custom error and warning messages

bin/wiki_entity_linking/training_set_creator.py

@@ -324,18 +324,19 @@ def read_training(nlp, training_dir, dev, limit):
                                         if 5 < sent_length < 100:
                                             ents_by_offset[str(ent.start_char) + "_" + str(ent.end_char)] = ent
                                 else:
-                                    skip_articles.add(current_article_id)
+                                    skip_articles.add(article_id)
                                     current_doc = None
                         except Exception as e:
                             print("Problem parsing article", article_id, e)
-                            skip_articles.add(current_article_id)
+                            skip_articles.add(article_id)
+                            raise e
 
                     # repeat checking this condition in case an exception was thrown
                     if current_doc and (current_article_id == article_id):
                         found_ent = ents_by_offset.get(start + "_" + end,  None)
                         if found_ent:
                             if found_ent.text != alias:
-                                skip_articles.add(current_article_id)
+                                skip_articles.add(article_id)
                                 current_doc = None
                             else:
                                 sent = found_ent.sent.as_doc()

spacy/errors.py

@@ -399,6 +399,9 @@ class Errors(object):
     E138 = ("Invalid JSONL format for raw text '{text}'. Make sure the input includes either the "
             "`text` or `tokens` key. For more info, see the docs:\n"
             "https://spacy.io/api/cli#pretrain-jsonl")
+    E139 = ("Knowledge base for component '{name}' not initialized. Did you forget to call set_kb()?")
+    E140 = ("The list of entities, prior probabilities and entity vectors should be of equal length.")
+    E141 = ("Entity vectors should be of length {required} instead of the provided {found}.")
 
 
 @add_codes

spacy/kb.pyx

@@ -106,9 +106,9 @@ cdef class KnowledgeBase:
             user_warning(Warnings.W018.format(entity=entity))
             return
 
+        # Raise an error if the provided entity vector is not of the correct length
         if len(entity_vector) != self.entity_vector_length:
-            # TODO: proper error
+            raise ValueError(Errors.E141.format(found=len(entity_vector), required=self.entity_vector_length))
-            raise ValueError("Entity vector length should have been", self.entity_vector_length)
 
         vector_index = self.c_add_vector(entity_vector=entity_vector)
 
@@ -121,13 +121,8 @@ cdef class KnowledgeBase:
         return entity_hash
 
     cpdef set_entities(self, entity_list, prob_list, vector_list):
-        if len(entity_list) != len(prob_list):
+        if len(entity_list) != len(prob_list) or len(entity_list) != len(vector_list):
-            # TODO: proper error
+            raise ValueError(Errors.E140)
-            raise ValueError("Entity list and prob list should have the same length")
-
-        if len(entity_list) != len(vector_list):
-            # TODO: proper error
-            raise ValueError("Entity list and vector list should have the same length")
 
         nr_entities = len(entity_list)
         self._entry_index = PreshMap(nr_entities+1)
@@ -138,8 +133,7 @@ cdef class KnowledgeBase:
         while i < nr_entities:
             entity_vector = vector_list[i]
             if len(entity_vector) != self.entity_vector_length:
-                # TODO: proper error
+                raise ValueError(Errors.E141.format(found=len(entity_vector), required=self.entity_vector_length))
-                raise ValueError("Entity vector is", len(entity_vector), "length but should have been", self.entity_vector_length)
 
             entity_hash = self.vocab.strings.add(entity_list[i])
             entry.entity_hash = entity_hash

spacy/pipeline/pipes.pyx

@@ -1002,7 +1002,7 @@ cdef class DependencyParser(Parser):
 
     @property
     def postprocesses(self):
-        return [nonproj.deprojectivize, merge_subtokens]
+        return [nonproj.deprojectivize]  # , merge_subtokens]
 
     def add_multitask_objective(self, target):
         if target == "cloze":
@@ -1100,8 +1100,7 @@ class EntityLinker(Pipe):
     def require_kb(self):
         # Raise an error if the knowledge base is not initialized.
         if getattr(self, "kb", None) in (None, True, False):
-            # TODO: custom error
+            raise ValueError(Errors.E139.format(name=self.name))
-            raise ValueError(Errors.E109.format(name=self.name))
 
     def begin_training(self, get_gold_tuples=lambda: [], pipeline=None, sgd=None, **kwargs):
         self.require_kb()