From c1c67d641211b4239bd7db39a6f2e5ee2b9fa850 Mon Sep 17 00:00:00 2001
From: lvmingfu <lvmingfu@huawei.com>
Date: Mon, 10 May 2021 17:33:20 +0800
Subject: [PATCH] fix error link in nn/lstm.py for master

---
 mindspore/nn/layer/lstm.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mindspore/nn/layer/lstm.py b/mindspore/nn/layer/lstm.py
index bc4cf121a65..f8a06c0f5a0 100755
--- a/mindspore/nn/layer/lstm.py
+++ b/mindspore/nn/layer/lstm.py
@@ -80,7 +80,7 @@ class LSTM(Cell):
     Details can be found in paper `LONG SHORT-TERM MEMORY
     <https://www.bioinf.jku.at/publications/older/2604.pdf>`_ and
     `Long Short-Term Memory Recurrent Neural Network Architectures for Large Scale Acoustic Modeling
-    <https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/43905.pdf>`_.
+    <https://static.googleusercontent.com/media/research.google.com/zh-CN/pubs/archive/43905.pdf>`_.
 
     Args:
         input_size (int): Number of features of input.
@@ -312,7 +312,7 @@ class LSTMCell(Cell):
     Details can be found in paper `LONG SHORT-TERM MEMORY
     <https://www.bioinf.jku.at/publications/older/2604.pdf>`_ and
     `Long Short-Term Memory Recurrent Neural Network Architectures for Large Scale Acoustic Modeling
-    <https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/43905.pdf>`_.
+    <https://static.googleusercontent.com/media/research.google.com/zh-CN/pubs/archive/43905.pdf>`_.
 
     LSTMCell is a single-layer RNN, you can achieve multi-layer RNN by stacking LSTMCell.