未验证 提交 78738d6c 编写于 作者: W whs 提交者: GitHub

Fix comments of ctc_greedy_decoder. (#14679)

test=develop
上级 1b9753d1
......@@ -4250,8 +4250,15 @@ def ctc_greedy_decoder(input, blank, name=None):
[0.5, 0.1, 0.3, 0.1]]
input.lod = [[4, 4]]
Computation:
Then:
step1: Apply argmax to first input sequence which is input.data[0:4]. Then we get:
[[0], [2], [1], [0]]
step2: merge repeated tokens and remove blank which is 0. Then we get first output sequence:
[[2], [1]]
Finally:
output.data = [[2],
[1],
......@@ -4259,6 +4266,7 @@ def ctc_greedy_decoder(input, blank, name=None):
output.lod = [[2, 1]]
Args:
input(Variable): (LoDTensor<float>), the probabilities of
......@@ -4273,8 +4281,10 @@ def ctc_greedy_decoder(input, blank, name=None):
name (str): The name of this layer. It is optional.
Returns:
Variable: CTC greedy decode result. If all the sequences in result were
empty, the result LoDTensor will be [-1] with LoD [[]] and dims [1, 1].
Variable: CTC greedy decode result which is a 2-D tensor with shape [Lp, 1].
'Lp' is the sum if all output sequences' length. If all the sequences
in result were empty, the result LoDTensor will be [-1] with
LoD [[]] and dims [1, 1].
Examples:
.. code-block:: python
......
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