adjust for pytorch-ie 0.28.8

README.md

@@ -0,0 +1,29 @@
+# PIE Dataset Card for "CDCP"
+
+This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the
+[CDCP Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/cdcp).
+
+## Data Schema
+
+The document type for this dataset is `CDCPDocument` which defines the following data fields:
+
+- `text` (str)
+- `id` (str, optional)
+- `metadata` (dictionary, optional)
+
+and the following annotation layers:
+
+- `propositions` (annotation type: `LabeledSpan`, target: `text`)
+- `relations` (annotation type: `BinaryRelation`, target: `propositions`)
+- `urls` (annotation type: `Attribute`, target: `propositions`)
+
+See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions.
+
+## Document Converters
+
+The dataset provides document converters for the following target document types:
+
+- `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations`
+
+See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type
+definitions.

cdcp.py

@@ -1,27 +1,27 @@
 import dataclasses
+import logging
 from typing import Any, Callable, Dict, List, Optional
 
 import datasets
-import pytorch_ie.data.builder
 from pytorch_ie.annotations import BinaryRelation, LabeledSpan
-from pytorch_ie.core import Annotation, AnnotationList, Document, annotation_field
+from pytorch_ie.core import Annotation, AnnotationList, annotation_field
+from pytorch_ie.documents import (
+    TextBasedDocument,
+    TextDocumentWithLabeledSpansAndBinaryRelations,
+)
 
-from src import utils
+from pie_datasets import GeneratorBasedBuilder
+from pie_datasets.document.processing.text_span_trimmer import trim_text_spans
 
-log = utils.get_pylogger(__name__)
+log = logging.getLogger(__name__)
 
 
 def dl2ld(dict_of_lists):
     return [dict(zip(dict_of_lists, t)) for t in zip(*dict_of_lists.values())]
 
 
-def ld2dl(list_of_dicts, keys: Optional[List[str]] = None, as_list: bool = False):
-    if keys is None:
-        keys = list_of_dicts[0].keys()
-    if as_list:
-        return [[d[k] for d in list_of_dicts] for k in keys]
-    else:
-        return {k: [d[k] for d in list_of_dicts] for k in keys}
+def ld2dl(list_of_dicts, keys: Optional[List[str]] = None):
+    return {k: [d[k] for d in list_of_dicts] for k in keys}
 
 
 @dataclasses.dataclass(frozen=True)
@@ -31,10 +31,7 @@ class Attribute(Annotation):
 
 
 @dataclasses.dataclass
-class CDCPDocument(Document):
-    text: str
-    id: Optional[str] = None
-    metadata: Dict[str, Any] = dataclasses.field(default_factory=dict)
+class CDCPDocument(TextBasedDocument):
     propositions: AnnotationList[LabeledSpan] = annotation_field(target="text")
     relations: AnnotationList[BinaryRelation] = annotation_field(target="propositions")
     urls: AnnotationList[Attribute] = annotation_field(target="propositions")
@@ -42,15 +39,15 @@ class CDCPDocument(Document):
 
 def example_to_document(
     example: Dict[str, Any],
-    relation_int2str: Callable[[int], str],
-    proposition_int2str: Callable[[int], str],
+    relation_label: datasets.ClassLabel,
+    proposition_label: datasets.ClassLabel,
 ):
     document = CDCPDocument(id=example["id"], text=example["text"])
     for proposition_dict in dl2ld(example["propositions"]):
         proposition = LabeledSpan(
             start=proposition_dict["start"],
             end=proposition_dict["end"],
-            label=proposition_int2str(proposition_dict["label"]),
+            label=proposition_label.int2str(proposition_dict["label"]),
         )
         document.propositions.append(proposition)
         if proposition_dict.get("url", "") != "":
@@ -61,7 +58,7 @@ def example_to_document(
         relation = BinaryRelation(
             head=document.propositions[relation_dict["head"]],
             tail=document.propositions[relation_dict["tail"]],
-            label=relation_int2str(relation_dict["label"]),
+            label=relation_label.int2str(relation_dict["label"]),
         )
         document.relations.append(relation)
 
@@ -70,8 +67,8 @@ def example_to_document(
 
 def document_to_example(
     document: CDCPDocument,
-    relation_str2int: Callable[[str], int],
-    proposition_str2int: Callable[[str], int],
+    relation_label: datasets.ClassLabel,
+    proposition_label: datasets.ClassLabel,
 ) -> Dict[str, Any]:
     result = {"id": document.id, "text": document.text}
     proposition2dict = {}
@@ -80,7 +77,7 @@ def document_to_example(
         proposition2dict[proposition] = {
             "start": proposition.start,
             "end": proposition.end,
-            "label": proposition_str2int(proposition.label),
+            "label": proposition_label.str2int(proposition.label),
             "url": "",
         }
         proposition2idx[proposition] = idx
@@ -95,7 +92,7 @@ def document_to_example(
         {
             "head": proposition2idx[relation.head],
             "tail": proposition2idx[relation.tail],
-            "label": relation_str2int(relation.label),
+            "label": relation_label.str2int(relation.label),
         }
         for relation in document.relations
     ]
@@ -104,20 +101,29 @@ def document_to_example(
     return result
 
 
-class CDCPConfig(datasets.BuilderConfig):
-    """BuilderConfig for CDCP."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for CDCP.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super().__init__(**kwargs)
+def convert_to_text_document_with_labeled_spans_and_binary_relations(
+    document: CDCPDocument,
+    verbose: bool = True,
+) -> TextDocumentWithLabeledSpansAndBinaryRelations:
+    doc_simplified = document.as_type(
+        TextDocumentWithLabeledSpansAndBinaryRelations,
+        field_mapping={"propositions": "labeled_spans", "relations": "binary_relations"},
+    )
+    result = trim_text_spans(
+        doc_simplified,
+        layer="labeled_spans",
+        verbose=verbose,
+    )
+    return result
 
 
-class CDCP(pytorch_ie.data.builder.GeneratorBasedBuilder):
+class CDCP(GeneratorBasedBuilder):
     DOCUMENT_TYPE = CDCPDocument
 
+    DOCUMENT_CONVERTERS = {
+        TextDocumentWithLabeledSpansAndBinaryRelations: convert_to_text_document_with_labeled_spans_and_binary_relations
+    }
+
     BASE_DATASET_PATH = "DFKI-SLT/cdcp"
 
     BUILDER_CONFIGS = [datasets.BuilderConfig(name="default")]
@@ -126,11 +132,11 @@ class CDCP(pytorch_ie.data.builder.GeneratorBasedBuilder):
 
     def _generate_document_kwargs(self, dataset):
         return {
-            "relation_int2str": dataset.features["relations"].feature["label"].int2str,
-            "proposition_int2str": dataset.features["propositions"].feature["label"].int2str,
+            "relation_label": dataset.features["relations"].feature["label"],
+            "proposition_label": dataset.features["propositions"].feature["label"],
         }
 
-    def _generate_document(self, example, relation_int2str, proposition_int2str):
+    def _generate_document(self, example, relation_label, proposition_label):
         return example_to_document(
-            example, relation_int2str=relation_int2str, proposition_int2str=proposition_int2str
+            example, relation_label=relation_label, proposition_label=proposition_label
         )

requirements.txt

@@ -0,0 +1 @@
+pie-datasets>=0.3.0