, bc_self, ca_self, cb_self]
@ -219,7 +219,7 @@ def make_repeat_map(row_splits: torch.Tensor):
>>> row_splits = torch.tensor([0, 3, 5], dtype=torch.int32)
>>> make_repeat_map(row_splits)
tensor([0, 1, 2, 0, 1, 2, 0, 1, 2, 3, 4, 3, 4], dtype=torch.int32)
tensor([1, 2, 0, 2, 0, 1, 4, 3], dtype=torch.int32)
"""
device = row_splits.device
@ -250,12 +250,11 @@ def make_repeat_map(row_splits: torch.Tensor):
def make_repeat(tokens: k2.RaggedTensor) -> k2.RaggedTensor:
"""Repeat the number of paths of an utterance to the number that
equals to the number of paths in the utterance.
"""Repeat paths in an utterance.
For instance, if an utterance contains 3 paths: [path1 path2 path3],
after repeating, this utterance will contain 9 paths:
[path1 path2 path3] [path1 path2 path3] [path1 path2 path3]
after repeating, this utterance will contain 6 paths:
[path2 path3] [path1 path3] [path1 path2]
>>> tokens = k2.RaggedTensor([ [[1, 2, 3], [4, 5], [9]], [[5, 8], [10, 1]] ])
>>> tokens.to_str_simple()