From 7f4b100042febb028d6bcb36bf9869b0f49d95d5 Mon Sep 17 00:00:00 2001
From: allegroai <>
Date: Thu, 16 Apr 2020 16:40:14 +0300
Subject: [PATCH] Fix text encoding utf-8 and pr_curve broken in Tensorboard
 support

---
 trains/binding/frameworks/tensorflow_bind.py | 21 +++++++++++---------
 1 file changed, 12 insertions(+), 9 deletions(-)

diff --git a/trains/binding/frameworks/tensorflow_bind.py b/trains/binding/frameworks/tensorflow_bind.py
index fc15b263..d95a497b 100644
--- a/trains/binding/frameworks/tensorflow_bind.py
+++ b/trains/binding/frameworks/tensorflow_bind.py
@@ -418,18 +418,21 @@ class EventTrainsWriter(object):
     def _add_plot(self, tag, step, values, vdict):
         # noinspection PyBroadException
         try:
-            plot_values = np.frombuffer(base64.b64decode(values['tensorContent'].encode('utf-8')),
-                                        dtype=np.float32)
+            if values.get('floatVal'):
+                plot_values = np.array(values.get('floatVal'), dtype=np.float32)
+            else:
+                plot_values = np.frombuffer(base64.b64decode(values['tensorContent'].encode('utf-8')),
+                                            dtype=np.float32)
             plot_values = plot_values.reshape((int(values['tensorShape']['dim'][0]['size']),
                                                int(values['tensorShape']['dim'][1]['size'])))
             if 'metadata' in vdict:
                 if tag not in self._series_name_lookup:
-                    self._series_name_lookup[tag] = [(tag, vdict['metadata']['displayName'],
+                    self._series_name_lookup[tag] = [(tag, vdict['metadata'].get('displayName', ''),
                                                       vdict['metadata']['pluginData']['pluginName'])]
                 else:
                     # this should not happen, maybe it's another run, let increase the value
-                    self._series_name_lookup[tag] += [(tag + '_%d' % len(self._series_name_lookup[tag]) + 1,
-                                                       vdict['metadata']['displayName'],
+                    self._series_name_lookup[tag] += [(tag + '_%d' % (len(self._series_name_lookup[tag]) + 1),
+                                                       vdict['metadata'].get('displayName', ''),
                                                        vdict['metadata']['pluginData']['pluginName'])]
 
             tag, series, plugin_name = self._series_name_lookup.get(tag, [(tag, tag, '')])[-1]
@@ -439,7 +442,7 @@ class EventTrainsWriter(object):
                 #   width = 1.0 / (num_thresholds - 1)
                 #   thresholds = [0.0, 1*width, 2*width, 3*width, ..., 1.0]
                 num_thresholds = plot_values.shape[1]
-                width = 1.0 / (num_thresholds - 1)
+                width = 1.0 / num_thresholds
                 thresholds = np.arange(0.0, 1.0, width, dtype=plot_values.dtype)
                 data_points = ['TP     ', 'FP     ', 'TN     ', 'FN     ', 'Precision ', ' Recall']
                 series = [{'name': series, 'data': np.vstack((thresholds, plot_values[-2])).T,
@@ -561,13 +564,13 @@ class EventTrainsWriter(object):
                     self._add_audio(tag, step, values)
                 elif metric == 'tensor' and values.get('dtype') == 'DT_STRING':
                     # text, just print to console
-                    text = base64.b64decode('\n'.join(values['stringVal'])).decode('utf-8')
+                    text = base64.b64decode('\n'.join(values['stringVal'])).decode('utf-8', errors='replace')
                     self._logger.report_text(msg='SUMMARY LOG: {} {}'.format(tag, text), print_console=False)
                 elif metric == 'tensor' and values.get('dtype') == 'DT_FLOAT':
                     self._add_plot(tag, step, values, vdict)
                 else:
-                    LoggerRoot.get_base_logger(TensorflowBinding).debug('Event unsupported. tag = %s, vdict keys [%s]'
-                                                       % (tag, ', '.join(vdict.keys())))
+                    LoggerRoot.get_base_logger(TensorflowBinding).debug(
+                        'Event unsupported. tag = %s, vdict keys [%s]' % (tag, ', '.join(vdict.keys())))
                     continue
 
     def get_logdir(self):