summary writer print all scalar by default

example_mnist.py

@@ -109,7 +109,7 @@ def get_config():
         dataset=dataset_train,
         optimizer=tf.train.AdamOptimizer(lr),
         callbacks=Callbacks([
-            SummaryWriter(print_tag=['train_cost', 'train_error']),
+            SummaryWriter(),
             PeriodicSaver(),
             ValidationError(dataset_test, prefix='validation'),
         ]),

tensorpack/callbacks/common.py

@@ -32,8 +32,9 @@ class PeriodicSaver(PeriodicCallback):
 
 class SummaryWriter(Callback):
     def __init__(self, print_tag=None):
+        """ if None, print all scalar summary"""
         self.log_dir = logger.LOG_DIR
-        self.print_tag = print_tag if print_tag else ['train_cost']
+        self.print_tag = print_tag
 
     def _before_train(self):
         self.writer = tf.train.SummaryWriter(
@@ -44,22 +45,20 @@ class SummaryWriter(Callback):
 
     def _trigger_epoch(self):
         self.epoch_num += 1
-        # check if there is any summary
+        # check if there is any summary to write
         if self.summary_op is None:
             return
         summary_str = self.summary_op.eval()
         summary = tf.Summary.FromString(summary_str)
         printed_tag = set()
         for val in summary.value:
-            #print val.tag
-            val.tag = re.sub('tower[0-9]*/', '', val.tag)
-            if val.tag in self.print_tag:
-                assert val.WhichOneof('value') == 'simple_value', \
-                    'Cannot print summary {}: not a simple_value summary!'.format(val.tag)
-                logger.info('{}: {:.4f}'.format(val.tag, val.simple_value))
-                printed_tag.add(val.tag)
+            if val.WhichOneof('value') == 'simple_value':
+                val.tag = re.sub('tower[0-9]*/', '', val.tag)
+                if self.print_tag is None or val.tag in self.print_tag:
+                    logger.info('{}: {:.4f}'.format(val.tag, val.simple_value))
+                    printed_tag.add(val.tag)
         self.writer.add_summary(summary, get_global_step())
-        if self.epoch_num == 1:
+        if self.print_tag is not None and self.epoch_num == 1:
             if len(printed_tag) != len(self.print_tag):
                 logger.warn("Tags to print not found in Summary Writer: {}".format(
                     ", ".join([k for k in self.print_tag if k not in printed_tag])))

tensorpack/train.py

@@ -72,6 +72,7 @@ def average_grads(tower_grads):
 def summary_grads(grads):
     for grad, var in grads:
         if grad:
+            # TODO also summary RMS and print
             tf.histogram_summary(var.op.name + '/gradients', grad)
 
 def check_grads(grads):