Enhanced dependency parsing

combo/data/fields/sequence_multilabel_field.py

@@ -5,7 +5,7 @@ from typing import Set, List, Callable, Iterator, Union, Dict
 
 import torch
 from allennlp import data
-from allennlp.common import checks, util
+from allennlp.common import checks
 from allennlp.data import fields
 from overrides import overrides
 
@@ -17,15 +17,16 @@ class SequenceMultiLabelField(data.Field[torch.Tensor]):
     A `SequenceMultiLabelField` is an extension of the :class:`MultiLabelField` that allows for multiple labels
     while keeping sequence dimension.
 
-    This field will get converted into a sequence of vectors of length equal to the vocabulary size with
-    M from N encoding for the labels (all zeros, and ones for the labels).
+    To allow configuration to different circumstances, class takes few delegates functions.
 
     # Parameters
 
     multi_labels : `List[List[str]]`
     multi_label_indexer : `Callable[[data.Vocabulary], Callable[[List[str]], List[int]]]`
-        Nested callable which based on vocab creates mapper for multilabel field in the sequence from strings
-        to indexed, int values.
+        Nested callable which based on vocab and sequence length maps values of the fields in the sequence
+        from strings to indexed, int values.
+    as_tensor: `Callable[["SequenceMultiLabelField"], Callable[[Dict[str, int]], torch.Tensor]]`
+        Nested callable which based on the field itself, maps indexed data to a tensor.
     sequence_field : `SequenceField`
         A field containing the sequence that this `SequenceMultiLabelField` is labeling.  Most often, this is a
         `TextField`, for tagging individual tokens in a sentence.
@@ -43,7 +44,8 @@ class SequenceMultiLabelField(data.Field[torch.Tensor]):
     def __init__(
             self,
             multi_labels: List[List[str]],
-            multi_label_indexer: Callable[[data.Vocabulary], Callable[[List[str]], List[int]]],
+            multi_label_indexer: Callable[[data.Vocabulary], Callable[[List[str], int], List[int]]],
+            as_tensor: Callable[["SequenceMultiLabelField"], Callable[[Dict[str, int]], torch.Tensor]],
             sequence_field: fields.SequenceField,
             label_namespace: str = "labels",
     ) -> None:
@@ -53,6 +55,7 @@ class SequenceMultiLabelField(data.Field[torch.Tensor]):
         self._label_namespace = label_namespace
         self._indexed_multi_labels = None
         self._maybe_warn_for_namespace(label_namespace)
+        self.as_tensor_wrapper = as_tensor(self)
         if len(multi_labels) != sequence_field.sequence_length():
             raise checks.ConfigurationError(
                 "Label length and sequence length "
@@ -101,7 +104,7 @@ class SequenceMultiLabelField(data.Field[torch.Tensor]):
 
         indexed = []
         for multi_label in self.multi_labels:
-            indexed.append(indexer(multi_label))
+            indexed.append(indexer(multi_label, len(self.multi_labels)))
         self._indexed_multi_labels = indexed
 
     @overrides
@@ -110,19 +113,13 @@ class SequenceMultiLabelField(data.Field[torch.Tensor]):
 
     @overrides
     def as_tensor(self, padding_lengths: Dict[str, int]) -> torch.Tensor:
-        desired_num_tokens = padding_lengths["num_tokens"]
-        assert len(self._indexed_multi_labels) > 0
-        classes_count = len(self._indexed_multi_labels[0])
-        default_value = [0.0] * classes_count
-        padded_tags = util.pad_sequence_to_length(self._indexed_multi_labels, desired_num_tokens, lambda: default_value)
-        tensor = torch.LongTensor(padded_tags)
-        return tensor
+        return self.as_tensor_wrapper(padding_lengths)
 
     @overrides
     def empty_field(self) -> "SequenceMultiLabelField":
-        # The empty_list here is needed for mypy
         empty_list: List[List[str]] = [[]]
         sequence_label_field = SequenceMultiLabelField(empty_list, lambda x: lambda y: y,
+                                                       lambda x: lambda y: y,
                                                        self.sequence_field.empty_field())
         sequence_label_field._indexed_labels = empty_list
         return sequence_label_field