fix periodic bug

examples/mnist_convnet.py

@@ -4,8 +4,6 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-from tensorflow.python.ops import control_flow_ops
-
 import numpy as np
 import os, sys
 import argparse
@@ -18,7 +16,6 @@
 from tensorpack.tfutils import *
 from tensorpack.callbacks import *
 from tensorpack.dataflow import *
-from IPython import embed; embed()
 
 """
 MNIST ConvNet example.

tensorpack/callbacks/validation_callback.py

@@ -11,23 +11,21 @@
 from ..utils.stat import *
 from ..tfutils import *
 from ..tfutils.summary import *
-from .base import PeriodicCallback, Callback, TestCallbackType
+from .base import Callback, TestCallbackType
 
 __all__ = ['ClassificationError', 'ValidationCallback', 'ValidationStatPrinter']
 
-class ValidationCallback(PeriodicCallback):
+class ValidationCallback(Callback):
     """
     Base class for validation callbacks.
     """
     type = TestCallbackType()
 
-    def __init__(self, ds, prefix, period=1):
+    def __init__(self, ds, prefix):
         """
         :param ds: validation dataset. must be a `DataFlow` instance.
         :param prefix: name to use for this validation.
-        :param period: period to perform validation.
         """
-        super(ValidationCallback, self).__init__(period)
         self.ds = ds
         self.prefix = prefix
 
@@ -63,23 +61,18 @@ def _run_validation(self):
                 yield (dp, outputs)
                 pbar.update()
 
-    @abstractmethod
-    def _trigger_periodic(self):
-        """ Implement the actual callback"""
-
 class ValidationStatPrinter(ValidationCallback):
     """
     Write stat and summary of some Op for a validation dataset.
     The result of the given Op must be a scalar, and will be averaged for all batches in the validaion set.
     """
-    def __init__(self, ds, names_to_print, prefix='validation', period=1):
+    def __init__(self, ds, names_to_print, prefix='validation'):
         """
         :param ds: validation dataset. must be a `DataFlow` instance.
         :param names_to_print: names of variables to print
         :param prefix: name to use for this validation.
-        :param period: period to perform validation.
         """
-        super(ValidationStatPrinter, self).__init__(ds, prefix, period)
+        super(ValidationStatPrinter, self).__init__(ds, prefix)
         self.names = names_to_print
 
     def _find_output_vars(self):
@@ -89,7 +82,7 @@ def _find_output_vars(self):
     def _get_output_vars(self):
         return self.vars_to_print
 
-    def _trigger_periodic(self):
+    def _trigger_epoch(self):
         stats = []
         for dp, outputs in self._run_validation():
             stats.append(outputs)
@@ -114,13 +107,12 @@ class ClassificationError(ValidationCallback):
     In theory, the result could be different from what produced by ValidationStatPrinter.
     """
     def __init__(self, ds, prefix='validation',
-                 period=1,
                  wrong_var_name='wrong:0'):
         """
         :param ds: a batched `DataFlow` instance
         :param wrong_var_name: name of the `wrong` variable
         """
-        super(ClassificationError, self).__init__(ds, prefix, period)
+        super(ClassificationError, self).__init__(ds, prefix)
         self.wrong_var_name = wrong_var_name
 
     def _find_output_vars(self):
@@ -129,7 +121,7 @@ def _find_output_vars(self):
     def _get_output_vars(self):
         return [self.wrong_var]
 
-    def _trigger_periodic(self):
+    def _trigger_epoch(self):
         err_stat = Accuracy()
         for dp, outputs in self._run_validation():
             batch_size = dp[0].shape[0]   # assume batched input