diff --git a/01.fit_a_line/index.cn.html b/01.fit_a_line/index.cn.html
index c6ad4e241ecfe804d1a9f0c4d852511a25e2bc7b..4d33d002cf89d99a5dac770bb2e1d60b8f88e9bb 100644
--- a/01.fit_a_line/index.cn.html
+++ b/01.fit_a_line/index.cn.html
@@ -219,80 +219,6 @@ PaddlePaddle提供了读取数据者发生器机制来读取训练数据。读
 feed_order=['x', 'y']
 ```
 
-以及一个绘画器来进行绘制：
-
-```python
-import six
-import os
-
-
-class PlotData(object):
-    def __init__(self):
-        self.step = []
-        self.value = []
-
-    def append(self, step, value):
-        self.step.append(step)
-        self.value.append(value)
-
-    def reset(self):
-        self.step = []
-        self.value = []
-
-
-class Ploter(object):
-    def __init__(self, *args):
-        self.__args__ = args
-        self.__plot_data__ = {}
-        for title in args:
-            self.__plot_data__[title] = PlotData()
-        # demo in notebooks will use Ploter to plot figure, but when we convert
-        # the ipydb to py file for testing, the import of matplotlib will make the
-        # script crash. So we can use `export DISABLE_PLOT=True` to disable import
-        # these libs
-        self.__disable_plot__ = os.environ.get("DISABLE_PLOT")
-        if not self.__plot_is_disabled__():
-            import matplotlib.pyplot as plt
-            from IPython import display
-            self.plt = plt
-            self.display = display
-
-    def __plot_is_disabled__(self):
-        return self.__disable_plot__ == "True"
-
-    def append(self, title, step, value):
-        assert isinstance(title, six.string_types)
-        assert title in self.__plot_data__
-        data = self.__plot_data__[title]
-        assert isinstance(data, PlotData)
-        data.append(step, value)
-
-    def plot(self, path=None):
-        if self.__plot_is_disabled__():
-            return
-
-        titles = []
-        for title in self.__args__:
-            data = self.__plot_data__[title]
-            assert isinstance(data, PlotData)
-            if len(data.step) > 0:
-                titles.append(title)
-                self.plt.plot(data.step, data.value)
-        self.plt.legend(titles, loc='upper left')
-        if path is None:
-            self.display.clear_output(wait=True)
-            self.display.display(self.plt.gcf())
-        else:
-            self.plt.savefig(path)
-        self.plt.gcf().clear()
-
-    def reset(self):
-        for key in self.__plot_data__:
-            data = self.__plot_data__[key]
-            assert isinstance(data, PlotData)
-            data.reset()
-```
-
 除此之外，可以定义一个事件响应器来处理类似`打印训练进程`的事件：
 
 ```python
@@ -300,6 +226,8 @@ class Ploter(object):
 params_dirname = "fit_a_line.inference.model"
 
 # Plot data
+from paddle.utils import Ploter
+
 train_title = "Train cost"
 test_title = "Test cost"
 plot_cost = Ploter(train_title, test_title)
diff --git a/01.fit_a_line/index.html b/01.fit_a_line/index.html
index d17a3c2106a30c3f210067a7dd503eea17a03c33..587c72893e44b7a2895fb391ffbfbdc1fb66d387 100644
--- a/01.fit_a_line/index.html
+++ b/01.fit_a_line/index.html
@@ -238,80 +238,6 @@ for loading the training data. A reader may return multiple columns, and we need
 feed_order=['x', 'y']
 ```
 
-And a ploter to plot metrics:
-
-```python
-import six
-import os
-
-
-class PlotData(object):
-    def __init__(self):
-        self.step = []
-        self.value = []
-
-    def append(self, step, value):
-        self.step.append(step)
-        self.value.append(value)
-
-    def reset(self):
-        self.step = []
-        self.value = []
-
-
-class Ploter(object):
-    def __init__(self, *args):
-        self.__args__ = args
-        self.__plot_data__ = {}
-        for title in args:
-            self.__plot_data__[title] = PlotData()
-        # demo in notebooks will use Ploter to plot figure, but when we convert
-        # the ipydb to py file for testing, the import of matplotlib will make the
-        # script crash. So we can use `export DISABLE_PLOT=True` to disable import
-        # these libs
-        self.__disable_plot__ = os.environ.get("DISABLE_PLOT")
-        if not self.__plot_is_disabled__():
-            import matplotlib.pyplot as plt
-            from IPython import display
-            self.plt = plt
-            self.display = display
-
-    def __plot_is_disabled__(self):
-        return self.__disable_plot__ == "True"
-
-    def append(self, title, step, value):
-        assert isinstance(title, six.string_types)
-        assert title in self.__plot_data__
-        data = self.__plot_data__[title]
-        assert isinstance(data, PlotData)
-        data.append(step, value)
-
-    def plot(self, path=None):
-        if self.__plot_is_disabled__():
-            return
-
-        titles = []
-        for title in self.__args__:
-            data = self.__plot_data__[title]
-            assert isinstance(data, PlotData)
-            if len(data.step) > 0:
-                titles.append(title)
-                self.plt.plot(data.step, data.value)
-        self.plt.legend(titles, loc='upper left')
-        if path is None:
-            self.display.clear_output(wait=True)
-            self.display.display(self.plt.gcf())
-        else:
-            self.plt.savefig(path)
-        self.plt.gcf().clear()
-
-    def reset(self):
-        for key in self.__plot_data__:
-            data = self.__plot_data__[key]
-            assert isinstance(data, PlotData)
-            data.reset()
-```
-
 Moreover, an event handler is provided to print the training progress:
 
 ```python
@@ -319,6 +245,8 @@ Moreover, an event handler is provided to print the training progress:
 params_dirname = "fit_a_line.inference.model"
 
 # Plot data
+from paddle.utils import Ploter
+
 train_title = "Train cost"
 test_title = "Test cost"
 plot_cost = Ploter(train_title, test_title)