use pie-documents (#476)

Changes:
 - use `pie-documents`
- remove `annotations` and `documents`, but re-export them from
`pie-documents`
    - remove respective tests
- remove `metrics` and `statistics` (except `TokenCountCollector`), but
re-export them from `pie-documents`
    - remove respective tests
    - remove `pandas` dependency (was just used in metrics)
- remove `is_contained_in` and `has_overlap` from `utils.span`, but
re-export them from `pie-documents`
    - remove  test file with tests that were commented out 
 - lower codecov project target from 70% to 68%   

This requires pie-documents release
[v0.1.0](https://github.com/ArneBinder/pie-documents/releases/tag/v0.1.0).

We mark this as **breaking, since documents and annotations are now from
another package** which may cause type mismatches.

**IMPORTANT: This will be incompatible with `pie-modules` (this is
enforced via may pytorch-ie version in latest pie-modules release).**

Author: ArneBinder

codecov.yml

@@ -2,7 +2,7 @@ coverage:
     status:
         project:
             default:
-                target: 70% # TODO: switch back to auto
+                target: 68% # TODO: switch back to auto
                 threshold: 1% # the leniency in hitting the target
         patch:
             default:

poetry.lock

@@ -18,12 +18,11 @@ dynamic = [ "classifiers" ]
 requires-python = ">=3.9,<4.0"
 dependencies = [
     "pie-core >=0.2.1, <0.4.0",
+    "pie-documents >=0.1.0, <0.2.0",
     "torch >=1.10",
     "pytorch-lightning >=2, <3",
     "torchmetrics >1, <2",
     "transformers >=4.18, <5",
-    # required for metrics: f1, confusion_matrix, and statsistics
-    "pandas >=2.0.0, <3",
 ]
 
 [project.urls]
@@ -44,6 +43,10 @@ classifiers = [
     "License :: OSI Approved :: MIT License"
 ]
 
+[tool.poetry.urls]
+"Bug Tracker" = "https://github.com/christophalt/pytorch-ie/issues"
+"Changelog" = "https://github.com/christophalt/pytorch-ie/releases"
+
 [tool.poetry.group.dev]
 optional = true
 

pyproject.toml

@@ -1,188 +1,13 @@
-from dataclasses import dataclass, field
-from typing import Any, Optional, Tuple
-
-from pie_core import Annotation
-
-
-def _post_init_single_label(self):
-    if not isinstance(self.label, str):
-        raise ValueError("label must be a single string.")
-
-    if not isinstance(self.score, float):
-        raise ValueError("score must be a single float.")
-
-
-def _post_init_multi_label(self):
-    if self.score is None:
-        score = tuple([1.0] * len(self.label))
-        object.__setattr__(self, "score", score)
-
-    if not isinstance(self.label, tuple):
-        object.__setattr__(self, "label", tuple(self.label))
-
-    if not isinstance(self.score, tuple):
-        object.__setattr__(self, "score", tuple(self.score))
-
-    if len(self.label) != len(self.score):
-        raise ValueError(
-            f"Number of labels ({len(self.label)}) and scores ({len(self.score)}) must be equal."
-        )
-
-
-def _post_init_multi_span(self):
-    if isinstance(self.slices, list):
-        object.__setattr__(self, "slices", tuple(tuple(s) for s in self.slices))
-
-
-def _post_init_arguments_and_roles(self):
-    if len(self.arguments) != len(self.roles):
-        raise ValueError(
-            f"Number of arguments ({len(self.arguments)}) and roles ({len(self.roles)}) must be equal"
-        )
-    if not isinstance(self.arguments, tuple):
-        object.__setattr__(self, "arguments", tuple(self.arguments))
-    if not isinstance(self.roles, tuple):
-        object.__setattr__(self, "roles", tuple(self.roles))
-
-
-@dataclass(eq=True, frozen=True)
-class Label(Annotation):
-    label: str
-    score: float = field(default=1.0, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_single_label(self)
-
-    def resolve(self) -> Any:
-        return self.label
-
-
-@dataclass(eq=True, frozen=True)
-class MultiLabel(Annotation):
-    label: Tuple[str, ...]
-    score: Optional[Tuple[float, ...]] = field(default=None, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_multi_label(self)
-
-    def resolve(self) -> Any:
-        return self.label
-
-
-@dataclass(eq=True, frozen=True)
-class Span(Annotation):
-    start: int
-    end: int
-
-    def __str__(self) -> str:
-        if not self.is_attached:
-            return super().__str__()
-        return str(self.target[self.start : self.end])
-
-    def resolve(self) -> Any:
-        if self.is_attached:
-            return self.target[self.start : self.end]
-        else:
-            raise ValueError(f"{self} is not attached to a target.")
-
-
-@dataclass(eq=True, frozen=True)
-class LabeledSpan(Span):
-    label: str
-    score: float = field(default=1.0, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_single_label(self)
-
-    def resolve(self) -> Any:
-        return self.label, super().resolve()
-
-
-@dataclass(eq=True, frozen=True)
-class MultiLabeledSpan(Span):
-    label: Tuple[str, ...]
-    score: Optional[Tuple[float, ...]] = field(default=None, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_multi_label(self)
-
-    def resolve(self) -> Any:
-        return self.label, super().resolve()
-
-
-@dataclass(eq=True, frozen=True)
-class MultiSpan(Annotation):
-    slices: Tuple[Tuple[int, int], ...]
-
-    def __post_init__(self) -> None:
-        _post_init_multi_span(self)
-
-    def __str__(self) -> str:
-        if not self.is_attached:
-            return super().__str__()
-        return str(tuple(self.target[start:end] for start, end in self.slices))
-
-    def resolve(self) -> Any:
-        if self.is_attached:
-            return tuple(self.target[start:end] for start, end in self.slices)
-        else:
-            raise ValueError(f"{self} is not attached to a target.")
-
-
-@dataclass(eq=True, frozen=True)
-class LabeledMultiSpan(MultiSpan):
-    label: str
-    score: float = field(default=1.0, compare=False)
-
-    def __post_init__(self) -> None:
-        super().__post_init__()
-        _post_init_single_label(self)
-
-    def resolve(self) -> Any:
-        return self.label, super().resolve()
-
-
-@dataclass(eq=True, frozen=True)
-class BinaryRelation(Annotation):
-    head: Annotation
-    tail: Annotation
-    label: str
-    score: float = field(default=1.0, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_single_label(self)
-
-    def resolve(self) -> Any:
-        return self.label, (self.head.resolve(), self.tail.resolve())
-
-
-@dataclass(eq=True, frozen=True)
-class MultiLabeledBinaryRelation(Annotation):
-    head: Annotation
-    tail: Annotation
-    label: Tuple[str, ...]
-    score: Optional[Tuple[float, ...]] = field(default=None, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_multi_label(self)
-
-    def resolve(self) -> Any:
-        return self.label, (self.head.resolve(), self.tail.resolve())
-
-
-@dataclass(eq=True, frozen=True)
-class NaryRelation(Annotation):
-    arguments: Tuple[Annotation, ...]
-    roles: Tuple[str, ...]
-    label: str
-    score: float = field(default=1.0, compare=False)
-
-    def __post_init__(self) -> None:
-        _post_init_arguments_and_roles(self)
-        _post_init_single_label(self)
-
-    def resolve(self) -> Any:
-        return (
-            self.label,
-            tuple((role, arg.resolve()) for arg, role in zip(self.arguments, self.roles)),
-        )
+# backward compatibility
+from pie_documents.annotations import (
+    BinaryRelation,
+    Label,
+    LabeledMultiSpan,
+    LabeledSpan,
+    MultiLabel,
+    MultiLabeledBinaryRelation,
+    MultiLabeledSpan,
+    MultiSpan,
+    NaryRelation,
+    Span,
+)