diff --git a/utils/__init__.py b/utils/__init__.py
index af5f185..e71c201 100644
--- a/utils/__init__.py
+++ b/utils/__init__.py
@@ -1,12 +1,7 @@
 from .config import *
 from .normalizer import *
 from .misc import *
-
-try:
-    from .tf_logger import Logger
-except:
-    from .vanilla_logger import Logger
-
+from .tf_logger import Logger
 import logging
 logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s: %(message)s')
 logger = logging.getLogger('MAIN')
diff --git a/utils/tf_logger.py b/utils/tf_logger.py
index 5d9b506..600dd0a 100644
--- a/utils/tf_logger.py
+++ b/utils/tf_logger.py
@@ -1,20 +1,14 @@
-# Adapted from https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/04-utils/tensorboard/logger.py
-# Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514
-import tensorflow as tf
-import numpy as np
-import scipy.misc
-import logging
-
-try:
-    from StringIO import StringIO  # Python 2.7
-except ImportError:
-    from io import BytesIO  # Python 3.x
+#######################################################################
+# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com)    #
+# Permission given to modify the code as long as you keep this        #
+# declaration at the top                                              #
+#######################################################################
 
+from tensorboardX import SummaryWriter
 
 class Logger(object):
     def __init__(self, log_dir, vanilla_logger, skip=False):
-        """Create a summary writer logging to log_dir."""
-        self.writer = tf.summary.FileWriter(log_dir)
+        self.writer = SummaryWriter(log_dir)
         self.info = vanilla_logger.info
         self.debug = vanilla_logger.debug
         self.warning = vanilla_logger.warning
@@ -23,61 +17,9 @@ class Logger(object):
     def scalar_summary(self, tag, value, step):
         if self.skip:
             return
-        """Log a scalar variable."""
-        summary = tf.Summary(value=[tf.Summary.Value(tag=tag, simple_value=value)])
-        self.writer.add_summary(summary, step)
+        self.writer.add_scalar(tag, value, step)
 
-    def image_summary(self, tag, images, step):
+    def histo_summary(self, tag, values, step):
         if self.skip:
             return
-        """Log a list of images."""
-
-        img_summaries = []
-        for i, img in enumerate(images):
-            # Write the image to a string
-            try:
-                s = StringIO()
-            except:
-                s = BytesIO()
-            scipy.misc.toimage(img).save(s, format="png")
-
-            # Create an Image object
-            img_sum = tf.Summary.Image(encoded_image_string=s.getvalue(),
-                                       height=img.shape[0],
-                                       width=img.shape[1])
-            # Create a Summary value
-            img_summaries.append(tf.Summary.Value(tag='%s/%d' % (tag, i), image=img_sum))
-
-        # Create and write Summary
-        summary = tf.Summary(value=img_summaries)
-        self.writer.add_summary(summary, step)
-
-    def histo_summary(self, tag, values, step, bins=1000):
-        if self.skip:
-            return
-        """Log a histogram of the tensor of values."""
-
-        # Create a histogram using numpy
-        counts, bin_edges = np.histogram(values, bins=bins)
-
-        # Fill the fields of the histogram proto
-        hist = tf.HistogramProto()
-        hist.min = float(np.min(values))
-        hist.max = float(np.max(values))
-        hist.num = int(np.prod(values.shape))
-        hist.sum = float(np.sum(values))
-        hist.sum_squares = float(np.sum(values ** 2))
-
-        # Drop the start of the first bin
-        bin_edges = bin_edges[1:]
-
-        # Add bin edges and counts
-        for edge in bin_edges:
-            hist.bucket_limit.append(edge)
-        for c in counts:
-            hist.bucket.append(c)
-
-        # Create and write Summary
-        summary = tf.Summary(value=[tf.Summary.Value(tag=tag, histo=hist)])
-        self.writer.add_summary(summary, step)
-        self.writer.flush()
\ No newline at end of file
+        self.writer.add_histogram(tag, values, step)
\ No newline at end of file
diff --git a/utils/vanilla_logger.py b/utils/vanilla_logger.py
deleted file mode 100644
index a21e785..0000000
--- a/utils/vanilla_logger.py
+++ /dev/null
@@ -1,22 +0,0 @@
-import numpy as np
-import logging
-
-class Logger(object):
-    def __init__(self, log_dir, vanilla_logger, skip=False):
-        """Create a summary writer logging to log_dir."""
-        self.info = vanilla_logger.info
-        self.debug = vanilla_logger.debug
-        self.warning = vanilla_logger.warning
-        self.skip = skip
-
-    def scalar_summary(self, tag, value, step):
-        if self.skip:
-            return
-
-    def image_summary(self, tag, images, step):
-        if self.skip:
-            return
-
-    def histo_summary(self, tag, values, step, bins=1000):
-        if self.skip:
-            return