fix image one sample bug (#156)

demo/mxnet/mxnet_demo.py

+import numpy as np
+import mxnet as mx
 import logging
 
 import mxnet as mx
@@ -22,6 +24,8 @@ with logger.mode("train"):
     # scalar0 is used to record scalar metrics while MXNet is training. We will record accuracy.
     # In the visualization, we can see the accuracy is increasing as more training steps happen.
     scalar0 = logger.scalar("scalars/scalar0")
+    image0 = logger.image("images/image0", 1)
+    histogram0 = logger.histogram("histogram/histogram0", num_buckets=100)
 
 # Record training steps
 cnt_step = 0
@@ -42,6 +46,19 @@ def add_scalar():
                 cnt_step += 1
     return _callback
 
+def add_image_histogram():
+    def _callback(iter_no, sym, arg, aux):
+        image0.start_sampling()
+        weight = arg['fullyconnected1_weight'].asnumpy()
+        shape = [100, 50]
+        data = weight.flatten()
+
+        image0.add_sample(shape, list(data))
+        histogram0.add_record(iter_no, list(data))
+
+        image0.finish_sampling()
+    return _callback
+
 
 # Start to build CNN in MXNet, train MNIST dataset. For more info, check MXNet's official website:
 # https://mxnet.incubator.apache.org/tutorials/python/mnist.html
@@ -81,7 +98,8 @@ lenet_model.fit(train_iter,
                 eval_metric='acc',
                 # integrate our customized callback method
                 batch_end_callback=[add_scalar()],
-                num_epoch=2)
+                epoch_end_callback=[add_image_histogram()],
+                num_epoch=5)
 
 test_iter = mx.io.NDArrayIter(mnist['test_data'], None, batch_size)
 prob = lenet_model.predict(test_iter)

visualdl/python/storage.py

@@ -140,7 +140,7 @@ class LogWriter(object):
         }
         return type2scalar[type](tag)
 
-    def image(self, tag, num_samples, step_cycle):
+    def image(self, tag, num_samples, step_cycle=1):
         """
         Create an image writer that used to write image data.
         """

visualdl/server/lib.py

 import pprint
 import re
+import sys
 import time
 import urllib
 from tempfile import NamedTemporaryFile
@@ -131,6 +132,7 @@ def get_invididual_image(storage, mode, tag, step_index, max_size=80):
     with storage.mode(mode) as reader:
         res = re.search(r".*/([0-9]+$)", tag)
         # remove suffix '/x'
+        offset = 0
         if res:
             offset = int(res.groups()[0])
             tag = tag[:tag.rfind('/')]
@@ -206,4 +208,6 @@ def retry(ntimes, function, time2sleep, *args, **kwargs):
         try:
             return function(*args, **kwargs)
         except:
+            error_info = '\n'.join(map(str, sys.exc_info()))
+            logger.error("Unexpected error: %s" % error_info)
             time.sleep(time2sleep)