use pie-modules instead of pytorch-ie

see https://github.com/ArneBinder/pie-datasets/pull/204 for further information

README.md

@@ -7,7 +7,7 @@ This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for t
 
 ```python
 from pie_datasets import load_dataset
-from pytorch_ie.documents import TextDocumentWithLabeledSpansAndBinaryRelations
+from pie_modules.documents import TextDocumentWithLabeledSpansAndBinaryRelations
 
 # load English variant
 dataset = load_dataset("pie/argmicro", name="en")
@@ -57,13 +57,13 @@ and the following annotation layers:
     - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`)
     - `label` (str, optional), values: `sup`, `exa`, `reb`, `und` (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37) for reference, but note that helper relations `seg` and `add` are not there anymore, see above).
 
-See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions.
+See [here](https://github.com/ArneBinder/pie-modules/blob/main/src/pie_modules/annotations.py) for the annotation type definitions.
 
 ## Document Converters
 
 The dataset provides document converters for the following target document types:
 
-- `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations`
+- `pie_modules.documents.TextDocumentWithLabeledSpansAndBinaryRelations`
   - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus`
     - labels: `opp`, `pro`
     - if an ADU contains multiple spans (i.e. EDUs), we take the start of the first EDU and the end of the last EDU as the boundaries of the new `LabeledSpan`. We also raise exceptions if any newly created `LabeledSpan`s overlap.
@@ -72,7 +72,7 @@ The dataset provides document converters for the following target document types
     - if the `head` or `tail` consists of multiple `adus`, then we build `BinaryRelation`s with all `head`-`tail` combinations and take the label from the original relation. Then, we build `BinaryRelations`' with label `joint` between each component that previously belongs to the same `head` or `tail`, respectively.
   - `metadata`, we keep the `ArgMicroDocument`'s `metadata`, but `stance` and `topic_id`.
 
-See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type
+See [here](https://github.com/ArneBinder/pie-modules/blob/main/src/pie_modules/documents.py) for the document type
 definitions.
 
 ### Collected Statistics after Document Conversion
@@ -97,7 +97,7 @@ input:
   name: en
 ```
 
-For token based metrics, this uses `bert-base-uncased` from `transformer.AutoTokenizer` (see [AutoTokenizer](https://huggingface.co/docs/transformers/v4.37.1/en/model_doc/auto#transformers.AutoTokenizer), and [bert-based-uncased](https://huggingface.co/bert-base-uncased) to tokenize `text` in `TextDocumentWithLabeledSpansAndBinaryRelations` (see [document type](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py)).
+For token based metrics, this uses `bert-base-uncased` from `transformer.AutoTokenizer` (see [AutoTokenizer](https://huggingface.co/docs/transformers/v4.37.1/en/model_doc/auto#transformers.AutoTokenizer), and [bert-based-uncased](https://huggingface.co/bert-base-uncased) to tokenize `text` in `TextDocumentWithLabeledSpansAndBinaryRelations` (see [document type](https://github.com/ArneBinder/pie-modules/blob/main/src/pie_modules/documents.py)).
 
 #### Relation argument (outer) token distance per label
 

argmicro.py

@@ -6,9 +6,9 @@ from itertools import combinations
 from typing import Any, Dict, List, Optional, Set, Tuple
 
 import datasets
-from pytorch_ie.annotations import BinaryRelation, Label, LabeledSpan, Span
-from pytorch_ie.core import Annotation, AnnotationList, annotation_field
-from pytorch_ie.documents import (
+from pie_core import Annotation, AnnotationLayer, annotation_field
+from pie_modules.annotations import BinaryRelation, Label, LabeledSpan, Span
+from pie_modules.documents import (
     TextBasedDocument,
     TextDocumentWithLabeledSpansAndBinaryRelations,
 )
@@ -42,10 +42,10 @@ class MultiRelation(Annotation):
 @dataclasses.dataclass
 class ArgMicroDocument(TextBasedDocument):
     topic_id: Optional[str] = None
-    stance: AnnotationList[Label] = annotation_field()
-    edus: AnnotationList[Span] = annotation_field(target="text")
-    adus: AnnotationList[LabeledAnnotationCollection] = annotation_field(target="edus")
-    relations: AnnotationList[MultiRelation] = annotation_field(target="adus")
+    stance: AnnotationLayer[Label] = annotation_field()
+    edus: AnnotationLayer[Span] = annotation_field(target="text")
+    adus: AnnotationLayer[LabeledAnnotationCollection] = annotation_field(target="edus")
+    relations: AnnotationLayer[MultiRelation] = annotation_field(target="adus")
 
 
 def example_to_document(

requirements.txt

@@ -1 +1,2 @@
-pie-datasets>=0.3.3,<0.11.0
+pie-datasets>=0.10.11,<0.11.0
+pie-modules>=0.15.9,<0.16.0