trigger rtfd (https://github.com/rtfd/readthedocs.org/issues/2640)

tensorpack/callbacks/stats.py

@@ -172,7 +172,7 @@ class SendStat(Triggerable):
             stats = [stats]
         self.stats = stats
 
-    def _trigger_epoch(self):
+    def _trigger(self):
         holder = self.trainer.stat_holder
         v = {k: holder.get_stat_now(k) for k in self.stats}
         cmd = self.command.format(**v)

tensorpack/tfutils/gradproc.py

@@ -12,7 +12,7 @@ from ..utils import logger
 from .symbolic_functions import rms
 from .summary import add_moving_summary
 
-__all__ = ['GradientProcessor', 'GlobalNormClip', 'MapGradient', 'SummaryGradient', 'CheckGradient',
+__all__ = ['GradientProcessor', 'FilterNoneGrad', 'GlobalNormClip', 'MapGradient', 'SummaryGradient', 'CheckGradient',
            'ScaleGradient', 'apply_grad_processors']
 
 
@@ -24,12 +24,8 @@ def apply_grad_processors(grads, gradprocs):
     Returns:
         list: list of (grad, var) went through the processors.
     """
-    g = []
-    for grad, var in grads:
-        if grad is None:
-            logger.warn("No Gradient w.r.t {}".format(var.op.name))
-        else:
-            g.append((grad, var))
+    gradprocs.insert(0, FilterNoneGrad())
+    g = grads
     for proc in gradprocs:
         g = proc.process(g)
     return g
@@ -58,6 +54,21 @@ class GradientProcessor(object):
         pass
 
 
+class FilterNoneGrad(GradientProcessor):
+    """
+    Skip the update and print a warning (instead of crashing),
+    when the gradient of certain variable is None.
+    """
+    def _process(self, grads):
+        g = []
+        for grad, var in grads:
+            if grad is None:
+                logger.warn("No Gradient w.r.t {}".format(var.op.name))
+            else:
+                g.append((grad, var))
+        return g
+
+
 class GlobalNormClip(GradientProcessor):
     """ Clip by global norm.
         The global norm is the sum of norm for **all** gradients.