use resolve_type from pie_core

src/pie_modules/document/processing/merge_spans_via_relation.py

@@ -2,9 +2,9 @@
 from typing import Optional, Sequence, Set, Tuple, TypeVar, Union
 
 from pie_core import AnnotationLayer, Document
+from pie_core.utils.hydra import resolve_type
 
 from pie_modules.annotations import BinaryRelation, LabeledMultiSpan, LabeledSpan
-from pie_modules.utils import resolve_type
 
 logger = logging.getLogger(__name__)
 

src/pie_modules/document/processing/tokenization.py

@@ -17,11 +17,11 @@
 )
 
 from pie_core import Annotation
+from pie_core.utils.hydra import resolve_type
 from transformers import PreTrainedTokenizer
 
 from pie_modules.annotations import MultiSpan, Span
 from pie_modules.documents import TextBasedDocument, TokenBasedDocument
-from pie_modules.utils import resolve_type
 
 logger = logging.getLogger(__name__)
 

src/pie_modules/metrics/span_coverage_collector.py

@@ -2,12 +2,12 @@
 from typing import Any, Dict, List, Optional, Set, Type, Union
 
 from pie_core import Document, DocumentStatistic
+from pie_core.utils.hydra import resolve_type
 from transformers import AutoTokenizer, PreTrainedTokenizer
 
 from pie_modules.annotations import LabeledMultiSpan, Span
 from pie_modules.document.processing import tokenize_document
 from pie_modules.documents import TextBasedDocument, TokenBasedDocument
-from pie_modules.utils import resolve_type
 
 logger = logging.getLogger(__name__)
 

src/pie_modules/metrics/span_length_collector.py

@@ -3,12 +3,12 @@
 from typing import Any, Callable, Dict, List, Optional, Type, Union
 
 from pie_core import Document, DocumentStatistic
+from pie_core.utils.hydra import resolve_type
 from transformers import AutoTokenizer, PreTrainedTokenizer
 
 from pie_modules.annotations import Span
 from pie_modules.document.processing import tokenize_document
 from pie_modules.documents import TextBasedDocument, TokenBasedDocument
-from pie_modules.utils import resolve_type
 
 logger = logging.getLogger(__name__)
 

src/pie_modules/models/simple_generative.py

@@ -3,6 +3,7 @@
 from typing import Any, Dict, Optional, Tuple, Type, Union
 
 import torch
+from pie_core.utils.hydra import resolve_type
 from pytorch_ie import PyTorchIEModel
 from pytorch_lightning.utilities.types import OptimizerLRScheduler
 from torch import FloatTensor, LongTensor
@@ -12,7 +13,6 @@
 from typing_extensions import TypeAlias
 
 from pie_modules.models.common import ModelWithBoilerplate
-from pie_modules.utils import resolve_type
 
 logger = logging.getLogger(__name__)
 

src/pie_modules/taskmodules/pointer_network_for_end2end_re.py

@@ -31,6 +31,7 @@
     TargetEncoding,
     TaskBatchEncoding,
 )
+from pie_core.utils.hydra import resolve_type
 from torchmetrics import Metric
 from transformers import AutoTokenizer, LogitsProcessorList, PreTrainedTokenizer
 from typing_extensions import TypeAlias
@@ -45,7 +46,6 @@
 )
 
 from ..document.processing import token_based_document_to_text_based, tokenize_document
-from ..utils import resolve_type
 from .common import BatchableMixin, get_first_occurrence_index
 from .metrics import (
     PrecisionRecallAndF1ForLabeledAnnotations,

src/pie_modules/taskmodules/text_to_text.py

@@ -28,6 +28,7 @@
     TargetEncoding,
     TaskBatchEncoding,
 )
+from pie_core.utils.hydra import resolve_type
 from torchmetrics import Metric
 from transformers import AutoTokenizer, PreTrainedTokenizer
 from typing_extensions import TypeAlias
@@ -38,7 +39,6 @@
     tokenize_document,
 )
 from pie_modules.documents import TextBasedDocument, TokenBasedDocument
-from pie_modules.utils import resolve_type
 
 from .common import BatchableMixin, get_first_occurrence_index
 from .metrics import WrappedMetricWithPrepareFunction

src/pie_modules/utils/__init__.py

@@ -1,2 +1,4 @@
 from .dictionary import flatten_dict, list_of_dicts2dict_of_lists
+
+# backwards compatibility
 from .hydra import resolve_type

src/pie_modules/utils/hydra.py

@@ -1,25 +1,2 @@
-from typing import Optional, Type, TypeVar, Union
-
-from pie_core import Document
-from pie_core.utils.hydra import resolve_target
-
-T = TypeVar("T", bound=Document)
-T_super = TypeVar("T_super", bound=Document)
-
-
-def resolve_type(
-    type_or_str: Union[str, Type[T]], expected_super_type: Optional[Type[T_super]] = None
-) -> Type[T]:
-    if isinstance(type_or_str, str):
-        dt = resolve_target(type_or_str)  # type: ignore
-    else:
-        dt = type_or_str
-    if not (
-        isinstance(dt, type)
-        and (expected_super_type is None or issubclass(dt, expected_super_type))
-    ):
-        raise TypeError(
-            f"type must be a subclass of {expected_super_type} or a string that resolves to that, "
-            f"but got {dt}"
-        )
-    return dt
+# backwards compatibility
+from pie_core.utils.hydra import resolve_target, resolve_type

tests/utils/test_hydra.py

@@ -2,10 +2,10 @@
 
 import pytest
 from pie_core import AnnotationLayer, annotation_field
+from pie_core.utils.hydra import resolve_type
 
 from pie_modules.annotations import LabeledSpan, Span
 from pie_modules.documents import TextBasedDocument
-from pie_modules.utils import resolve_type
 
 
 @dataclasses.dataclass