add plot cost in v2 api

python/paddle/v2/__init__.py

@@ -29,11 +29,12 @@ import inference
 import networks
 import py_paddle.swig_paddle as api
 import minibatch
+import plot_curve
 
 __all__ = [
     'optimizer', 'layer', 'activation', 'parameters', 'init', 'trainer',
     'event', 'data_type', 'attr', 'pooling', 'data_feeder', 'dataset', 'reader',
-    'topology', 'networks', 'infer'
+    'topology', 'networks', 'infer', 'plot_curve'
 ]
 
 

python/paddle/v2/plot_curve.py

+import matplotlib.pyplot as plt
+from IPython import display
+
+
+class PlotCost(object):
+    """
+    append train and test cost in event_handle and then call plot.
+    """
+    def __init__(self):
+        self.train_costs = ([], [])
+        self.test_costs = ([], [])
+
+    def plot(self):
+        plt.plot(*self.train_costs)
+        plt.plot(*self.test_costs)
+        title = []
+        if len(self.train_costs[0]) > 0:
+            title.append('Train Cost')
+        if len(self.test_costs[0]) > 0:
+            title.append('Test Cost')
+        plt.legend(title, loc='upper left')
+        display.clear_output(wait=True)
+        display.display(plt.gcf())
+        plt.gcf().clear()
+
+    def append_train_cost(self, step, cost):
+        self.train_costs[0].append(step)
+        self.train_costs[1].append(cost)
+
+    def append_test_cost(self, step, cost):
+        self.test_costs[0].append(step)
+        self.test_costs[1].append(cost)
+
+    def reset(self):
+        self.train_costs = ([], [])
+        self.test_costs = ([], [])