From e5150df665a58a898c4a3438e7b4ae870baeaa11 Mon Sep 17 00:00:00 2001
From: foreverseer <1923212756@qq.com>
Date: Tue, 22 Dec 2020 14:11:24 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E4=BA=86writer=E9=87=8C?=
 =?UTF-8?q?=E9=9D=A2=E6=89=80=E6=9C=89=E6=B3=A8=E9=87=8Anumpy.ndarray?=
 =?UTF-8?q?=E5=8F=98=E4=B8=BAnp.ndarray=20(#877)?=
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lgtm
---
 visualdl/writer/writer.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/visualdl/writer/writer.py b/visualdl/writer/writer.py
index 971293661..9aceabebf 100644
--- a/visualdl/writer/writer.py
+++ b/visualdl/writer/writer.py
@@ -168,7 +168,7 @@ def add_image(self, tag, img, step, walltime=None, dataformats="HWC"):
 
         Args:
             tag (string): Data identifier
-            img (numpy.ndarray): Image represented by a numpy.array
+            img (np.ndarray): Image represented by a numpy.array
             step (int): Step of image
             walltime (int): Wall time of image
             dataformats (string): Format of image
@@ -266,7 +266,7 @@ def add_audio(self,
 
         Args:
             tag (string): Data identifier
-            audio (numpy.ndarray or list): audio represented by a numpy.array
+            audio (np.ndarray or list): audio represented by a numpy.array
             step (int): Step of audio
             sample_rate (int): Sample rate of audio
             walltime (int): Wall time of audio
@@ -312,7 +312,7 @@ def add_histogram(self,
 
         Args:
             tag (string): Data identifier
-            value (numpy.ndarray or list): value represented by a numpy.array or list
+            value (np.ndarray or list): value represented by a numpy.array or list
             step (int): Step of histogram
             walltime (int): Wall time of audio
             buckets (int): Number of buckets, default is 10
@@ -349,8 +349,8 @@ def add_pr_curve(self,
 
         Args:
             tag (string): Data identifier
-            labels (numpy.ndarray or list): Binary labels for each element.
-            predictions (numpy.ndarray or list): The probability that an element
+            labels (np.ndarray or list): Binary labels for each element.
+            predictions (np.ndarray or list): The probability that an element
                 be classified as true.
             step (int): Step of pr curve.
             weights (float): Multiple of data to display on the curve.