add htmls

.tools/build_docker.sh

@@ -67,6 +67,7 @@ RUN ${update_mirror_cmd}
     apt-get -y install gcc && \
     apt-get -y clean && \
     localedef -f UTF-8 -i en_US en_US.UTF-8 && \
+    pip install --upgrade pip && \
     pip install -U pillow matplotlib jupyter numpy requests scipy
 
 #convert md to ipynb

01.fit_a_line/README.en.md

@@ -162,6 +162,23 @@ feeding={'x': 0, 'y': 1}
 
 Moreover, an event handler is provided to print the training progress:
 
+```python
+lists = []
+
+def event_handler(event):
+    if isinstance(event, paddle.event.EndIteration):
+        if event.batch_id % 100 == 0:
+            print "Pass %d, Batch %d, Cost %f, %s" % (
+                event.pass_id, event.batch_id, event.cost, event.metrics)
+    if isinstance(event, paddle.event.EndPass):
+        result = trainer.test(reader=paddle.batch(
+            paddle.dataset.mnist.test(), batch_size=128))
+        print "Test with Pass %d, Cost %f, %s\n" % (
+            event.pass_id, result.cost, result.metrics)
+        lists.append((event.pass_id, result.cost,
+                      result.metrics['classification_error_evaluator']))
+```
+
 ```python
 # event_handler to print training and testing info
 from paddle.v2.plot import Ploter
@@ -172,7 +189,7 @@ plot_cost = Ploter(train_title, test_title)
 
 step = 0
 
-def event_handler(event):
+def event_handler_plot(event):
     global step
     if isinstance(event, paddle.event.EndIteration):
         if step % 10 == 0:  # every 10 batches, record a train cost
@@ -200,7 +217,7 @@ trainer.train(
             uci_housing.train(), buf_size=500),
         batch_size=2),
     feeding=feeding,
-    event_handler=event_handler,
+    event_handler=event_handler_plot,
     num_passes=30)
 ```
 

01.fit_a_line/README.md

@@ -157,6 +157,23 @@ feeding={'x': 0, 'y': 1}
 
 此外，我们还可以提供一个 event handler，来打印训练的进度：
 
+```python
+lists = []
+
+def event_handler(event):
+    if isinstance(event, paddle.event.EndIteration):
+        if event.batch_id % 100 == 0:
+            print "Pass %d, Batch %d, Cost %f, %s" % (
+                event.pass_id, event.batch_id, event.cost, event.metrics)
+    if isinstance(event, paddle.event.EndPass):
+        result = trainer.test(reader=paddle.batch(
+            paddle.dataset.mnist.test(), batch_size=128))
+        print "Test with Pass %d, Cost %f, %s\n" % (
+            event.pass_id, result.cost, result.metrics)
+        lists.append((event.pass_id, result.cost,
+                      result.metrics['classification_error_evaluator']))
+```
+
 ```python
 # event_handler to print training and testing info
 from paddle.v2.plot import Ploter
@@ -167,7 +184,7 @@ cost_ploter = Ploter(train_title, test_title)
 
 step = 0
 
-def event_handler(event):
+def event_handler_plot(event):
     global step
     if isinstance(event, paddle.event.EndIteration):
         if step % 10 == 0:  # every 10 batches, record a train cost
@@ -195,7 +212,7 @@ trainer.train(
             uci_housing.train(), buf_size=500),
         batch_size=2),
     feeding=feeding,
-    event_handler=event_handler,
+    event_handler=event_handler_plot,
     num_passes=30)
 ```
 

01.fit_a_line/index.en.html

@@ -204,6 +204,23 @@ feeding={'x': 0, 'y': 1}
 
 Moreover, an event handler is provided to print the training progress:
 
+```python
+lists = []
+
+def event_handler(event):
+    if isinstance(event, paddle.event.EndIteration):
+        if event.batch_id % 100 == 0:
+            print "Pass %d, Batch %d, Cost %f, %s" % (
+                event.pass_id, event.batch_id, event.cost, event.metrics)
+    if isinstance(event, paddle.event.EndPass):
+        result = trainer.test(reader=paddle.batch(
+            paddle.dataset.mnist.test(), batch_size=128))
+        print "Test with Pass %d, Cost %f, %s\n" % (
+            event.pass_id, result.cost, result.metrics)
+        lists.append((event.pass_id, result.cost,
+                      result.metrics['classification_error_evaluator']))
+```
+
 ```python
 # event_handler to print training and testing info
 from paddle.v2.plot import Ploter
@@ -214,7 +231,7 @@ plot_cost = Ploter(train_title, test_title)
 
 step = 0
 
-def event_handler(event):
+def event_handler_plot(event):
     global step
     if isinstance(event, paddle.event.EndIteration):
         if step % 10 == 0:  # every 10 batches, record a train cost
@@ -242,7 +259,7 @@ trainer.train(
             uci_housing.train(), buf_size=500),
         batch_size=2),
     feeding=feeding,
-    event_handler=event_handler,
+    event_handler=event_handler_plot,
     num_passes=30)
 ```
 

01.fit_a_line/index.html

@@ -199,6 +199,23 @@ feeding={'x': 0, 'y': 1}
 
 此外，我们还可以提供一个 event handler，来打印训练的进度：
 
+```python
+lists = []
+
+def event_handler(event):
+    if isinstance(event, paddle.event.EndIteration):
+        if event.batch_id % 100 == 0:
+            print "Pass %d, Batch %d, Cost %f, %s" % (
+                event.pass_id, event.batch_id, event.cost, event.metrics)
+    if isinstance(event, paddle.event.EndPass):
+        result = trainer.test(reader=paddle.batch(
+            paddle.dataset.mnist.test(), batch_size=128))
+        print "Test with Pass %d, Cost %f, %s\n" % (
+            event.pass_id, result.cost, result.metrics)
+        lists.append((event.pass_id, result.cost,
+                      result.metrics['classification_error_evaluator']))
+```
+
 ```python
 # event_handler to print training and testing info
 from paddle.v2.plot import Ploter
@@ -209,7 +226,7 @@ cost_ploter = Ploter(train_title, test_title)
 
 step = 0
 
-def event_handler(event):
+def event_handler_plot(event):
     global step
     if isinstance(event, paddle.event.EndIteration):
         if step % 10 == 0:  # every 10 batches, record a train cost
@@ -237,7 +254,7 @@ trainer.train(
             uci_housing.train(), buf_size=500),
         batch_size=2),
     feeding=feeding,
-    event_handler=event_handler,
+    event_handler=event_handler_plot,
     num_passes=30)
 ```