Merge pull request #143 from customprogrammingsolutions/bugfix-assert…

…s-as-validation

[MRG] Raise exceptions not just asserts

persephone/corpus.py

@@ -473,10 +473,13 @@ def ensure_no_set_overlap(self) -> None:
 
         if train & valid:
             logger.warning("train and valid have overlapping items: {}".format(train & valid))
+            raise PersephoneException("train and valid have overlapping items: {}".format(train & valid))
         if train & test:
             logger.warning("train and test have overlapping items: {}".format(train & test))
+            raise PersephoneException("train and test have overlapping items: {}".format(train & test))
         if valid & test:
             logger.warning("valid and test have overlapping items: {}".format(valid & test))
+            raise PersephoneException("valid and test have overlapping items: {}".format(valid & test))
 
     def pickle(self):
         """ Pickles the Corpus object in a file in tgt_dir. """

persephone/corpus_reader.py

@@ -57,8 +57,10 @@ def __init__(self, corpus, num_train=None, batch_size=None, max_samples=None, ra
         if batch_size:
             self.batch_size = batch_size
             if num_train % batch_size != 0:
-                raise PersephoneException("""Number of training examples %d not divisible
-                                   by batch size %d.""" % (num_train, batch_size))
+                logger.error("Number of training examples {} not divisible"
+                             " by batch size {}.".format(num_train, batch_size))
+                raise PersephoneException("Number of training examples {} not divisible"
+                                          " by batch size {}.".format(num_train, batch_size))
         else:
             # Dynamically change batch size based on number of training
             # examples.
@@ -70,6 +72,11 @@ def __init__(self, corpus, num_train=None, batch_size=None, max_samples=None, ra
             # For now we hope that training numbers are powers of two or
             # something... If not, crash before anything else happens.
             assert num_train % self.batch_size == 0
+            if num_train % self.batch_size != 0:
+                logger.error("Number of training examples {} not divisible"
+                             " by batch size {}.".format(num_train, self.batch_size))
+                raise PersephoneException("Number of training examples {} not divisible"
+                                          " by batch size {}.".format(num_train, batch_size))
 
         random.seed(rand_seed)
 

persephone/utils.py

@@ -60,6 +60,10 @@ def zero_pad(matrix, to_length):
     x is of length to_length."""
 
     assert matrix.shape[0] <= to_length
+    if not matrix.shape[0] <= to_length:
+        logger.error("zero_pad cannot be performed on matrix with shape {}"
+                     " to length {}".format(matrix.shape[0], to_length))
+        raise ValueError
     result = np.zeros((to_length,) + matrix.shape[1:])
     result[:matrix.shape[0]] = matrix
     return result