From ad6c5ea81f47e878109c3b9dcf802f1ef6cbae57 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 17:50:00 +0200
Subject: [PATCH 01/11] use pie-modules from branch `remove-pytorch_ie`
 (https://github.com/ArneBinder/pie-modules/pull/187)

---
 poetry.lock    | 1825 ++++++++++++++++++++++++++++++++++++++++++------
 pyproject.toml |    4 +
 2 files changed, 1615 insertions(+), 214 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index cd2b795c..52a46263 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,17 @@
 # This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand.
 
+[[package]]
+name = "absl-py"
+version = "1.4.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
+    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
+]
+
 [[package]]
 name = "aiohttp"
 version = "3.9.5"
@@ -112,6 +124,68 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "alabaster"
+version = "0.7.16"
+description = "A light, configurable Sphinx theme"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"},
+    {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"},
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
+[[package]]
+name = "anyio"
+version = "4.4.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
+    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\""]
+trio = ["trio (>=0.23)"]
+
+[[package]]
+name = "argcomplete"
+version = "3.3.0"
+description = "Bash tab completion for argparse"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "argcomplete-3.3.0-py3-none-any.whl", hash = "sha256:c168c3723482c031df3c207d4ba8fa702717ccb9fc0bfe4117166c1f537b4a54"},
+    {file = "argcomplete-3.3.0.tar.gz", hash = "sha256:fd03ff4a5b9e6580569d34b273f741e85cd9e072f3feeeee3eba4891c70eda62"},
+]
+
+[package.extras]
+test = ["coverage", "mypy", "pexpect", "ruff", "wheel"]
+
 [[package]]
 name = "async-timeout"
 version = "4.0.3"
@@ -131,7 +205,7 @@ version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
     {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
@@ -145,6 +219,83 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6) ; platform_python_implementation == \"CPython\" and python_version >= \"3.8\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.8\""]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
+[[package]]
+name = "authlib"
+version = "1.3.0"
+description = "The ultimate Python library in building OAuth and OpenID Connect servers and clients."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "Authlib-1.3.0-py2.py3-none-any.whl", hash = "sha256:9637e4de1fb498310a56900b3e2043a206b03cb11c05422014b0302cbc814be3"},
+    {file = "Authlib-1.3.0.tar.gz", hash = "sha256:959ea62a5b7b5123c5059758296122b57cd2585ae2ed1c0622c21b371ffdae06"},
+]
+
+[package.dependencies]
+cryptography = "*"
+
+[[package]]
+name = "babel"
+version = "2.15.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "Babel-2.15.0-py3-none-any.whl", hash = "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb"},
+    {file = "babel-2.15.0.tar.gz", hash = "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413"},
+]
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+
+[[package]]
+name = "bandit"
+version = "1.7.8"
+description = "Security oriented static analyser for python code."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "bandit-1.7.8-py3-none-any.whl", hash = "sha256:509f7af645bc0cd8fd4587abc1a038fc795636671ee8204d502b933aee44f381"},
+    {file = "bandit-1.7.8.tar.gz", hash = "sha256:36de50f720856ab24a24dbaa5fee2c66050ed97c1477e0a1159deab1775eab6b"},
+]
+
+[package.dependencies]
+colorama = {version = ">=0.3.9", markers = "platform_system == \"Windows\""}
+PyYAML = ">=5.3.1"
+rich = "*"
+stevedore = ">=1.20.0"
+
+[package.extras]
+baseline = ["GitPython (>=3.1.30)"]
+sarif = ["jschema-to-python (>=1.2.3)", "sarif-om (>=1.0.4)"]
+test = ["beautifulsoup4 (>=4.8.0)", "coverage (>=4.5.4)", "fixtures (>=3.0.0)", "flake8 (>=4.0.0)", "pylint (==1.9.4)", "stestr (>=2.5.0)", "testscenarios (>=0.5.0)", "testtools (>=2.3.0)"]
+toml = ["tomli (>=1.1.0) ; python_version < \"3.11\""]
+yaml = ["PyYAML"]
+
+[[package]]
+name = "beautifulsoup4"
+version = "4.12.3"
+description = "Screen-scraping library"
+optional = false
+python-versions = ">=3.6.0"
+groups = ["dev"]
+files = [
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
+]
+
+[package.dependencies]
+soupsieve = ">1.2"
+
+[package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
 [[package]]
 name = "black"
 version = "24.4.2"
@@ -192,18 +343,110 @@ d = ["aiohttp (>=3.7.4) ; sys_platform != \"win32\" or implementation_name != \"
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
+[[package]]
+name = "build"
+version = "1.2.2.post1"
+description = "A simple, correct Python build frontend"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "build-1.2.2.post1-py3-none-any.whl", hash = "sha256:1d61c0887fa860c01971625baae8bdd338e517b836a2f70dd1f7aa3a6b2fc5b5"},
+    {file = "build-1.2.2.post1.tar.gz", hash = "sha256:b36993e92ca9375a219c99e606a122ff365a760a2d4bba0caa09bd5278b608b7"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "os_name == \"nt\""}
+importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
+packaging = ">=19.1"
+pyproject_hooks = "*"
+tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0) ; python_version < \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.11\"", "setuptools (>=67.8.0) ; python_version >= \"3.12\"", "wheel (>=0.36.0)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
+virtualenv = ["virtualenv (>=20.0.35)"]
+
 [[package]]
 name = "certifi"
 version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
     {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.16.0"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+markers = "platform_python_implementation != \"PyPy\""
+files = [
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 [[package]]
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 version = "3.4.0"
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 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
-groups = ["main"]
+groups = ["main", "dev"]
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+
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+groups = ["dev"]
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 [package.dependencies]
@@ -448,6 +673,73 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 [package.extras]
 toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
+[[package]]
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+optional = false
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+groups = ["dev"]
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+    {file = "cryptography-42.0.7-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:e9b2a6309f14c0497f348d08a065d52f3020656f675819fc405fb63bbcd26562"},
+    {file = "cryptography-42.0.7-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:d8e3098721b84392ee45af2dd554c947c32cc52f862b6a3ae982dbb90f577f14"},
+    {file = "cryptography-42.0.7-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:c65f96dad14f8528a447414125e1fc8feb2ad5a272b8f68477abbcc1ea7d94b9"},
+    {file = "cryptography-42.0.7-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:36017400817987670037fbb0324d71489b6ead6231c9604f8fc1f7d008087c68"},
+    {file = "cryptography-42.0.7.tar.gz", hash = "sha256:ecbfbc00bf55888edda9868a4cf927205de8499e7fabe6c050322298382953f2"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
+docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
+nox = ["nox"]
+pep8test = ["check-sdist", "click", "mypy", "ruff"]
+sdist = ["build"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test-randomorder = ["pytest-randomly"]
+
+[[package]]
+name = "darglint"
+version = "1.8.1"
+description = "A utility for ensuring Google-style docstrings stay up to date with the source code."
+optional = false
+python-versions = ">=3.6,<4.0"
+groups = ["dev"]
+files = [
+    {file = "darglint-1.8.1-py3-none-any.whl", hash = "sha256:5ae11c259c17b0701618a20c3da343a3eb98b3bc4b5a83d31cdd94f5ebdced8d"},
+    {file = "darglint-1.8.1.tar.gz", hash = "sha256:080d5106df149b199822e7ee7deb9c012b49891538f14a11be681044f0bb20da"},
+]
+
 [[package]]
 name = "distlib"
 version = "0.3.8"
@@ -461,35 +753,54 @@ files = [
 ]
 
 [[package]]
-name = "exceptiongroup"
-version = "1.2.1"
-description = "Backport of PEP 654 (exception groups)"
+name = "docutils"
+version = "0.21.2"
+description = "Docutils -- Python Documentation Utilities"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "docutils-0.21.2-py3-none-any.whl", hash = "sha256:dafca5b9e384f0e419294eb4d2ff9fa826435bf15f15b7bd45723e8ad76811b2"},
+    {file = "docutils-0.21.2.tar.gz", hash = "sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f"},
+]
+
+[[package]]
+name = "dparse"
+version = "0.6.4b0"
+description = "A parser for Python dependency files"
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
-markers = "python_version < \"3.11\""
 files = [
-    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
-    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
+    {file = "dparse-0.6.4b0-py3-none-any.whl", hash = "sha256:592ff183348b8a5ea0a18442a7965e29445d3a26063654ec2c7e8ef42cd5753c"},
+    {file = "dparse-0.6.4b0.tar.gz", hash = "sha256:f8d49b41a527f3d16a269f854e6665245b325e50e41d2c213810cb984553e5c8"},
 ]
 
+[package.dependencies]
+packaging = "*"
+tomli = {version = "*", markers = "python_version < \"3.11\""}
+
 [package.extras]
-test = ["pytest (>=6)"]
+all = ["dparse[conda]", "dparse[pipenv]", "dparse[poetry]"]
+conda = ["pyyaml"]
+pipenv = ["pipenv"]
+poetry = ["poetry"]
 
 [[package]]
-name = "execnet"
-version = "2.1.1"
-description = "execnet: rapid multi-Python deployment"
+name = "exceptiongroup"
+version = "1.2.1"
+description = "Backport of PEP 654 (exception groups)"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 groups = ["dev"]
+markers = "python_version < \"3.11\""
 files = [
-    {file = "execnet-2.1.1-py3-none-any.whl", hash = "sha256:26dee51f1b80cebd6d0ca8e74dd8745419761d3bef34163928cbebbdc4749fdc"},
-    {file = "execnet-2.1.1.tar.gz", hash = "sha256:5189b52c6121c24feae288166ab41b32549c7e2348652736540b9e6e7d4e72e3"},
+    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
+    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
 ]
 
 [package.extras]
-testing = ["hatch", "pre-commit", "pytest", "tox"]
+test = ["pytest (>=6)"]
 
 [[package]]
 name = "filelock"
@@ -508,6 +819,94 @@ docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1
 testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
 typing = ["typing-extensions (>=4.8) ; python_version < \"3.11\""]
 
+[[package]]
+name = "flake8"
+version = "7.0.0"
+description = "the modular source code checker: pep8 pyflakes and co"
+optional = false
+python-versions = ">=3.8.1"
+groups = ["dev"]
+files = [
+    {file = "flake8-7.0.0-py2.py3-none-any.whl", hash = "sha256:a6dfbb75e03252917f2473ea9653f7cd799c3064e54d4c8140044c5c065f53c3"},
+    {file = "flake8-7.0.0.tar.gz", hash = "sha256:33f96621059e65eec474169085dc92bf26e7b2d47366b70be2f67ab80dc25132"},
+]
+
+[package.dependencies]
+mccabe = ">=0.7.0,<0.8.0"
+pycodestyle = ">=2.11.0,<2.12.0"
+pyflakes = ">=3.2.0,<3.3.0"
+
+[[package]]
+name = "flake8-bandit"
+version = "4.1.1"
+description = "Automated security testing with bandit and flake8."
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "flake8_bandit-4.1.1-py3-none-any.whl", hash = "sha256:4c8a53eb48f23d4ef1e59293657181a3c989d0077c9952717e98a0eace43e06d"},
+    {file = "flake8_bandit-4.1.1.tar.gz", hash = "sha256:068e09287189cbfd7f986e92605adea2067630b75380c6b5733dab7d87f9a84e"},
+]
+
+[package.dependencies]
+bandit = ">=1.7.3"
+flake8 = ">=5.0.0"
+
+[[package]]
+name = "flake8-bugbear"
+version = "24.4.26"
+description = "A plugin for flake8 finding likely bugs and design problems in your program. Contains warnings that don't belong in pyflakes and pycodestyle."
+optional = false
+python-versions = ">=3.8.1"
+groups = ["dev"]
+files = [
+    {file = "flake8_bugbear-24.4.26-py3-none-any.whl", hash = "sha256:cb430dd86bc821d79ccc0b030789a9c87a47a369667f12ba06e80f11305e8258"},
+    {file = "flake8_bugbear-24.4.26.tar.gz", hash = "sha256:ff8d4ba5719019ebf98e754624c30c05cef0dadcf18a65d91c7567300e52a130"},
+]
+
+[package.dependencies]
+attrs = ">=19.2.0"
+flake8 = ">=6.0.0"
+
+[package.extras]
+dev = ["coverage", "hypothesis", "hypothesmith (>=0.2)", "pre-commit", "pytest", "tox"]
+
+[[package]]
+name = "flake8-docstrings"
+version = "1.7.0"
+description = "Extension for flake8 which uses pydocstyle to check docstrings"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "flake8_docstrings-1.7.0-py2.py3-none-any.whl", hash = "sha256:51f2344026da083fc084166a9353f5082b01f72901df422f74b4d953ae88ac75"},
+    {file = "flake8_docstrings-1.7.0.tar.gz", hash = "sha256:4c8cc748dc16e6869728699e5d0d685da9a10b0ea718e090b1ba088e67a941af"},
+]
+
+[package.dependencies]
+flake8 = ">=3"
+pydocstyle = ">=2.1"
+
+[[package]]
+name = "flake8-rst-docstrings"
+version = "0.3.0"
+description = "Python docstring reStructuredText (RST) validator for flake8"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "flake8-rst-docstrings-0.3.0.tar.gz", hash = "sha256:d1ce22b4bd37b73cd86b8d980e946ef198cfcc18ed82fedb674ceaa2f8d1afa4"},
+    {file = "flake8_rst_docstrings-0.3.0-py3-none-any.whl", hash = "sha256:f8c3c6892ff402292651c31983a38da082480ad3ba253743de52989bdc84ca1c"},
+]
+
+[package.dependencies]
+flake8 = ">=3"
+pygments = "*"
+restructuredtext-lint = "*"
+
+[package.extras]
+develop = ["build", "twine"]
+
 [[package]]
 name = "frozenlist"
 version = "1.4.1"
@@ -635,6 +1034,36 @@ smb = ["smbprotocol"]
 ssh = ["paramiko"]
 tqdm = ["tqdm"]
 
+[[package]]
+name = "furo"
+version = "2024.5.6"
+description = "A clean customisable Sphinx documentation theme."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "furo-2024.5.6-py3-none-any.whl", hash = "sha256:490a00d08c0a37ecc90de03ae9227e8eb5d6f7f750edf9807f398a2bdf2358de"},
+    {file = "furo-2024.5.6.tar.gz", hash = "sha256:81f205a6605ebccbb883350432b4831c0196dd3d1bc92f61e1f459045b3d2b0b"},
+]
+
+[package.dependencies]
+beautifulsoup4 = "*"
+pygments = ">=2.7"
+sphinx = ">=6.0,<8.0"
+sphinx-basic-ng = ">=1.0.0.beta2"
+
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
 [[package]]
 name = "huggingface-hub"
 version = "0.25.2"
@@ -691,12 +1120,24 @@ version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
     {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
 ]
 
+[[package]]
+name = "imagesize"
+version = "1.4.1"
+description = "Getting image size from png/jpeg/jpeg2000/gif file"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["dev"]
+files = [
+    {file = "imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b"},
+    {file = "imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a"},
+]
+
 [[package]]
 name = "importlib-metadata"
 version = "7.1.0"
@@ -704,7 +1145,7 @@ description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.9\""
+markers = "python_full_version < \"3.10.2\""
 files = [
     {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
     {file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
@@ -767,7 +1208,7 @@ version = "3.1.4"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
     {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
@@ -801,13 +1242,38 @@ cli = ["fire"]
 docs = ["requests (>=2.0.0)"]
 typing = ["mypy (>=1.0.0)", "types-setuptools"]
 
+[[package]]
+name = "markdown-it-py"
+version = "3.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
+    {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"},
+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+code-style = ["pre-commit (>=3.0,<4.0)"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins"]
+profiling = ["gprof2dot"]
+rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
 [[package]]
 name = "markupsafe"
 version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc"},
     {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72b6be590cc35924b02c78ef34b467da4ba07e4e0f0454a2c5907f473fc50ce5"},
@@ -871,6 +1337,70 @@ files = [
     {file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
 ]
 
+[[package]]
+name = "marshmallow"
+version = "3.21.2"
+description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "marshmallow-3.21.2-py3-none-any.whl", hash = "sha256:70b54a6282f4704d12c0a41599682c5c5450e843b9ec406308653b47c59648a1"},
+    {file = "marshmallow-3.21.2.tar.gz", hash = "sha256:82408deadd8b33d56338d2182d455db632c6313aa2af61916672146bb32edc56"},
+]
+
+[package.dependencies]
+packaging = ">=17.0"
+
+[package.extras]
+dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
+docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.3.7)", "sphinx-issues (==4.1.0)", "sphinx-version-warning (==1.1.2)"]
+tests = ["pytest", "pytz", "simplejson"]
+
+[[package]]
+name = "mccabe"
+version = "0.7.0"
+description = "McCabe checker, plugin for flake8"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "mccabe-0.7.0-py2.py3-none-any.whl", hash = "sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e"},
+    {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"},
+]
+
+[[package]]
+name = "mdit-py-plugins"
+version = "0.4.1"
+description = "Collection of plugins for markdown-it-py"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+groups = ["dev"]
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+
+[[package]]
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+description = "Check PEP-8 naming conventions, plugin for flake8"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
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+
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+version = "0.15.9"
+description = "Utility modules for Python-IE"
+optional = false
+python-versions = "^3.9"
+groups = ["main"]
+files = []
+develop = false
+
+[package.dependencies]
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+
+[package.source]
+type = "git"
+url = "https://github.com/ArneBinder/pie-modules"
+reference = "remove-pytorch_ie"
+resolved_reference = "6ddb6b4f055991f3111920bfbc3d34cdf8248058"
 
 [[package]]
 name = "platformdirs"
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-pluggy = ">=1.2"
-pytest = ">=6.2.5"
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
+
+[[package]]
+name = "pydocstyle"
+version = "6.3.0"
+description = "Python docstring style checker"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
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+[package.dependencies]
+snowballstemmer = ">=2.2.0"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+toml = ["tomli (>=1.2.3) ; python_version < \"3.11\""]
 
 [[package]]
-name = "pytest-xdist"
-version = "3.8.0"
-description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs"
+name = "pyflakes"
+version = "3.2.0"
+description = "passive checker of Python programs"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
+[[package]]
+name = "pyproject-hooks"
+version = "1.2.0"
+description = "Wrappers to call pyproject.toml-based build backend hooks."
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
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+
+[[package]]
+name = "pytest"
+version = "8.2.1"
+description = "pytest: simple powerful testing with Python"
+optional = false
+python-versions = ">=3.8"
 groups = ["dev"]
 files = [
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+    {file = "pytest-8.2.1.tar.gz", hash = "sha256:5046e5b46d8e4cac199c373041f26be56fdb81eb4e67dc11d4e10811fc3408fd"},
 ]
 
 [package.dependencies]
-execnet = ">=2.1"
-pytest = ">=7.0.0"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
+iniconfig = "*"
+packaging = "*"
+pluggy = ">=1.5,<2.0"
+tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-psutil = ["psutil (>=3.0)"]
-setproctitle = ["setproctitle"]
-testing = ["filelock"]
+dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
@@ -1638,30 +2424,30 @@ test = ["cloudpickle (>=1.3)", "coverage (==7.3.1)", "fastapi", "onnx (>=0.14.0)
 
 [[package]]
 name = "pytz"
-version = "2025.2"
+version = "2024.1"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
 groups = ["main"]
 files = [
-    {file = "pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00"},
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+    {file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"},
+    {file = "pytz-2024.1.tar.gz", hash = "sha256:2a29735ea9c18baf14b448846bde5a48030ed267578472d8955cd0e7443a9812"},
 ]
 
 [[package]]
 name = "pyupgrade"
-version = "3.20.0"
+version = "3.15.2"
 description = "A tool to automatically upgrade syntax for newer versions."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8.1"
 groups = ["dev"]
 files = [
-    {file = "pyupgrade-3.20.0-py2.py3-none-any.whl", hash = "sha256:cd5bf842b863f50adad324a01c30aef60b9f698a9814848094818659c92cd1f4"},
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+    {file = "pyupgrade-3.15.2-py2.py3-none-any.whl", hash = "sha256:ce309e0ff8ecb73f56a45f12570be84bbbde9540d13697cacb261a7f595fb1f5"},
+    {file = "pyupgrade-3.15.2.tar.gz", hash = "sha256:c488d6896c546d25845712ef6402657123008d56c1063174e27aabe15bd6b4e5"},
 ]
 
 [package.dependencies]
-tokenize-rt = ">=6.1.0"
+tokenize-rt = ">=5.2.0"
 
 [[package]]
 name = "pyyaml"
@@ -1819,7 +2605,7 @@ version = "2.32.2"
 description = "Python HTTP for Humans."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
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@@ -1835,6 +2621,39 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "restructuredtext-lint"
+version = "1.4.0"
+description = "reStructuredText linter"
+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
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+]
+
+[package.dependencies]
+docutils = ">=0.11,<1.0"
+
+[[package]]
+name = "rich"
+version = "13.7.1"
+description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+optional = false
+python-versions = ">=3.7.0"
+groups = ["dev"]
+files = [
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+    {file = "rich-13.7.1.tar.gz", hash = "sha256:9be308cb1fe2f1f57d67ce99e95af38a1e2bc71ad9813b0e247cf7ffbcc3a432"},
+]
+
+[package.dependencies]
+markdown-it-py = ">=2.2.0"
+pygments = ">=2.13.0,<3.0.0"
+
+[package.extras]
+jupyter = ["ipywidgets (>=7.5.1,<9)"]
+
 [[package]]
 name = "ruamel-yaml"
 version = "0.18.6"
@@ -2038,6 +2857,59 @@ tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
 testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
 torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
+[[package]]
+name = "safety"
+version = "3.2.0"
+description = "Checks installed dependencies for known vulnerabilities and licenses."
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
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+    {file = "safety-3.2.0.tar.gz", hash = "sha256:8bd5cab5f3d8a61ce0ea6e98f267c1006d056097c45c644fee7afeff7d5949c1"},
+]
+
+[package.dependencies]
+Authlib = ">=1.2.0"
+Click = ">=8.0.2"
+dparse = ">=0.6.4b0"
+jinja2 = ">=3.1.0"
+marshmallow = ">=3.15.0"
+packaging = ">=21.0"
+pydantic = ">=1.10.12"
+requests = "*"
+rich = "*"
+"ruamel.yaml" = ">=0.17.21"
+safety-schemas = ">=0.0.2"
+setuptools = ">=65.5.1"
+typer = "*"
+typing-extensions = ">=4.7.1"
+urllib3 = ">=1.26.5"
+
+[package.extras]
+github = ["pygithub (>=1.43.3)"]
+gitlab = ["python-gitlab (>=1.3.0)"]
+spdx = ["spdx-tools (>=0.8.2)"]
+
+[[package]]
+name = "safety-schemas"
+version = "0.0.2"
+description = "Schemas for Safety tools"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "safety_schemas-0.0.2-py3-none-any.whl", hash = "sha256:277c077ce6e53221874a87c29515ffdd2f3773a6db4d035a9f67cc98db3b8c7f"},
+    {file = "safety_schemas-0.0.2.tar.gz", hash = "sha256:7d1b040ec06480f05cff6b45ea7a93e09c8942df864fb0d01ddeb67c323cfa8c"},
+]
+
+[package.dependencies]
+dparse = ">=0.6.4b0"
+packaging = ">=21.0"
+pydantic = "*"
+ruamel-yaml = ">=0.17.21"
+typing-extensions = ">=4.7.1"
+
 [[package]]
 name = "setuptools"
 version = "70.0.0"
@@ -2066,18 +2938,295 @@ files = [
     {file = "sh-2.0.6.tar.gz", hash = "sha256:9b2998f313f201c777e2c0061f0b1367497097ef13388595be147e2a00bf7ba1"},
 ]
 
+[[package]]
+name = "shellingham"
+version = "1.5.4"
+description = "Tool to Detect Surrounding Shell"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "shellingham-1.5.4-py2.py3-none-any.whl", hash = "sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686"},
+    {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"},
+]
+
 [[package]]
 name = "six"
-version = "1.17.0"
+version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 groups = ["main"]
 files = [
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-    {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"},
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
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+]
+
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
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+]
+
+[[package]]
+name = "snowballstemmer"
+version = "2.2.0"
+description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms."
+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
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+[[package]]
+name = "soupsieve"
+version = "2.5"
+description = "A modern CSS selector implementation for Beautiful Soup."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+[[package]]
+name = "sphinx"
+version = "7.3.7"
+description = "Python documentation generator"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
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+docutils = ">=0.18.1,<0.22"
+imagesize = ">=1.3"
+importlib-metadata = {version = ">=4.8", markers = "python_version < \"3.10\""}
+Jinja2 = ">=3.0"
+packaging = ">=21.0"
+Pygments = ">=2.14"
+requests = ">=2.25.0"
+snowballstemmer = ">=2.0"
+sphinxcontrib-applehelp = "*"
+sphinxcontrib-devhelp = "*"
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+sphinxcontrib-jsmath = "*"
+sphinxcontrib-qthelp = "*"
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+optional = false
+python-versions = ">=3.9"
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+
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+description = "The little ASGI library that shines."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
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+typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
+
+[[package]]
+name = "stevedore"
+version = "5.2.0"
+description = "Manage dynamic plugins for Python applications"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+[package.dependencies]
+pbr = ">=2.0.0,<2.1.0 || >2.1.0"
+
 [[package]]
 name = "sympy"
 version = "1.12"
@@ -2110,14 +3259,14 @@ files = [
 
 [[package]]
 name = "tokenize-rt"
-version = "6.2.0"
+version = "5.2.0"
 description = "A wrapper around the stdlib `tokenize` which roundtrips."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["dev"]
 files = [
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+    {file = "tokenize_rt-5.2.0-py2.py3-none-any.whl", hash = "sha256:b79d41a65cfec71285433511b50271b05da3584a1da144a0752e9c621a285289"},
+    {file = "tokenize_rt-5.2.0.tar.gz", hash = "sha256:9fe80f8a5c1edad2d3ede0f37481cc0cc1538a2f442c9c2f9e4feacd2792d054"},
 ]
 
 [[package]]
@@ -2251,6 +3400,18 @@ files = [
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 ]
 
+[[package]]
+name = "tomlkit"
+version = "0.12.5"
+description = "Style preserving TOML library"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
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+    {file = "tomlkit-0.12.5.tar.gz", hash = "sha256:eef34fba39834d4d6b73c9ba7f3e4d1c417a4e56f89a7e96e090dd0d24b8fb3c"},
+]
+
 [[package]]
 name = "torch"
 version = "2.3.0"
@@ -2469,6 +3630,24 @@ typing-extensions = ">=4.10.0"
 doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.3.0)"]
 test = ["coverage[toml] (>=7)", "mypy (>=1.2.0) ; platform_python_implementation != \"PyPy\"", "pytest (>=7)"]
 
+[[package]]
+name = "typer"
+version = "0.12.3"
+description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
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+    {file = "typer-0.12.3.tar.gz", hash = "sha256:49e73131481d804288ef62598d97a1ceef3058905aa536a1134f90891ba35482"},
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+
+[package.dependencies]
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+rich = ">=10.11.0"
+shellingham = ">=1.3.0"
+typing-extensions = ">=3.7.4.3"
+
 [[package]]
 name = "types-requests"
 version = "2.32.0.20240523"
@@ -2498,14 +3677,14 @@ files = [
 
 [[package]]
 name = "tzdata"
-version = "2025.2"
+version = "2024.1"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 groups = ["main"]
 files = [
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+    {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
+    {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
 ]
 
 [[package]]
@@ -2526,6 +3705,26 @@ h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "uvicorn"
+version = "0.30.0"
+description = "The lightning-fast ASGI server."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+    {file = "uvicorn-0.30.0.tar.gz", hash = "sha256:f678dec4fa3a39706bbf49b9ec5fc40049d42418716cea52b53f07828a60aa37"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+h11 = ">=0.8"
+typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+standard = ["colorama (>=0.4) ; sys_platform == \"win32\"", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1) ; sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\"", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+
 [[package]]
 name = "virtualenv"
 version = "20.26.2"
@@ -2547,6 +3746,204 @@ platformdirs = ">=3.9.1,<5"
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
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+[[package]]
+name = "watchfiles"
+version = "0.22.0"
+description = "Simple, modern and high performance file watching and code reload in python."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
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+Pygments = {version = "*", optional = true, markers = "python_version >= \"3.5.0\" and extra == \"colors\""}
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+[package.extras]
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+tests = ["pytest (>=4.6.0) ; python_version < \"3.10.0\" and python_version >= \"3.7.0\"", "pytest (>=4.6.0) ; python_version < \"3.7.0\" and python_version >= \"3.6.0\"", "pytest (>=6.2.5) ; python_version >= \"3.10.0\"", "pytest-cov (>=3.0.0) ; python_version >= \"3.6.0\"", "typing (>=3.7.4) ; python_version <= \"3.4\""]
+tests-binary = ["cmake ; python_version < \"3.11\"", "cmake ; python_version < \"4.0\" and python_version >= \"3.11\"", "ninja ; python_version < \"3.11\"", "ninja ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 ; python_version < \"3.11\"", "pybind11 ; python_version < \"4.0\" and python_version >= \"3.11\"", "scikit-build ; python_version < \"3.11\"", "scikit-build ; python_version < \"4.0\" and python_version >= \"3.11\""]
+tests-binary-strict = ["cmake (==3.21.2) ; python_version < \"3.11\"", "cmake (==3.25.0) ; python_version < \"4.0\" and python_version >= \"3.11\"", "ninja (==1.10.2) ; python_version < \"3.11\"", "ninja (==1.11.1) ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 (==2.10.3) ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 (==2.7.1) ; python_version < \"3.11\"", "scikit-build (==0.11.1) ; python_version < \"3.11\"", "scikit-build (==0.16.1) ; python_version < \"4.0\" and python_version >= \"3.11\""]
+tests-strict = ["pytest (==4.6.0) ; python_version < \"3.10.0\" and python_version >= \"3.7.0\"", "pytest (==4.6.0) ; python_version < \"3.7.0\" and python_version >= \"3.6.0\"", "pytest (==6.2.5) ; python_version >= \"3.10.0\"", "pytest-cov (==3.0.0) ; python_version >= \"3.6.0\"", "typing (==3.7.4) ; python_version <= \"3.4\""]
+
 [[package]]
 name = "yarl"
 version = "1.9.4"
@@ -2658,7 +4055,7 @@ description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.9\""
+markers = "python_full_version < \"3.10.2\""
 files = [
     {file = "zipp-3.19.0-py3-none-any.whl", hash = "sha256:96dc6ad62f1441bcaccef23b274ec471518daf4fbbc580341204936a5a3dddec"},
     {file = "zipp-3.19.0.tar.gz", hash = "sha256:952df858fb3164426c976d9338d3961e8e8b3758e2e059e0f754b8c4262625ee"},
@@ -2670,5 +4067,5 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more
 
 [metadata]
 lock-version = "2.1"
-python-versions = ">=3.9,<4.0"
-content-hash = "41b9146c4a075dccea911a688d3b42819cdecf86459effc0f2b5073fc7d4db22"
+python-versions = "^3.9"
+content-hash = "e3abc1c30948dee05da1c096336758d976d1483f14fb0092bad1e0311792210e"
diff --git a/pyproject.toml b/pyproject.toml
index 4d91a0e4..05d381ea 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -44,6 +44,10 @@ 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
 

From 1266f40f4e88624a058407846a1b4a4fbafd6c0b Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 17:50:29 +0200
Subject: [PATCH 02/11] re-export annotations and documents from pie-modules

---
 src/pytorch_ie/annotations.py | 201 +++-------------------------------
 src/pytorch_ie/documents.py   | 193 +++++---------------------------
 2 files changed, 39 insertions(+), 355 deletions(-)

diff --git a/src/pytorch_ie/annotations.py b/src/pytorch_ie/annotations.py
index 91b877de..f219d788 100644
--- a/src/pytorch_ie/annotations.py
+++ b/src/pytorch_ie/annotations.py
@@ -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 imports for annotations
+from pie_modules.annotations import (
+    BinaryRelation,
+    Label,
+    LabeledMultiSpan,
+    LabeledSpan,
+    MultiLabel,
+    MultiLabeledBinaryRelation,
+    MultiLabeledSpan,
+    MultiSpan,
+    NaryRelation,
+    Span,
+)
diff --git a/src/pytorch_ie/documents.py b/src/pytorch_ie/documents.py
index f1f0076b..8475c263 100644
--- a/src/pytorch_ie/documents.py
+++ b/src/pytorch_ie/documents.py
@@ -1,171 +1,30 @@
-import dataclasses
-from typing import Any, Dict, Optional, Tuple
-
-from pie_core import AnnotationLayer, Document, annotation_field
-from typing_extensions import TypeAlias
-
-from pytorch_ie.annotations import (
-    BinaryRelation,
-    Label,
-    LabeledMultiSpan,
-    LabeledSpan,
-    MultiLabel,
-    Span,
+from pie_modules.documents import (
+    DocumentWithLabel,
+    DocumentWithMultiLabel,
+    TextBasedDocument,
+    TextDocumentWithLabel,
+    TextDocumentWithLabeledMultiSpans,
+    TextDocumentWithLabeledMultiSpansAndBinaryRelations,
+    TextDocumentWithLabeledMultiSpansAndLabeledPartitions,
+    TextDocumentWithLabeledMultiSpansBinaryRelationsAndLabeledPartitions,
+    TextDocumentWithLabeledPartitions,
+    TextDocumentWithLabeledSpans,
+    TextDocumentWithLabeledSpansAndBinaryRelations,
+    TextDocumentWithLabeledSpansAndLabeledPartitions,
+    TextDocumentWithLabeledSpansAndSentences,
+    TextDocumentWithLabeledSpansBinaryRelationsAndLabeledPartitions,
+    TextDocumentWithMultiLabel,
+    TextDocumentWithSentences,
+    TextDocumentWithSpans,
+    TextDocumentWithSpansAndBinaryRelations,
+    TextDocumentWithSpansAndLabeledPartitions,
+    TextDocumentWithSpansBinaryRelationsAndLabeledPartitions,
+    TokenBasedDocument,
+    WithMetadata,
+    WithText,
+    WithTokens,
 )
-
-
-@dataclasses.dataclass
-class WithMetadata:
-    id: Optional[str] = None
-    metadata: Dict[str, Any] = dataclasses.field(default_factory=dict)
-
-
-@dataclasses.dataclass
-class WithTokens:
-    tokens: Tuple[str, ...]
-
-
-@dataclasses.dataclass
-class WithText:
-    text: str
-
-
-@dataclasses.dataclass
-class TextBasedDocument(WithMetadata, WithText, Document):
-    pass
-
-
-@dataclasses.dataclass
-class TokenBasedDocument(WithMetadata, WithTokens, Document):
-    def __post_init__(self) -> None:
-
-        # When used in a dataset, the document gets serialized to json like structure which does not know tuples,
-        # so they get converted to lists. This is a workaround to automatically convert the "tokens" back to tuples
-        # when the document is created from a dataset.
-        if isinstance(self.tokens, list):
-            object.__setattr__(self, "tokens", tuple(self.tokens))
-        elif not isinstance(self.tokens, tuple):
-            raise ValueError("tokens must be a tuple.")
-
-        # Call the default document construction code
-        super().__post_init__()
-
+from typing_extensions import TypeAlias
 
 # backwards compatibility
 TextDocument: TypeAlias = TextBasedDocument
-
-
-@dataclasses.dataclass
-class DocumentWithLabel(Document):
-    label: AnnotationLayer[Label] = annotation_field()
-
-
-@dataclasses.dataclass
-class DocumentWithMultiLabel(Document):
-    label: AnnotationLayer[MultiLabel] = annotation_field()
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabel(DocumentWithLabel, TextBasedDocument):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithMultiLabel(DocumentWithMultiLabel, TextBasedDocument):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledPartitions(TextBasedDocument):
-    labeled_partitions: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
-
-
-@dataclasses.dataclass
-class TextDocumentWithSentences(TextBasedDocument):
-    sentences: AnnotationLayer[Span] = annotation_field(target="text")
-
-
-@dataclasses.dataclass
-class TextDocumentWithSpans(TextBasedDocument):
-    spans: AnnotationLayer[Span] = annotation_field(target="text")
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledSpans(TextBasedDocument):
-    labeled_spans: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledSpansAndLabeledPartitions(
-    TextDocumentWithLabeledSpans, TextDocumentWithLabeledPartitions
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledSpansAndSentences(
-    TextDocumentWithLabeledSpans, TextDocumentWithSentences
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledSpansAndBinaryRelations(TextDocumentWithLabeledSpans):
-    binary_relations: AnnotationLayer[BinaryRelation] = annotation_field(target="labeled_spans")
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledSpansBinaryRelationsAndLabeledPartitions(
-    TextDocumentWithLabeledSpansAndLabeledPartitions,
-    TextDocumentWithLabeledSpansAndBinaryRelations,
-    TextDocumentWithLabeledPartitions,
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithSpansAndBinaryRelations(TextDocumentWithSpans):
-    binary_relations: AnnotationLayer[BinaryRelation] = annotation_field(target="spans")
-
-
-@dataclasses.dataclass
-class TextDocumentWithSpansAndLabeledPartitions(
-    TextDocumentWithSpans, TextDocumentWithLabeledPartitions
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithSpansBinaryRelationsAndLabeledPartitions(
-    TextDocumentWithSpansAndLabeledPartitions,
-    TextDocumentWithSpansAndBinaryRelations,
-    TextDocumentWithLabeledPartitions,
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledMultiSpans(TextBasedDocument):
-    labeled_multi_spans: AnnotationLayer[LabeledMultiSpan] = annotation_field(target="text")
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledMultiSpansAndLabeledPartitions(
-    TextDocumentWithLabeledMultiSpans, TextDocumentWithLabeledPartitions
-):
-    pass
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledMultiSpansAndBinaryRelations(TextDocumentWithLabeledMultiSpans):
-    binary_relations: AnnotationLayer[BinaryRelation] = annotation_field(
-        target="labeled_multi_spans"
-    )
-
-
-@dataclasses.dataclass
-class TextDocumentWithLabeledMultiSpansBinaryRelationsAndLabeledPartitions(
-    TextDocumentWithLabeledMultiSpansAndLabeledPartitions,
-    TextDocumentWithLabeledMultiSpansAndBinaryRelations,
-):
-    pass

From 7eddad2272df7f5a77b74d2c969c55304cc4f5e4 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:09:13 +0200
Subject: [PATCH 03/11] minors

---
 src/pytorch_ie/annotations.py | 2 +-
 src/pytorch_ie/documents.py   | 1 +
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/pytorch_ie/annotations.py b/src/pytorch_ie/annotations.py
index f219d788..3cfa66b0 100644
--- a/src/pytorch_ie/annotations.py
+++ b/src/pytorch_ie/annotations.py
@@ -1,4 +1,4 @@
-# backward compatibility imports for annotations
+# backward compatibility
 from pie_modules.annotations import (
     BinaryRelation,
     Label,
diff --git a/src/pytorch_ie/documents.py b/src/pytorch_ie/documents.py
index 8475c263..4b5509e2 100644
--- a/src/pytorch_ie/documents.py
+++ b/src/pytorch_ie/documents.py
@@ -1,3 +1,4 @@
+# backwards compatibility
 from pie_modules.documents import (
     DocumentWithLabel,
     DocumentWithMultiLabel,

From 2c0c2a3c2dc5c5e52739c9590d10589e9fb44e17 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:13:18 +0200
Subject: [PATCH 04/11] remove metrics and statistics (except
 TokenCountCollector), but import them from `pie-modules`; fix
 test_confusion_matrix

---
 src/pytorch_ie/metrics/__init__.py            |   6 +-
 src/pytorch_ie/metrics/confusion_matrix.py    | 157 ------------------
 src/pytorch_ie/metrics/f1.py                  | 153 -----------------
 src/pytorch_ie/metrics/statistics.py          | 135 ---------------
 src/pytorch_ie/metrics/statistics/__init__.py |   8 +
 .../statistics/token_count_collector.py       |  40 +++++
 tests/metrics/test_confusion_matrix.py        |   4 +-
 7 files changed, 52 insertions(+), 451 deletions(-)
 delete mode 100644 src/pytorch_ie/metrics/confusion_matrix.py
 delete mode 100644 src/pytorch_ie/metrics/f1.py
 delete mode 100644 src/pytorch_ie/metrics/statistics.py
 create mode 100644 src/pytorch_ie/metrics/statistics/__init__.py
 create mode 100644 src/pytorch_ie/metrics/statistics/token_count_collector.py

diff --git a/src/pytorch_ie/metrics/__init__.py b/src/pytorch_ie/metrics/__init__.py
index 49b3a056..1ded4fd8 100644
--- a/src/pytorch_ie/metrics/__init__.py
+++ b/src/pytorch_ie/metrics/__init__.py
@@ -1,4 +1,2 @@
-from .confusion_matrix import ConfusionMatrix
-from .f1 import F1Metric
-
-__all__ = ["F1Metric", "ConfusionMatrix"]
+# backwards compatibility
+from pie_modules.metrics import ConfusionMatrix, F1Metric, SQuADF1
diff --git a/src/pytorch_ie/metrics/confusion_matrix.py b/src/pytorch_ie/metrics/confusion_matrix.py
deleted file mode 100644
index 4d1df92a..00000000
--- a/src/pytorch_ie/metrics/confusion_matrix.py
+++ /dev/null
@@ -1,157 +0,0 @@
-import logging
-from collections import defaultdict
-from typing import Callable, Dict, Optional, Tuple, Union
-
-import pandas as pd
-from pie_core import Annotation, Document, DocumentMetric
-
-from pytorch_ie.utils.hydra import resolve_target
-
-logger = logging.getLogger(__name__)
-
-
-class ConfusionMatrix(DocumentMetric):
-    """Computes the confusion matrix for a given annotation layer that contains labeled annotations.
-
-    Args:
-        layer: The layer to compute the confusion matrix for.
-        label_field: The field to use for the label. Defaults to "label".
-        unassignable_label: The label to use for false negative annotations. Defaults to "UNASSIGNABLE".
-        undetected_label: The label to use for false positive annotations. Defaults to "UNDETECTED".
-        strict: If True, raises an error if a base annotation has multiple gold labels. If False, logs a warning.
-        show_as_markdown: If True, logs the confusion matrix as markdown on the console when calling compute().
-        annotation_processor: A callable that processes the annotations before calculating the confusion matrix.
-    """
-
-    def __init__(
-        self,
-        layer: str,
-        label_field: str = "label",
-        show_as_markdown: bool = False,
-        unassignable_label: str = "UNASSIGNABLE",
-        undetected_label: str = "UNDETECTED",
-        strict: bool = True,
-        annotation_processor: Optional[Union[Callable[[Annotation], Annotation], str]] = None,
-    ):
-        super().__init__()
-        self.layer = layer
-        self.label_field = label_field
-        self.unassignable_label = unassignable_label
-        self.undetected_label = undetected_label
-        self.strict = strict
-        self.show_as_markdown = show_as_markdown
-        self.annotation_processor: Optional[Callable[[Annotation], Annotation]]
-        if isinstance(annotation_processor, str):
-            self.annotation_processor = resolve_target(annotation_processor)
-        else:
-            self.annotation_processor = annotation_processor
-
-    def reset(self):
-        self.counts: Dict[Tuple[str, str], int] = defaultdict(int)
-
-    def calculate_counts(
-        self,
-        document: Document,
-        annotation_filter: Optional[Callable[[Annotation], bool]] = None,
-        annotation_processor: Optional[Callable[[Annotation], Annotation]] = None,
-    ) -> Dict[Tuple[str, str], int]:
-        annotation_processor = annotation_processor or (lambda ann: ann)
-        annotation_filter = annotation_filter or (lambda ann: True)
-        predicted_annotations = {
-            annotation_processor(ann)
-            for ann in document[self.layer].predictions
-            if annotation_filter(ann)
-        }
-        gold_annotations = {
-            annotation_processor(ann) for ann in document[self.layer] if annotation_filter(ann)
-        }
-        base2gold = defaultdict(list)
-        for ann in gold_annotations:
-            base_ann_kwargs = {self.label_field: "DUMMY_LABEL"}
-            base_ann = ann.copy(**base_ann_kwargs)
-            base2gold[base_ann].append(ann)
-        base2pred = defaultdict(list)
-        for ann in predicted_annotations:
-            base_ann_kwargs = {self.label_field: "DUMMY_LABEL"}
-            base_ann = ann.copy(**base_ann_kwargs)
-            base2pred[base_ann].append(ann)
-
-        # (gold_label, pred_label) -> count
-        counts: Dict[Tuple[str, str], int] = defaultdict(int)
-        for base_ann in set(base2gold) | set(base2pred):
-            gold_labels = [getattr(ann, self.label_field) for ann in base2gold[base_ann]]
-            pred_labels = [getattr(ann, self.label_field) for ann in base2pred[base_ann]]
-
-            if self.undetected_label in gold_labels:
-                raise ValueError(
-                    f"The gold annotation has the label '{self.undetected_label}' for undetected instances. "
-                    f"Set a different undetected_label."
-                )
-            if self.unassignable_label in pred_labels:
-                raise ValueError(
-                    f"The predicted annotation has the label '{self.unassignable_label}' for unassignable predictions. "
-                    f"Set a different unassignable_label."
-                )
-
-            if len(gold_labels) > 1:
-                msg = f"The base annotation {base_ann} has multiple gold labels: {gold_labels}."
-                if self.strict:
-                    raise ValueError(msg)
-                else:
-                    logger.warning(msg + " Skip this base annotation.")
-                    continue
-
-            # use placeholder labels for empty gold or prediction labels
-            if len(gold_labels) == 0:
-                gold_labels.append(self.undetected_label)
-            if len(pred_labels) == 0:
-                pred_labels.append(self.unassignable_label)
-
-            # main logic
-            for gold_label in gold_labels:
-                for pred_label in pred_labels:
-                    counts[(gold_label, pred_label)] += 1
-
-        return counts
-
-    def add_counts(self, counts: Dict[Tuple[str, str], int]):
-        for key, value in counts.items():
-            self.counts[key] += value
-
-    def _update(self, document: Document):
-        new_counts = self.calculate_counts(
-            document=document,
-            annotation_processor=self.annotation_processor,
-        )
-        self.add_counts(new_counts)
-
-    def _compute(self) -> Dict[str, Dict[str, int]]:
-
-        res: Dict[str, Dict[str, int]] = defaultdict(dict)
-        for gold_label, pred_label in sorted(self.counts):
-            res[gold_label][pred_label] = self.counts[(gold_label, pred_label)]
-
-        if self.show_as_markdown:
-            res_df = pd.DataFrame(res).fillna(0)
-            # index is prediction, columns is gold
-            gold_labels = res_df.columns
-            pred_labels = res_df.index
-
-            # re-arrange index and columns: sort and put undetected_label and unassignable_label at the end
-            gold_labels_sorted = sorted(
-                [gold_label for gold_label in gold_labels if gold_label != self.undetected_label]
-            )
-            # re-add undetected_label at the end, if it was in the gold labels
-            if self.undetected_label in gold_labels:
-                gold_labels_sorted = gold_labels_sorted + [self.undetected_label]
-            pred_labels_sorted = sorted(
-                [pred_label for pred_label in pred_labels if pred_label != self.unassignable_label]
-            )
-            # re-add unassignable_label at the end, if it was in the pred labels
-            if self.unassignable_label in pred_labels:
-                pred_labels_sorted = pred_labels_sorted + [self.unassignable_label]
-            res_df_sorted = res_df.loc[pred_labels_sorted, gold_labels_sorted]
-
-            # transpose and show as markdown: index is now gold, columns is prediction
-            logger.info(f"\n{self.layer}:\n{res_df_sorted.T.to_markdown()}")
-        return res
diff --git a/src/pytorch_ie/metrics/f1.py b/src/pytorch_ie/metrics/f1.py
deleted file mode 100644
index 7d4a02e8..00000000
--- a/src/pytorch_ie/metrics/f1.py
+++ /dev/null
@@ -1,153 +0,0 @@
-import logging
-from collections import defaultdict
-from functools import partial
-from typing import Callable, Collection, Dict, Hashable, Optional, Tuple, Union
-
-import pandas as pd
-from pie_core import Annotation, Document, DocumentMetric
-
-from pytorch_ie.utils.hydra import resolve_target
-
-logger = logging.getLogger(__name__)
-
-
-def has_one_of_the_labels(ann: Annotation, label_field: str, labels: Collection[str]) -> bool:
-    return getattr(ann, label_field) in labels
-
-
-def has_this_label(ann: Annotation, label_field: str, label: str) -> bool:
-    return getattr(ann, label_field) == label
-
-
-class F1Metric(DocumentMetric):
-    """Computes the (micro aggregated) F1 score for a given layer. If labels are provided,
-    it also computes the F1 score for each label separately and the macro F1 score.
-
-    Args:
-        layer: The layer to compute the F1 score for.
-        labels: If provided, calculate F1 score for each label.
-        label_field: The field to use for the label. Defaults to "label".
-        show_as_markdown: If True, logs the F1 score as markdown on the console when calling compute().
-    """
-
-    def __init__(
-        self,
-        layer: str,
-        labels: Optional[Union[Collection[str], str]] = None,
-        label_field: str = "label",
-        show_as_markdown: bool = False,
-        annotation_processor: Optional[Union[Callable[[Annotation], Hashable], str]] = None,
-    ):
-        super().__init__()
-        self.layer = layer
-        self.label_field = label_field
-        self.show_as_markdown = show_as_markdown
-        self.annotation_processor: Optional[Callable[[Annotation], Hashable]]
-        if isinstance(annotation_processor, str):
-            self.annotation_processor = resolve_target(annotation_processor)
-        else:
-            self.annotation_processor = annotation_processor
-
-        self.per_label = labels is not None
-        self.infer_labels = False
-        if self.per_label:
-            if isinstance(labels, str):
-                if labels != "INFERRED":
-                    raise ValueError(
-                        "labels can only be 'INFERRED' if per_label is True and labels is a string"
-                    )
-                self.labels = []
-                self.infer_labels = True
-            elif isinstance(labels, Collection):
-                if not all(isinstance(label, str) for label in labels):
-                    raise ValueError("labels must be a collection of strings")
-                if "MICRO" in labels or "MACRO" in labels:
-                    raise ValueError(
-                        "labels cannot contain 'MICRO' or 'MACRO' because they are used to capture aggregated metrics"
-                    )
-                if len(labels) == 0:
-                    raise ValueError("labels cannot be empty")
-                self.labels = list(labels)
-            else:
-                raise ValueError("labels must be a string or a collection of strings")
-
-    def reset(self):
-        self.counts = defaultdict(lambda: (0, 0, 0))
-
-    def calculate_counts(
-        self,
-        document: Document,
-        annotation_filter: Optional[Callable[[Annotation], bool]] = None,
-        annotation_processor: Optional[Callable[[Annotation], Hashable]] = None,
-    ) -> Tuple[int, int, int]:
-        annotation_processor = annotation_processor or (lambda ann: ann)
-        annotation_filter = annotation_filter or (lambda ann: True)
-        predicted_annotations = {
-            annotation_processor(ann)
-            for ann in document[self.layer].predictions
-            if annotation_filter(ann)
-        }
-        gold_annotations = {
-            annotation_processor(ann) for ann in document[self.layer] if annotation_filter(ann)
-        }
-        tp = len([ann for ann in predicted_annotations & gold_annotations])
-        fn = len([ann for ann in gold_annotations - predicted_annotations])
-        fp = len([ann for ann in predicted_annotations - gold_annotations])
-        return tp, fp, fn
-
-    def add_counts(self, counts: Tuple[int, int, int], label: str):
-        self.counts[label] = (
-            self.counts[label][0] + counts[0],
-            self.counts[label][1] + counts[1],
-            self.counts[label][2] + counts[2],
-        )
-
-    def _update(self, document: Document):
-        new_counts = self.calculate_counts(
-            document=document,
-            annotation_filter=(
-                partial(has_one_of_the_labels, label_field=self.label_field, labels=self.labels)
-                if self.per_label and not self.infer_labels
-                else None
-            ),
-            annotation_processor=self.annotation_processor,
-        )
-        self.add_counts(new_counts, label="MICRO")
-        if self.infer_labels:
-            layer = document[self.layer]
-            # collect labels from gold data and predictions
-            for ann in list(layer) + list(layer.predictions):
-                label = getattr(ann, self.label_field)
-                if label not in self.labels:
-                    self.labels.append(label)
-        if self.per_label:
-            for label in self.labels:
-                new_counts = self.calculate_counts(
-                    document=document,
-                    annotation_filter=partial(
-                        has_this_label, label_field=self.label_field, label=label
-                    ),
-                    annotation_processor=self.annotation_processor,
-                )
-                self.add_counts(new_counts, label=label)
-
-    def _compute(self) -> Dict[str, Dict[str, float]]:
-        res = dict()
-        if self.per_label:
-            res["MACRO"] = {"f1": 0.0, "p": 0.0, "r": 0.0}
-        for label, counts in self.counts.items():
-            tp, fp, fn = counts
-            if tp == 0:
-                p, r, f1 = 0.0, 0.0, 0.0
-            else:
-                p = tp / (tp + fp)
-                r = tp / (tp + fn)
-                f1 = 2 * p * r / (p + r)
-            res[label] = {"f1": f1, "p": p, "r": r, "s": tp + fn}
-            if self.per_label and label in self.labels:
-                res["MACRO"]["f1"] += f1 / len(self.labels)
-                res["MACRO"]["p"] += p / len(self.labels)
-                res["MACRO"]["r"] += r / len(self.labels)
-        if self.show_as_markdown:
-            logger.info(f"\n{self.layer}:\n{pd.DataFrame(res).round(3).T.to_markdown()}")
-        return res
diff --git a/src/pytorch_ie/metrics/statistics.py b/src/pytorch_ie/metrics/statistics.py
deleted file mode 100644
index b4a9c134..00000000
--- a/src/pytorch_ie/metrics/statistics.py
+++ /dev/null
@@ -1,135 +0,0 @@
-import logging
-from collections import defaultdict
-from typing import Any, Callable, Dict, List, Optional, Type, Union
-
-from pie_core import Document, DocumentStatistic
-from transformers import AutoTokenizer, PreTrainedTokenizer
-
-from pytorch_ie.documents import TextBasedDocument
-
-logger = logging.getLogger(__name__)
-
-
-class TokenCountCollector(DocumentStatistic):
-    """Collects the token count of a field when tokenizing its content with a Huggingface
-    tokenizer.
-
-    The content of the field should be a string.
-    """
-
-    def __init__(
-        self,
-        tokenizer: Union[str, PreTrainedTokenizer],
-        text_field: str = "text",
-        tokenizer_kwargs: Optional[Dict[str, Any]] = None,
-        document_type: Optional[Type[Document]] = None,
-        **kwargs,
-    ):
-        if document_type is None and text_field == "text":
-            document_type = TextBasedDocument
-        super().__init__(document_type=document_type, **kwargs)
-        self.tokenizer = (
-            AutoTokenizer.from_pretrained(tokenizer) if isinstance(tokenizer, str) else tokenizer
-        )
-        self.tokenizer_kwargs = tokenizer_kwargs or {}
-        self.text_field = text_field
-
-    def _collect(self, doc: Document) -> int:
-        text = getattr(doc, self.text_field)
-        encodings = self.tokenizer(text, **self.tokenizer_kwargs)
-        tokens = encodings.tokens()
-        return len(tokens)
-
-
-class FieldLengthCollector(DocumentStatistic):
-    """Collects the length of a field, e.g. to collect the number the characters in the input text.
-
-    The field should be a list of sized elements.
-    """
-
-    def __init__(self, field: str, **kwargs):
-        super().__init__(**kwargs)
-        self.field = field
-
-    def _collect(self, doc: Document) -> int:
-        field_obj = getattr(doc, self.field)
-        return len(field_obj)
-
-
-class SubFieldLengthCollector(DocumentStatistic):
-    """Collects the length of a subfield in a field, e.g. to collect the number of arguments of
-    N-ary relations."""
-
-    def __init__(self, field: str, subfield: str, **kwargs):
-        super().__init__(**kwargs)
-        self.field = field
-        self.subfield = subfield
-
-    def _collect(self, doc: Document) -> List[int]:
-        field_obj = getattr(doc, self.field)
-        lengths = []
-        for entry in field_obj:
-            subfield_obj = getattr(entry, self.subfield)
-            lengths.append(len(subfield_obj))
-        return lengths
-
-
-class DummyCollector(DocumentStatistic):
-    """A dummy collector that always returns 1, e.g. to count the number of documents.
-
-    Can be used to count the number of documents.
-    """
-
-    DEFAULT_AGGREGATION_FUNCTIONS = ["sum"]
-
-    def _collect(self, doc: Document) -> int:
-        return 1
-
-
-class LabelCountCollector(DocumentStatistic):
-    """Collects the number of field entries per label, e.g. to collect the number of entities per
-    type.
-
-    The field should be a list of elements with a label attribute.
-
-    Important: To make correct use of the result data, missing values need to be filled with 0, e.g.:
-        {("ORG",): [2, 3], ("LOC",): [2]} -> {("ORG",): [2, 3], ("LOC",): [2, 0]}
-    """
-
-    DEFAULT_AGGREGATION_FUNCTIONS = ["mean", "std", "min", "max", "len", "sum"]
-
-    def __init__(
-        self, field: str, labels: Union[List[str], str], label_attribute: str = "label", **kwargs
-    ):
-        super().__init__(**kwargs)
-        self.field = field
-        self.label_attribute = label_attribute
-        if not (isinstance(labels, list) or labels == "INFERRED"):
-            raise ValueError("labels must be a list of strings or 'INFERRED'")
-        if labels == "INFERRED":
-            logger.warning(
-                f"Inferring labels with {self.__class__.__name__} from data produces wrong results "
-                f"for certain aggregation functions (e.g. 'mean', 'std', 'min') because zero values "
-                f"are not included in the calculation. We remove these aggregation functions from "
-                f"this collector, but be aware that the results may be wrong for your own aggregation "
-                f"functions that rely on zero values."
-            )
-            self.aggregation_functions: Dict[str, Callable[[List], Any]] = {
-                name: func
-                for name, func in self.aggregation_functions.items()
-                if name not in ["mean", "std", "min"]
-            }
-
-        self.labels = labels
-
-    def _collect(self, doc: Document) -> Dict[str, int]:
-        field_obj = getattr(doc, self.field)
-        counts: Dict[str, int]
-        if self.labels == "INFERRED":
-            counts = defaultdict(int)
-        else:
-            counts = {label: 0 for label in self.labels}
-        for elem in field_obj:
-            label = getattr(elem, self.label_attribute)
-            counts[label] += 1
-        return dict(counts)
diff --git a/src/pytorch_ie/metrics/statistics/__init__.py b/src/pytorch_ie/metrics/statistics/__init__.py
new file mode 100644
index 00000000..d2acb1d3
--- /dev/null
+++ b/src/pytorch_ie/metrics/statistics/__init__.py
@@ -0,0 +1,8 @@
+from pie_modules.metrics.statistics import (
+    DummyCollector,
+    FieldLengthCollector,
+    LabelCountCollector,
+    SubFieldLengthCollector,
+)
+
+from .token_count_collector import TokenCountCollector
diff --git a/src/pytorch_ie/metrics/statistics/token_count_collector.py b/src/pytorch_ie/metrics/statistics/token_count_collector.py
new file mode 100644
index 00000000..91545a84
--- /dev/null
+++ b/src/pytorch_ie/metrics/statistics/token_count_collector.py
@@ -0,0 +1,40 @@
+import logging
+from typing import Any, Dict, Optional, Type, Union
+
+from pie_core import Document, DocumentStatistic
+from transformers import AutoTokenizer, PreTrainedTokenizer
+
+from pytorch_ie.documents import TextBasedDocument
+
+logger = logging.getLogger(__name__)
+
+
+class TokenCountCollector(DocumentStatistic):
+    """Collects the token count of a field when tokenizing its content with a Huggingface
+    tokenizer.
+
+    The content of the field should be a string.
+    """
+
+    def __init__(
+        self,
+        tokenizer: Union[str, PreTrainedTokenizer],
+        text_field: str = "text",
+        tokenizer_kwargs: Optional[Dict[str, Any]] = None,
+        document_type: Optional[Type[Document]] = None,
+        **kwargs,
+    ):
+        if document_type is None and text_field == "text":
+            document_type = TextBasedDocument
+        super().__init__(document_type=document_type, **kwargs)
+        self.tokenizer = (
+            AutoTokenizer.from_pretrained(tokenizer) if isinstance(tokenizer, str) else tokenizer
+        )
+        self.tokenizer_kwargs = tokenizer_kwargs or {}
+        self.text_field = text_field
+
+    def _collect(self, doc: Document) -> int:
+        text = getattr(doc, self.text_field)
+        encodings = self.tokenizer(text, **self.tokenizer_kwargs)
+        tokens = encodings.tokens()
+        return len(tokens)
diff --git a/tests/metrics/test_confusion_matrix.py b/tests/metrics/test_confusion_matrix.py
index cf09d6c4..5466bacc 100644
--- a/tests/metrics/test_confusion_matrix.py
+++ b/tests/metrics/test_confusion_matrix.py
@@ -50,11 +50,11 @@ def test_confusion_matrix(documents):
     assert dict(metric.counts) == {
         ("animal", "animal"): 1,
         ("animal", "cat"): 1,
-        ("UNDETECTED", "company"): 1,
+        ("UNASSIGNABLE", "company"): 1,
         ("company", "company"): 1,
     }
     assert metric.compute() == {
         "animal": {"animal": 1, "cat": 1},
-        "UNDETECTED": {"company": 1},
+        "UNASSIGNABLE": {"company": 1},
         "company": {"company": 1},
     }

From ca557674c90b20e1b09d29fe4bb18a83788b409c Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:21:43 +0200
Subject: [PATCH 05/11] minor

---
 src/pytorch_ie/utils/hydra.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/pytorch_ie/utils/hydra.py b/src/pytorch_ie/utils/hydra.py
index 23bb51f6..2c3d562b 100644
--- a/src/pytorch_ie/utils/hydra.py
+++ b/src/pytorch_ie/utils/hydra.py
@@ -1,3 +1,4 @@
+# backwards compatibility
 from pie_core.utils.hydra import (
     InstantiationException,
     resolve_optional_document_type,

From 8c7630830d3d48bb716f0d35478e04ef8b8105b8 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:23:23 +0200
Subject: [PATCH 06/11] remove tests for removed metrics and statistics

---
 tests/metrics/test_confusion_matrix.py |  60 ------------
 tests/metrics/test_f1.py               | 128 -------------------------
 tests/metrics/test_statistics.py       |  74 +-------------
 3 files changed, 1 insertion(+), 261 deletions(-)
 delete mode 100644 tests/metrics/test_confusion_matrix.py
 delete mode 100644 tests/metrics/test_f1.py

diff --git a/tests/metrics/test_confusion_matrix.py b/tests/metrics/test_confusion_matrix.py
deleted file mode 100644
index 5466bacc..00000000
--- a/tests/metrics/test_confusion_matrix.py
+++ /dev/null
@@ -1,60 +0,0 @@
-from dataclasses import dataclass
-
-import pytest
-from pie_core import AnnotationLayer, annotation_field
-
-from pytorch_ie.annotations import LabeledSpan
-from pytorch_ie.documents import TextBasedDocument
-from pytorch_ie.metrics import ConfusionMatrix
-
-
-@pytest.fixture
-def documents():
-    @dataclass
-    class TextDocumentWithEntities(TextBasedDocument):
-        entities: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
-
-    # a test sentence with two entities
-    doc1 = TextDocumentWithEntities(
-        text="The quick brown fox jumps over the lazy dog.",
-    )
-    doc1.entities.append(LabeledSpan(start=4, end=19, label="animal"))
-    doc1.entities.append(LabeledSpan(start=35, end=43, label="animal"))
-    assert str(doc1.entities[0]) == "quick brown fox"
-    assert str(doc1.entities[1]) == "lazy dog"
-
-    # a second test sentence with a different text and a single entity (a company)
-    doc2 = TextDocumentWithEntities(text="Apple is a great company.")
-    doc2.entities.append(LabeledSpan(start=0, end=5, label="company"))
-    assert str(doc2.entities[0]) == "Apple"
-
-    documents = [doc1, doc2]
-
-    # add predictions
-    # correct
-    documents[0].entities.predictions.append(LabeledSpan(start=4, end=19, label="animal"))
-    # wrong label
-    documents[0].entities.predictions.append(LabeledSpan(start=35, end=43, label="cat"))
-    # correct
-    documents[1].entities.predictions.append(LabeledSpan(start=0, end=5, label="company"))
-    # wrong span
-    documents[1].entities.predictions.append(LabeledSpan(start=10, end=15, label="company"))
-
-    return documents
-
-
-def test_confusion_matrix(documents):
-    metric = ConfusionMatrix(layer="entities")
-    metric(documents)
-    # (gold_label, predicted_label): count
-    assert dict(metric.counts) == {
-        ("animal", "animal"): 1,
-        ("animal", "cat"): 1,
-        ("UNASSIGNABLE", "company"): 1,
-        ("company", "company"): 1,
-    }
-    assert metric.compute() == {
-        "animal": {"animal": 1, "cat": 1},
-        "UNASSIGNABLE": {"company": 1},
-        "company": {"company": 1},
-    }
diff --git a/tests/metrics/test_f1.py b/tests/metrics/test_f1.py
deleted file mode 100644
index 5e6e5539..00000000
--- a/tests/metrics/test_f1.py
+++ /dev/null
@@ -1,128 +0,0 @@
-from dataclasses import dataclass
-
-import pytest
-from pie_core import AnnotationLayer, annotation_field
-
-from pytorch_ie.annotations import LabeledSpan
-from pytorch_ie.documents import TextBasedDocument
-from pytorch_ie.metrics import F1Metric
-
-
-@pytest.fixture
-def documents():
-    @dataclass
-    class TextDocumentWithEntities(TextBasedDocument):
-        entities: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
-
-    # a test sentence with two entities
-    doc1 = TextDocumentWithEntities(
-        text="The quick brown fox jumps over the lazy dog.",
-    )
-    doc1.entities.append(LabeledSpan(start=4, end=19, label="animal"))
-    doc1.entities.append(LabeledSpan(start=35, end=43, label="animal"))
-    assert str(doc1.entities[0]) == "quick brown fox"
-    assert str(doc1.entities[1]) == "lazy dog"
-
-    # a second test sentence with a different text and a single entity (a company)
-    doc2 = TextDocumentWithEntities(text="Apple is a great company.")
-    doc2.entities.append(LabeledSpan(start=0, end=5, label="company"))
-    assert str(doc2.entities[0]) == "Apple"
-
-    documents = [doc1, doc2]
-
-    # add predictions
-    # correct
-    documents[0].entities.predictions.append(LabeledSpan(start=4, end=19, label="animal"))
-    # correct, but duplicate, this should not be counted
-    documents[0].entities.predictions.append(LabeledSpan(start=4, end=19, label="animal"))
-    # correct
-    documents[0].entities.predictions.append(LabeledSpan(start=35, end=43, label="animal"))
-    # wrong label
-    documents[0].entities.predictions.append(LabeledSpan(start=35, end=43, label="cat"))
-    # correct
-    documents[1].entities.predictions.append(LabeledSpan(start=0, end=5, label="company"))
-    # wrong span
-    documents[1].entities.predictions.append(LabeledSpan(start=10, end=15, label="company"))
-
-    return documents
-
-
-def test_f1(documents):
-    metric = F1Metric(layer="entities")
-    metric(documents)
-    # tp, fp, fn for micro
-    assert dict(metric.counts) == {"MICRO": (3, 2, 0)}
-    assert metric.compute() == {"MICRO": {"f1": 0.7499999999999999, "p": 0.6, "r": 1.0, "s": 3}}
-
-
-def test_f1_per_label(documents):
-    metric = F1Metric(layer="entities", labels=["animal", "company", "cat"])
-    metric(documents)
-    # tp, fp, fn for micro and per label
-    assert dict(metric.counts) == {
-        "MICRO": (3, 2, 0),
-        "cat": (0, 1, 0),
-        "company": (1, 1, 0),
-        "animal": (2, 0, 0),
-    }
-    assert metric.compute() == {
-        "MACRO": {"f1": 0.5555555555555556, "p": 0.5, "r": 0.6666666666666666},
-        "MICRO": {"f1": 0.7499999999999999, "p": 0.6, "r": 1.0, "s": 3},
-        "animal": {"f1": 1.0, "p": 1.0, "r": 1.0, "s": 2},
-        "cat": {"f1": 0.0, "p": 0.0, "r": 0.0, "s": 0},
-        "company": {"f1": 0.6666666666666666, "p": 0.5, "r": 1.0, "s": 1},
-    }
-
-
-def test_f1_per_label_inferred(documents):
-    metric = F1Metric(layer="entities", labels="INFERRED")
-    metric(documents)
-    # tp, fp, fn for micro and per label
-    assert dict(metric.counts) == {
-        "MICRO": (3, 2, 0),
-        "animal": (2, 0, 0),
-        "company": (1, 1, 0),
-        "cat": (0, 1, 0),
-    }
-    assert metric.compute() == {
-        "MACRO": {"f1": 0.5555555555555556, "p": 0.5, "r": 0.6666666666666666},
-        "MICRO": {"f1": 0.7499999999999999, "p": 0.6, "r": 1.0, "s": 3},
-        "animal": {"f1": 1.0, "p": 1.0, "r": 1.0, "s": 2},
-        "cat": {"f1": 0.0, "p": 0.0, "r": 0.0, "s": 0},
-        "company": {"f1": 0.6666666666666666, "p": 0.5, "r": 1.0, "s": 1},
-    }
-
-
-def test_f1_per_label_no_labels(documents):
-    with pytest.raises(ValueError) as excinfo:
-        F1Metric(layer="entities", labels=[])
-    assert str(excinfo.value) == "labels cannot be empty"
-
-
-def test_f1_per_label_not_allowed():
-    with pytest.raises(ValueError) as excinfo:
-        F1Metric(layer="entities", labels=["animal", "MICRO"])
-    assert (
-        str(excinfo.value)
-        == "labels cannot contain 'MICRO' or 'MACRO' because they are used to capture aggregated metrics"
-    )
-
-
-# def test_f1_show_as_markdown(documents, caplog):
-#    metric = F1Metric(layer="entities", labels=["animal", "company", "cat"], show_as_markdown=True)
-#    metric(documents)
-#    caplog.set_level(logging.INFO)
-#    caplog.clear()
-#    metric.compute()
-#    assert len(caplog.records) == 1
-#    assert (
-#        caplog.records[0].message == "\n"
-#        "entities:\n"
-#        "|         |    f1 |   p |     r |\n"
-#        "|:--------|------:|----:|------:|\n"
-#        "| MACRO   | 0.556 | 0.5 | 0.667 |\n"
-#        "| MICRO   | 0.75  | 0.6 | 1     |\n"
-#        "| animal  | 1     | 1   | 1     |\n"
-#        "| company | 0.667 | 0.5 | 1     |\n"
-#        "| cat     | 0     | 0   | 0     |"
-#    )
diff --git a/tests/metrics/test_statistics.py b/tests/metrics/test_statistics.py
index 8035b462..d48dd767 100644
--- a/tests/metrics/test_statistics.py
+++ b/tests/metrics/test_statistics.py
@@ -1,76 +1,4 @@
-from pytorch_ie.metrics.statistics import (
-    DummyCollector,
-    FieldLengthCollector,
-    LabelCountCollector,
-    SubFieldLengthCollector,
-    TokenCountCollector,
-)
-
-
-def test_statistics(document_dataset):
-    statistic = DummyCollector()
-    values = statistic(document_dataset)
-    assert values == {"test": {"sum": 2}, "train": {"sum": 8}, "val": {"sum": 2}}
-
-    # note that we check for labels=["LOC", "PER", "ORG"], but the actual labels in the data are just ["PER", "ORG"]
-    statistic = LabelCountCollector(field="entities", labels=["LOC", "PER", "ORG"])
-    values = statistic(document_dataset)
-    assert values == {
-        "test": {
-            "LOC": {"mean": 0.0, "std": 0.0, "min": 0, "max": 0, "len": 2, "sum": 0},
-            "PER": {"mean": 0.5, "std": 0.5, "min": 0, "max": 1, "len": 2, "sum": 1},
-            "ORG": {"mean": 1.0, "std": 1.0, "min": 0, "max": 2, "len": 2, "sum": 2},
-        },
-        "val": {
-            "LOC": {"mean": 0.0, "std": 0.0, "min": 0, "max": 0, "len": 2, "sum": 0},
-            "PER": {"mean": 0.5, "std": 0.5, "min": 0, "max": 1, "len": 2, "sum": 1},
-            "ORG": {"mean": 1.0, "std": 1.0, "min": 0, "max": 2, "len": 2, "sum": 2},
-        },
-        "train": {
-            "LOC": {"mean": 0.0, "std": 0.0, "min": 0, "max": 0, "len": 8, "sum": 0},
-            "PER": {
-                "mean": 0.875,
-                "std": 0.5994789404140899,
-                "min": 0,
-                "max": 2,
-                "len": 8,
-                "sum": 7,
-            },
-            "ORG": {
-                "mean": 1.125,
-                "std": 0.7806247497997998,
-                "min": 0,
-                "max": 2,
-                "len": 8,
-                "sum": 9,
-            },
-        },
-    }
-
-    statistic = LabelCountCollector(field="entities", labels="INFERRED")
-    values = statistic(document_dataset)
-    assert values == {
-        "test": {"PER": {"max": 1, "len": 1, "sum": 1}, "ORG": {"max": 2, "len": 1, "sum": 2}},
-        "val": {"PER": {"max": 1, "len": 1, "sum": 1}, "ORG": {"max": 2, "len": 1, "sum": 2}},
-        "train": {"PER": {"max": 2, "len": 6, "sum": 7}, "ORG": {"max": 2, "len": 6, "sum": 9}},
-    }
-
-    statistic = FieldLengthCollector(field="text")
-    values = statistic(document_dataset)
-    assert values == {
-        "test": {"max": 51, "mean": 34.5, "min": 18, "std": 16.5},
-        "train": {"max": 54, "mean": 28.25, "min": 15, "std": 14.694812009685595},
-        "val": {"max": 51, "mean": 34.5, "min": 18, "std": 16.5},
-    }
-
-    # this is not super useful, we just collect the lengths of the labels, but it is enough to test the code
-    statistic = SubFieldLengthCollector(field="entities", subfield="label")
-    values = statistic(document_dataset)
-    assert values == {
-        "test": {"max": 3, "mean": 3.0, "min": 3, "std": 0.0},
-        "train": {"max": 3, "mean": 3.0, "min": 3, "std": 0.0},
-        "val": {"max": 3, "mean": 3.0, "min": 3, "std": 0.0},
-    }
+from pytorch_ie.metrics.statistics import TokenCountCollector
 
 
 def test_statistics_with_tokenize(document_dataset):

From 71496e205c70b8a6d463dbec99d3915779237e6b Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:25:51 +0200
Subject: [PATCH 07/11] remove tests for annotations

---
 tests/conftest.py         |  13 +-
 tests/test_annotations.py | 377 --------------------------------------
 2 files changed, 1 insertion(+), 389 deletions(-)
 delete mode 100644 tests/test_annotations.py

diff --git a/tests/conftest.py b/tests/conftest.py
index c6f71c97..5417bbc5 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,9 +1,8 @@
 import dataclasses
 import json
-from typing import Dict, Optional
 
 import pytest
-from pie_core import Annotation, AnnotationLayer, annotation_field
+from pie_core import AnnotationLayer, annotation_field
 
 from pytorch_ie.annotations import BinaryRelation, LabeledSpan, Span
 from pytorch_ie.documents import TextDocument
@@ -61,13 +60,3 @@ def documents(document_dataset):
 def test_documents(documents):
     assert len(documents) == 8
     assert all(isinstance(doc, TestDocument) for doc in documents)
-
-
-def _test_annotation_reconstruction(
-    annotation: Annotation, annotation_store: Optional[Dict[int, Annotation]] = None
-):
-    ann_str = json.dumps(annotation.asdict())
-    annotation_reconstructed = type(annotation).fromdict(
-        json.loads(ann_str), annotation_store=annotation_store
-    )
-    assert annotation_reconstructed == annotation
diff --git a/tests/test_annotations.py b/tests/test_annotations.py
deleted file mode 100644
index 03116aa9..00000000
--- a/tests/test_annotations.py
+++ /dev/null
@@ -1,377 +0,0 @@
-import dataclasses
-import re
-
-import pytest
-
-from pytorch_ie import AnnotationLayer, annotation_field
-from pytorch_ie.annotations import (
-    BinaryRelation,
-    Label,
-    LabeledMultiSpan,
-    LabeledSpan,
-    MultiLabel,
-    MultiLabeledBinaryRelation,
-    MultiLabeledSpan,
-    NaryRelation,
-    Span,
-)
-from pytorch_ie.documents import TextBasedDocument
-from tests.conftest import _test_annotation_reconstruction
-
-
-def test_label():
-    label1 = Label(label="label1")
-    assert label1.label == "label1"
-    assert label1.score == pytest.approx(1.0)
-    assert label1.resolve() == "label1"
-
-    label2 = Label(label="label2", score=0.5)
-    assert label2.label == "label2"
-    assert label2.score == pytest.approx(0.5)
-
-    assert label2.asdict() == {
-        "_id": label2._id,
-        "label": "label2",
-        "score": 0.5,
-    }
-
-    _test_annotation_reconstruction(label2)
-
-
-def test_multilabel():
-    multilabel1 = MultiLabel(label=("label1", "label2"))
-    assert multilabel1.label == ("label1", "label2")
-    assert multilabel1.score == pytest.approx((1.0, 1.0))
-    assert multilabel1.resolve() == ("label1", "label2")
-
-    multilabel2 = MultiLabel(label=("label3", "label4"), score=(0.4, 0.5))
-    assert multilabel2.label == ("label3", "label4")
-    assert multilabel2.score == pytest.approx((0.4, 0.5))
-
-    assert multilabel2.asdict() == {
-        "_id": multilabel2._id,
-        "label": ("label3", "label4"),
-        "score": (0.4, 0.5),
-    }
-
-    _test_annotation_reconstruction(multilabel2)
-
-    with pytest.raises(
-        ValueError, match=re.escape("Number of labels (2) and scores (3) must be equal.")
-    ):
-        MultiLabel(label=("label5", "label6"), score=(0.1, 0.2, 0.3))
-
-
-def test_span():
-    span = Span(start=1, end=2)
-    assert span.start == 1
-    assert span.end == 2
-
-    assert span.asdict() == {
-        "_id": span._id,
-        "start": 1,
-        "end": 2,
-    }
-
-    _test_annotation_reconstruction(span)
-
-    with pytest.raises(ValueError) as excinfo:
-        span.resolve()
-    assert str(excinfo.value) == "Span(start=1, end=2) is not attached to a target."
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[Span] = annotation_field(target="text")
-
-    doc = TestDocument(text="Hello, world!")
-    span = Span(start=7, end=12)
-    doc.spans.append(span)
-    assert span.resolve() == "world"
-
-
-def test_labeled_span():
-    labeled_span1 = LabeledSpan(start=1, end=2, label="label1")
-    assert labeled_span1.start == 1
-    assert labeled_span1.end == 2
-    assert labeled_span1.label == "label1"
-    assert labeled_span1.score == pytest.approx(1.0)
-
-    labeled_span2 = LabeledSpan(start=3, end=4, label="label2", score=0.5)
-    assert labeled_span2.start == 3
-    assert labeled_span2.end == 4
-    assert labeled_span2.label == "label2"
-    assert labeled_span2.score == pytest.approx(0.5)
-
-    assert labeled_span2.asdict() == {
-        "_id": labeled_span2._id,
-        "start": 3,
-        "end": 4,
-        "label": "label2",
-        "score": 0.5,
-    }
-
-    _test_annotation_reconstruction(labeled_span2)
-
-    with pytest.raises(ValueError) as excinfo:
-        labeled_span1.resolve()
-    assert (
-        str(excinfo.value)
-        == "LabeledSpan(start=1, end=2, label='label1', score=1.0) is not attached to a target."
-    )
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
-
-    doc = TestDocument(text="Hello, world!")
-    labeled_span = LabeledSpan(start=7, end=12, label="LOC")
-    doc.spans.append(labeled_span)
-    assert labeled_span.resolve() == ("LOC", "world")
-
-
-def test_multilabeled_span():
-    multilabeled_span1 = MultiLabeledSpan(start=1, end=2, label=("label1", "label2"))
-    assert multilabeled_span1.start == 1
-    assert multilabeled_span1.end == 2
-    assert multilabeled_span1.label == ("label1", "label2")
-    assert multilabeled_span1.score == pytest.approx((1.0, 1.0))
-
-    multilabeled_span2 = MultiLabeledSpan(
-        start=3, end=4, label=("label3", "label4"), score=(0.4, 0.5)
-    )
-    assert multilabeled_span2.start == 3
-    assert multilabeled_span2.end == 4
-    assert multilabeled_span2.label == ("label3", "label4")
-    assert multilabeled_span2.score == pytest.approx((0.4, 0.5))
-
-    assert multilabeled_span2.asdict() == {
-        "_id": multilabeled_span2._id,
-        "start": 3,
-        "end": 4,
-        "label": ("label3", "label4"),
-        "score": (0.4, 0.5),
-    }
-
-    _test_annotation_reconstruction(multilabeled_span2)
-
-    with pytest.raises(
-        ValueError, match=re.escape("Number of labels (2) and scores (3) must be equal.")
-    ):
-        MultiLabeledSpan(start=5, end=6, label=("label5", "label6"), score=(0.1, 0.2, 0.3))
-
-    with pytest.raises(ValueError) as excinfo:
-        multilabeled_span1.resolve()
-    assert (
-        str(excinfo.value)
-        == "MultiLabeledSpan(start=1, end=2, label=('label1', 'label2'), score=(1.0, 1.0)) is not attached to a target."
-    )
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[MultiLabeledSpan] = annotation_field(target="text")
-
-    doc = TestDocument(text="Hello, world!")
-    multilabeled_span = MultiLabeledSpan(start=7, end=12, label=("LOC", "ORG"))
-    doc.spans.append(multilabeled_span)
-    assert multilabeled_span.resolve() == (("LOC", "ORG"), "world")
-
-
-def test_labeled_multi_span():
-    labeled_multi_span1 = LabeledMultiSpan(slices=((1, 2), (3, 4)), label="label1")
-    assert labeled_multi_span1.slices == ((1, 2), (3, 4))
-    assert labeled_multi_span1.label == "label1"
-    assert labeled_multi_span1.score == pytest.approx(1.0)
-
-    labeled_multi_span2 = LabeledMultiSpan(
-        slices=((5, 6), (7, 8)),
-        label="label2",
-        score=0.5,
-    )
-    assert labeled_multi_span2.slices == ((5, 6), (7, 8))
-    assert labeled_multi_span2.label == "label2"
-    assert labeled_multi_span2.score == pytest.approx(0.5)
-
-    assert labeled_multi_span2.asdict() == {
-        "_id": labeled_multi_span2._id,
-        "slices": ((5, 6), (7, 8)),
-        "label": "label2",
-        "score": 0.5,
-    }
-
-    _test_annotation_reconstruction(labeled_multi_span2)
-
-
-def test_binary_relation():
-    head = Span(start=1, end=2)
-    tail = Span(start=3, end=4)
-
-    binary_relation1 = BinaryRelation(head=head, tail=tail, label="label1")
-    assert binary_relation1.head == head
-    assert binary_relation1.tail == tail
-    assert binary_relation1.label == "label1"
-    assert binary_relation1.score == pytest.approx(1.0)
-
-    binary_relation2 = BinaryRelation(head=head, tail=tail, label="label2", score=0.5)
-    assert binary_relation2.head == head
-    assert binary_relation2.tail == tail
-    assert binary_relation2.label == "label2"
-    assert binary_relation2.score == pytest.approx(0.5)
-
-    assert binary_relation2.asdict() == {
-        "_id": binary_relation2._id,
-        "head": head._id,
-        "tail": tail._id,
-        "label": "label2",
-        "score": 0.5,
-    }
-
-    annotation_store = {
-        head._id: head,
-        tail._id: tail,
-    }
-    _test_annotation_reconstruction(binary_relation2, annotation_store=annotation_store)
-
-    with pytest.raises(
-        ValueError,
-        match=re.escape("Unable to resolve the annotation id without annotation_store."),
-    ):
-        BinaryRelation.fromdict(binary_relation2.asdict())
-
-    with pytest.raises(ValueError) as excinfo:
-        binary_relation1.resolve()
-    assert str(excinfo.value) == "Span(start=1, end=2) is not attached to a target."
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[Span] = annotation_field(target="text")
-        relations: AnnotationLayer[BinaryRelation] = annotation_field(target="spans")
-
-    doc = TestDocument(text="Hello, world!")
-    head = Span(start=0, end=5)
-    tail = Span(start=7, end=12)
-    doc.spans.extend([head, tail])
-    relation = BinaryRelation(head=head, tail=tail, label="LABEL")
-    doc.relations.append(relation)
-    assert relation.resolve() == ("LABEL", ("Hello", "world"))
-
-
-def test_multilabeled_binary_relation():
-    head = Span(start=1, end=2)
-    tail = Span(start=3, end=4)
-
-    binary_relation1 = MultiLabeledBinaryRelation(head=head, tail=tail, label=("label1", "label2"))
-    assert binary_relation1.head == head
-    assert binary_relation1.tail == tail
-    assert binary_relation1.label == ("label1", "label2")
-    assert binary_relation1.score == pytest.approx((1.0, 1.0))
-
-    binary_relation2 = MultiLabeledBinaryRelation(
-        head=head, tail=tail, label=("label3", "label4"), score=(0.4, 0.5)
-    )
-    assert binary_relation2.head == head
-    assert binary_relation2.tail == tail
-    assert binary_relation2.label == ("label3", "label4")
-    assert binary_relation2.score == pytest.approx((0.4, 0.5))
-
-    assert binary_relation2.asdict() == {
-        "_id": binary_relation2._id,
-        "head": head._id,
-        "tail": tail._id,
-        "label": ("label3", "label4"),
-        "score": (0.4, 0.5),
-    }
-
-    annotation_store = {
-        head._id: head,
-        tail._id: tail,
-    }
-    _test_annotation_reconstruction(binary_relation2, annotation_store=annotation_store)
-
-    with pytest.raises(
-        ValueError,
-        match=re.escape("Unable to resolve the annotation id without annotation_store."),
-    ):
-        MultiLabeledBinaryRelation.fromdict(binary_relation2.asdict())
-
-    with pytest.raises(
-        ValueError, match=re.escape("Number of labels (2) and scores (3) must be equal.")
-    ):
-        MultiLabeledBinaryRelation(
-            head=head, tail=tail, label=("label5", "label6"), score=(0.1, 0.2, 0.3)
-        )
-
-    with pytest.raises(ValueError) as excinfo:
-        binary_relation1.resolve()
-    assert str(excinfo.value) == "Span(start=1, end=2) is not attached to a target."
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[Span] = annotation_field(target="text")
-        relations: AnnotationLayer[MultiLabeledBinaryRelation] = annotation_field(target="spans")
-
-    doc = TestDocument(text="Hello, world!")
-    head = Span(start=0, end=5)
-    tail = Span(start=7, end=12)
-    doc.spans.extend([head, tail])
-    relation = MultiLabeledBinaryRelation(head=head, tail=tail, label=("LABEL1", "LABEL2"))
-    doc.relations.append(relation)
-    assert relation.resolve() == (("LABEL1", "LABEL2"), ("Hello", "world"))
-
-
-def test_nary_relation():
-    arg1 = Span(start=1, end=2)
-    arg2 = Span(start=3, end=4)
-    arg3 = Span(start=5, end=6)
-
-    nary_relation1 = NaryRelation(
-        arguments=(arg1, arg2, arg3), roles=("role1", "role2", "role3"), label="label1"
-    )
-
-    assert nary_relation1.arguments == (arg1, arg2, arg3)
-    assert nary_relation1.roles == ("role1", "role2", "role3")
-    assert nary_relation1.label == "label1"
-    assert nary_relation1.score == pytest.approx(1.0)
-
-    assert nary_relation1.asdict() == {
-        "_id": nary_relation1._id,
-        "arguments": [arg1._id, arg2._id, arg3._id],
-        "roles": ("role1", "role2", "role3"),
-        "label": "label1",
-        "score": 1.0,
-    }
-
-    annotation_store = {
-        arg1._id: arg1,
-        arg2._id: arg2,
-        arg3._id: arg3,
-    }
-    _test_annotation_reconstruction(nary_relation1, annotation_store=annotation_store)
-
-    with pytest.raises(
-        ValueError,
-        match=re.escape("Unable to resolve the annotation id without annotation_store."),
-    ):
-        NaryRelation.fromdict(nary_relation1.asdict())
-
-    with pytest.raises(ValueError) as excinfo:
-        nary_relation1.resolve()
-    assert str(excinfo.value) == "Span(start=1, end=2) is not attached to a target."
-
-    @dataclasses.dataclass
-    class TestDocument(TextBasedDocument):
-        spans: AnnotationLayer[Span] = annotation_field(target="text")
-        relations: AnnotationLayer[NaryRelation] = annotation_field(target="spans")
-
-    doc = TestDocument(text="Hello, world A and B!")
-    arg1 = Span(start=0, end=5)
-    arg2 = Span(start=7, end=14)
-    arg3 = Span(start=19, end=20)
-    doc.spans.extend([arg1, arg2, arg3])
-    relation = NaryRelation(
-        arguments=(arg1, arg2, arg3), roles=("ARG1", "ARG2", "ARG3"), label="LABEL"
-    )
-    doc.relations.append(relation)
-    assert relation.resolve() == (
-        "LABEL",
-        (("ARG1", "Hello"), ("ARG2", "world A"), ("ARG3", "B")),
-    )

From bcf2e371fab0382748873940c3321aff78b7a451 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:32:14 +0200
Subject: [PATCH 08/11] lower codecov project target from 70% to 68%

---
 codecov.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/codecov.yml b/codecov.yml
index 4daa1dd8..3ac41467 100644
--- a/codecov.yml
+++ b/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:

From c648243d95d8d59d51d5a0631f84ef1371e820d7 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Sat, 19 Jul 2025 18:49:11 +0200
Subject: [PATCH 09/11] remove is_contained_in and has_overlap, but re-export
 them from pie-modules; remove empty test file

---
 src/pytorch_ie/utils/span.py |  18 +-
 tests/utils/test_span.py     | 442 -----------------------------------
 2 files changed, 4 insertions(+), 456 deletions(-)
 delete mode 100644 tests/utils/test_span.py

diff --git a/src/pytorch_ie/utils/span.py b/src/pytorch_ie/utils/span.py
index ddef0d4c..347367e1 100644
--- a/src/pytorch_ie/utils/span.py
+++ b/src/pytorch_ie/utils/span.py
@@ -13,11 +13,14 @@
     Tuple,
 )
 
+# backwards compatibility imports from pie_modules.utils.span
+from pie_modules.utils.span import have_overlap as has_overlap
+from pie_modules.utils.span import is_contained_in
 from transformers import PreTrainedTokenizer
 
 from pytorch_ie.annotations import LabeledSpan, Span
 
-# TODO: most of this should be superseded by pie_modules.utils.span and pie_modules.utils.sequence_tagging,
+# TODO: most of this should be superseded by pie_modules.utils.sequence_tagging,
 #  remove respective content
 
 TypedSpan = Tuple[int, Tuple[int, int]]
@@ -229,19 +232,6 @@ def get_token_slice(
     return start, before_end + 1
 
 
-def is_contained_in(start_end: Tuple[int, int], other_start_end: Tuple[int, int]) -> bool:
-    return other_start_end[0] <= start_end[0] and start_end[1] <= other_start_end[1]
-
-
-def has_overlap(start_end: Tuple[int, int], other_start_end: Tuple[int, int]):
-    return (
-        start_end[0] <= other_start_end[0] < start_end[1]
-        or start_end[0] < other_start_end[1] <= start_end[1]
-        or other_start_end[0] <= start_end[0] < other_start_end[1]
-        or other_start_end[0] < start_end[1] <= other_start_end[1]
-    )
-
-
 def _char_to_token_mapper(
     char_idx: int,
     char_to_token_mapping: Dict[int, int],
diff --git a/tests/utils/test_span.py b/tests/utils/test_span.py
deleted file mode 100644
index 555da4f0..00000000
--- a/tests/utils/test_span.py
+++ /dev/null
@@ -1,442 +0,0 @@
-# import pytest
-
-# from pytorch_ie.utils.span import (
-#     convert_span_annotations_to_tag_sequence,
-#     get_char_to_token_mapper,
-#     has_overlap,
-# )
-# from tests.fixtures.document import get_doc1, get_doc2, get_doc3
-
-
-# @pytest.fixture
-# def documents():
-#     doc_kwargs = dict(
-#         assert_span_text=True,
-#     )
-#     documents = [get_doc1(**doc_kwargs), get_doc2(**doc_kwargs), get_doc3(**doc_kwargs)]
-#     return documents
-
-
-# @pytest.mark.skip
-# def test_get_char_to_token_mapper():
-#     # TODO: implement!
-#     pass
-
-
-# @pytest.mark.skip
-# def test_get_special_token_mask():
-#     # TODO: implement!
-#     pass
-
-
-# def test_convert_span_annotations_to_tag_sequence(documents):
-#     doc = documents[0]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 3
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         5: 2,
-#         6: 2,
-#         7: 2,
-#         8: 2,
-#         9: 2,
-#         11: 3,
-#         12: 3,
-#         14: 4,
-#         15: 4,
-#         16: 4,
-#         17: 4,
-#         18: 4,
-#         19: 4,
-#         20: 5,
-#         22: 6,
-#         23: 6,
-#         24: 6,
-#         25: 6,
-#         27: 7,
-#         28: 7,
-#         30: 8,
-#         31: 8,
-#         33: 9,
-#         34: 9,
-#         35: 9,
-#         36: 9,
-#         37: 9,
-#         38: 9,
-#         39: 9,
-#         40: 9,
-#         42: 10,
-#         43: 10,
-#         44: 10,
-#         45: 10,
-#         46: 10,
-#         48: 11,
-#         49: 11,
-#         50: 11,
-#         51: 11,
-#     }
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#     )
-#     assert tag_sequence == [
-#         None,
-#         "B-person",
-#         "O",
-#         "O",
-#         "B-city",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "B-person",
-#         None,
-#     ]
-
-#     doc = documents[1]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 2
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         4: 1,
-#         5: 1,
-#         6: 1,
-#         8: 2,
-#         9: 2,
-#         11: 3,
-#         13: 4,
-#         14: 4,
-#         15: 4,
-#         16: 4,
-#         17: 4,
-#         19: 5,
-#         20: 5,
-#         21: 5,
-#         22: 5,
-#         23: 6,
-#         25: 7,
-#         26: 7,
-#         27: 7,
-#         28: 7,
-#         29: 7,
-#         31: 8,
-#         32: 8,
-#         33: 9,
-#         34: 9,
-#         35: 9,
-#         36: 10,
-#         38: 11,
-#         39: 11,
-#         41: 12,
-#         42: 12,
-#         43: 12,
-#         45: 13,
-#         46: 13,
-#         47: 13,
-#         48: 13,
-#         49: 14,
-#         50: 15,
-#         52: 16,
-#         53: 16,
-#         54: 16,
-#         55: 16,
-#         56: 16,
-#         57: 17,
-#     }
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#     )
-#     assert tag_sequence == [
-#         None,
-#         "B-city",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "B-person",
-#         "I-person",
-#         "I-person",
-#         "I-person",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         None,
-#     ]
-
-#     doc = documents[2]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 2
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         5: 2,
-#         6: 2,
-#         7: 2,
-#         8: 2,
-#         9: 2,
-#         10: 2,
-#         12: 3,
-#         13: 3,
-#         14: 3,
-#         15: 3,
-#         16: 3,
-#         18: 4,
-#         19: 4,
-#         20: 4,
-#         21: 4,
-#         23: 5,
-#         24: 5,
-#         26: 6,
-#         27: 6,
-#         28: 6,
-#         29: 6,
-#         30: 6,
-#         31: 6,
-#         32: 7,
-#     }
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 0, 1]
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#     )
-#     assert tag_sequence == [None, "B-person", "O", "O", "O", "O", "B-city", "O", None]
-
-
-# def test_convert_span_annotations_to_tag_sequence_with_partition(documents):
-#     doc = documents[0]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 3
-#     partitions = doc.annotations.spans["sentences"]
-#     assert len(partitions) == 1
-#     partition = partitions[0]
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         5: 2,
-#         6: 2,
-#         7: 2,
-#         8: 2,
-#         9: 2,
-#         11: 3,
-#         12: 3,
-#         14: 4,
-#         15: 4,
-#         16: 4,
-#         17: 4,
-#         18: 4,
-#         19: 4,
-#         20: 5,
-#     }
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 1]
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#         partition=partition,
-#     )
-#     assert tag_sequence == [None, "B-person", "O", "O", "B-city", "O", None]
-
-#     doc = documents[1]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 2
-#     partitions = doc.annotations.spans["sentences"]
-#     assert len(partitions) == 2
-#     partition = partitions[0]
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         4: 1,
-#         5: 1,
-#         6: 1,
-#         8: 2,
-#         9: 2,
-#         11: 3,
-#         13: 4,
-#         14: 4,
-#         15: 4,
-#         16: 4,
-#         17: 4,
-#         19: 5,
-#         20: 5,
-#         21: 5,
-#         22: 5,
-#         23: 6,
-#     }
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 1]
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#         partition=partition,
-#     )
-#     assert tag_sequence == [None, "B-city", "O", "O", "O", "O", "O", None]
-#     partition = partitions[1]
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         4: 1,
-#         6: 2,
-#         7: 2,
-#         8: 3,
-#         9: 3,
-#         10: 3,
-#         11: 4,
-#         13: 5,
-#         14: 5,
-#         16: 6,
-#         17: 6,
-#         18: 6,
-#         20: 7,
-#         21: 7,
-#         22: 7,
-#         23: 7,
-#         24: 8,
-#         25: 9,
-#         27: 10,
-#         28: 10,
-#         29: 10,
-#         30: 10,
-#         31: 10,
-#         32: 11,
-#     }
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#         partition=partition,
-#     )
-#     assert tag_sequence == [
-#         None,
-#         "B-person",
-#         "I-person",
-#         "I-person",
-#         "I-person",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         "O",
-#         None,
-#     ]
-
-#     doc = documents[2]
-#     entities = doc.annotations.spans["entities"]
-#     assert len(entities) == 2
-#     partitions = doc.annotations.spans["sentences"]
-#     assert len(partitions) == 1
-#     partition = partitions[0]
-#     char_to_token_mapping = {
-#         0: 1,
-#         1: 1,
-#         2: 1,
-#         3: 1,
-#         5: 2,
-#         6: 2,
-#         7: 2,
-#         8: 2,
-#         9: 2,
-#         10: 2,
-#         12: 3,
-#         13: 3,
-#         14: 3,
-#         15: 3,
-#         16: 3,
-#         18: 4,
-#         19: 4,
-#         20: 4,
-#         21: 4,
-#         23: 5,
-#         24: 5,
-#         26: 6,
-#         27: 6,
-#         28: 6,
-#         29: 6,
-#         30: 6,
-#         31: 6,
-#         32: 7,
-#     }
-#     special_tokens_mask = [1, 0, 0, 0, 0, 0, 0, 0, 1]
-#     char_to_token_mapper = get_char_to_token_mapper(
-#         char_to_token_mapping=char_to_token_mapping,
-#     )
-#     tag_sequence = convert_span_annotations_to_tag_sequence(
-#         spans=entities,
-#         special_tokens_mask=special_tokens_mask,
-#         char_to_token_mapper=char_to_token_mapper,
-#         partition=partition,
-#     )
-#     assert tag_sequence == [None, "B-person", "O", "O", "O", "O", "B-city", "O", None]
-
-
-# def test_has_overlap():
-#     # no overlap - not touching
-#     assert not has_overlap((3, 5), (6, 10))
-#     assert not has_overlap((6, 10), (3, 5))
-
-#     # no overlap - touching
-#     assert not has_overlap((5, 10), (3, 5))
-#     assert not has_overlap((3, 5), (5, 10))
-
-#     # partly overlap
-#     assert has_overlap((3, 5), (4, 10))
-#     assert has_overlap((4, 10), (3, 5))
-
-#     # partly overlap - same start
-#     assert has_overlap((3, 5), (3, 10))
-#     assert has_overlap((3, 10), (3, 5))
-
-#     # partly overlap - same end
-#     assert has_overlap((3, 5), (2, 5))
-#     assert has_overlap((2, 5), (3, 5))
-
-#     # total overlap (containing)
-#     assert has_overlap((3, 5), (2, 10))
-#     assert has_overlap((2, 10), (3, 5))

From 2547c7c3a3197b80940d42e460619c62a6dd9324 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Mon, 22 Sep 2025 23:35:44 +0200
Subject: [PATCH 10/11] use pie-documents instead of pie-modules

---
 poetry.lock                                   | 1574 +----------------
 pyproject.toml                                |    1 +
 src/pytorch_ie/annotations.py                 |    2 +-
 src/pytorch_ie/documents.py                   |    2 +-
 src/pytorch_ie/metrics/__init__.py            |    2 +-
 src/pytorch_ie/metrics/statistics/__init__.py |    2 +-
 src/pytorch_ie/utils/span.py                  |    8 +-
 7 files changed, 81 insertions(+), 1510 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 52a46263..a5eac398 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,17 +1,5 @@
 # This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand.
 
-[[package]]
-name = "absl-py"
-version = "1.4.0"
-description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
-optional = false
-python-versions = ">=3.6"
-groups = ["main"]
-files = [
-    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
-    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
-]
-
 [[package]]
 name = "aiohttp"
 version = "3.9.5"
@@ -124,68 +112,6 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
-[[package]]
-name = "alabaster"
-version = "0.7.16"
-description = "A light, configurable Sphinx theme"
-optional = false
-python-versions = ">=3.9"
-groups = ["dev"]
-files = [
-    {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"},
-    {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"},
-]
-
-[[package]]
-name = "annotated-types"
-version = "0.7.0"
-description = "Reusable constraint types to use with typing.Annotated"
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
-    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
-]
-
-[[package]]
-name = "anyio"
-version = "4.4.0"
-description = "High level compatibility layer for multiple asynchronous event loop implementations"
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
-]
-
-[package.dependencies]
-exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
-idna = ">=2.8"
-sniffio = ">=1.1"
-typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
-
-[package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\""]
-trio = ["trio (>=0.23)"]
-
-[[package]]
-name = "argcomplete"
-version = "3.3.0"
-description = "Bash tab completion for argparse"
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "argcomplete-3.3.0-py3-none-any.whl", hash = "sha256:c168c3723482c031df3c207d4ba8fa702717ccb9fc0bfe4117166c1f537b4a54"},
-    {file = "argcomplete-3.3.0.tar.gz", hash = "sha256:fd03ff4a5b9e6580569d34b273f741e85cd9e072f3feeeee3eba4891c70eda62"},
-]
-
-[package.extras]
-test = ["coverage", "mypy", "pexpect", "ruff", "wheel"]
-
 [[package]]
 name = "async-timeout"
 version = "4.0.3"
@@ -205,7 +131,7 @@ version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
     {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
     {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
@@ -219,83 +145,6 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6) ; platform_python_implementation == \"CPython\" and python_version >= \"3.8\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.8\""]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
-[[package]]
-name = "authlib"
-version = "1.3.0"
-description = "The ultimate Python library in building OAuth and OpenID Connect servers and clients."
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "Authlib-1.3.0-py2.py3-none-any.whl", hash = "sha256:9637e4de1fb498310a56900b3e2043a206b03cb11c05422014b0302cbc814be3"},
-    {file = "Authlib-1.3.0.tar.gz", hash = "sha256:959ea62a5b7b5123c5059758296122b57cd2585ae2ed1c0622c21b371ffdae06"},
-]
-
-[package.dependencies]
-cryptography = "*"
-
-[[package]]
-name = "babel"
-version = "2.15.0"
-description = "Internationalization utilities"
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "Babel-2.15.0-py3-none-any.whl", hash = "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb"},
-    {file = "babel-2.15.0.tar.gz", hash = "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413"},
-]
-
-[package.extras]
-dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
-
-[[package]]
-name = "bandit"
-version = "1.7.8"
-description = "Security oriented static analyser for python code."
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "bandit-1.7.8-py3-none-any.whl", hash = "sha256:509f7af645bc0cd8fd4587abc1a038fc795636671ee8204d502b933aee44f381"},
-    {file = "bandit-1.7.8.tar.gz", hash = "sha256:36de50f720856ab24a24dbaa5fee2c66050ed97c1477e0a1159deab1775eab6b"},
-]
-
-[package.dependencies]
-colorama = {version = ">=0.3.9", markers = "platform_system == \"Windows\""}
-PyYAML = ">=5.3.1"
-rich = "*"
-stevedore = ">=1.20.0"
-
-[package.extras]
-baseline = ["GitPython (>=3.1.30)"]
-sarif = ["jschema-to-python (>=1.2.3)", "sarif-om (>=1.0.4)"]
-test = ["beautifulsoup4 (>=4.8.0)", "coverage (>=4.5.4)", "fixtures (>=3.0.0)", "flake8 (>=4.0.0)", "pylint (==1.9.4)", "stestr (>=2.5.0)", "testscenarios (>=0.5.0)", "testtools (>=2.3.0)"]
-toml = ["tomli (>=1.1.0) ; python_version < \"3.11\""]
-yaml = ["PyYAML"]
-
-[[package]]
-name = "beautifulsoup4"
-version = "4.12.3"
-description = "Screen-scraping library"
-optional = false
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-html5lib = ["html5lib"]
-lxml = ["lxml"]
-
 [[package]]
 name = "black"
 version = "24.4.2"
@@ -343,110 +192,18 @@ d = ["aiohttp (>=3.7.4) ; sys_platform != \"win32\" or implementation_name != \"
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
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-
 [[package]]
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 version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
-groups = ["main", "dev"]
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-]
-
-[package.dependencies]
-pycparser = "*"
-
 [[package]]
 name = "cfgv"
 version = "3.4.0"
@@ -465,7 +222,7 @@ version = "3.3.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
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@@ -585,25 +342,7 @@ files = [
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-
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-description = "Add colours to the output of Python's logging module."
-optional = false
-python-versions = ">=3.6"
-groups = ["dev"]
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-
-[package.dependencies]
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-
-[package.extras]
-development = ["black", "flake8", "mypy", "pytest", "types-colorama"]
+markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\" or platform_system == \"Windows\""}
 
 [[package]]
 name = "coverage"
@@ -673,73 +412,6 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 [package.extras]
 toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
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-    {file = "cryptography-42.0.7.tar.gz", hash = "sha256:ecbfbc00bf55888edda9868a4cf927205de8499e7fabe6c050322298382953f2"},
-]
-
-[package.dependencies]
-cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
-
-[package.extras]
-docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
-docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
-nox = ["nox"]
-pep8test = ["check-sdist", "click", "mypy", "ruff"]
-sdist = ["build"]
-ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
-test-randomorder = ["pytest-randomly"]
-
-[[package]]
-name = "darglint"
-version = "1.8.1"
-description = "A utility for ensuring Google-style docstrings stay up to date with the source code."
-optional = false
-python-versions = ">=3.6,<4.0"
-groups = ["dev"]
-files = [
-    {file = "darglint-1.8.1-py3-none-any.whl", hash = "sha256:5ae11c259c17b0701618a20c3da343a3eb98b3bc4b5a83d31cdd94f5ebdced8d"},
-    {file = "darglint-1.8.1.tar.gz", hash = "sha256:080d5106df149b199822e7ee7deb9c012b49891538f14a11be681044f0bb20da"},
-]
-
 [[package]]
 name = "distlib"
 version = "0.3.8"
@@ -753,54 +425,35 @@ files = [
 ]
 
 [[package]]
-name = "docutils"
-version = "0.21.2"
-description = "Docutils -- Python Documentation Utilities"
-optional = false
-python-versions = ">=3.9"
-groups = ["dev"]
-files = [
-    {file = "docutils-0.21.2-py3-none-any.whl", hash = "sha256:dafca5b9e384f0e419294eb4d2ff9fa826435bf15f15b7bd45723e8ad76811b2"},
-    {file = "docutils-0.21.2.tar.gz", hash = "sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f"},
-]
-
-[[package]]
-name = "dparse"
-version = "0.6.4b0"
-description = "A parser for Python dependency files"
+name = "exceptiongroup"
+version = "1.2.1"
+description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
+markers = "python_version < \"3.11\""
 files = [
-    {file = "dparse-0.6.4b0-py3-none-any.whl", hash = "sha256:592ff183348b8a5ea0a18442a7965e29445d3a26063654ec2c7e8ef42cd5753c"},
-    {file = "dparse-0.6.4b0.tar.gz", hash = "sha256:f8d49b41a527f3d16a269f854e6665245b325e50e41d2c213810cb984553e5c8"},
+    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
+    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
 ]
 
-[package.dependencies]
-packaging = "*"
-tomli = {version = "*", markers = "python_version < \"3.11\""}
-
 [package.extras]
-all = ["dparse[conda]", "dparse[pipenv]", "dparse[poetry]"]
-conda = ["pyyaml"]
-pipenv = ["pipenv"]
-poetry = ["poetry"]
+test = ["pytest (>=6)"]
 
 [[package]]
-name = "exceptiongroup"
-version = "1.2.1"
-description = "Backport of PEP 654 (exception groups)"
+name = "execnet"
+version = "2.1.1"
+description = "execnet: rapid multi-Python deployment"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version < \"3.11\""
 files = [
-    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
-    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
+    {file = "execnet-2.1.1-py3-none-any.whl", hash = "sha256:26dee51f1b80cebd6d0ca8e74dd8745419761d3bef34163928cbebbdc4749fdc"},
+    {file = "execnet-2.1.1.tar.gz", hash = "sha256:5189b52c6121c24feae288166ab41b32549c7e2348652736540b9e6e7d4e72e3"},
 ]
 
 [package.extras]
-test = ["pytest (>=6)"]
+testing = ["hatch", "pre-commit", "pytest", "tox"]
 
 [[package]]
 name = "filelock"
@@ -819,94 +472,6 @@ docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1
 testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
 typing = ["typing-extensions (>=4.8) ; python_version < \"3.11\""]
 
-[[package]]
-name = "flake8"
-version = "7.0.0"
-description = "the modular source code checker: pep8 pyflakes and co"
-optional = false
-python-versions = ">=3.8.1"
-groups = ["dev"]
-files = [
-    {file = "flake8-7.0.0-py2.py3-none-any.whl", hash = "sha256:a6dfbb75e03252917f2473ea9653f7cd799c3064e54d4c8140044c5c065f53c3"},
-    {file = "flake8-7.0.0.tar.gz", hash = "sha256:33f96621059e65eec474169085dc92bf26e7b2d47366b70be2f67ab80dc25132"},
-]
-
-[package.dependencies]
-mccabe = ">=0.7.0,<0.8.0"
-pycodestyle = ">=2.11.0,<2.12.0"
-pyflakes = ">=3.2.0,<3.3.0"
-
-[[package]]
-name = "flake8-bandit"
-version = "4.1.1"
-description = "Automated security testing with bandit and flake8."
-optional = false
-python-versions = ">=3.6"
-groups = ["dev"]
-files = [
-    {file = "flake8_bandit-4.1.1-py3-none-any.whl", hash = "sha256:4c8a53eb48f23d4ef1e59293657181a3c989d0077c9952717e98a0eace43e06d"},
-    {file = "flake8_bandit-4.1.1.tar.gz", hash = "sha256:068e09287189cbfd7f986e92605adea2067630b75380c6b5733dab7d87f9a84e"},
-]
-
-[package.dependencies]
-bandit = ">=1.7.3"
-flake8 = ">=5.0.0"
-
-[[package]]
-name = "flake8-bugbear"
-version = "24.4.26"
-description = "A plugin for flake8 finding likely bugs and design problems in your program. Contains warnings that don't belong in pyflakes and pycodestyle."
-optional = false
-python-versions = ">=3.8.1"
-groups = ["dev"]
-files = [
-    {file = "flake8_bugbear-24.4.26-py3-none-any.whl", hash = "sha256:cb430dd86bc821d79ccc0b030789a9c87a47a369667f12ba06e80f11305e8258"},
-    {file = "flake8_bugbear-24.4.26.tar.gz", hash = "sha256:ff8d4ba5719019ebf98e754624c30c05cef0dadcf18a65d91c7567300e52a130"},
-]
-
-[package.dependencies]
-attrs = ">=19.2.0"
-flake8 = ">=6.0.0"
-
-[package.extras]
-dev = ["coverage", "hypothesis", "hypothesmith (>=0.2)", "pre-commit", "pytest", "tox"]
-
-[[package]]
-name = "flake8-docstrings"
-version = "1.7.0"
-description = "Extension for flake8 which uses pydocstyle to check docstrings"
-optional = false
-python-versions = ">=3.7"
-groups = ["dev"]
-files = [
-    {file = "flake8_docstrings-1.7.0-py2.py3-none-any.whl", hash = "sha256:51f2344026da083fc084166a9353f5082b01f72901df422f74b4d953ae88ac75"},
-    {file = "flake8_docstrings-1.7.0.tar.gz", hash = "sha256:4c8cc748dc16e6869728699e5d0d685da9a10b0ea718e090b1ba088e67a941af"},
-]
-
-[package.dependencies]
-flake8 = ">=3"
-pydocstyle = ">=2.1"
-
-[[package]]
-name = "flake8-rst-docstrings"
-version = "0.3.0"
-description = "Python docstring reStructuredText (RST) validator for flake8"
-optional = false
-python-versions = ">=3.7"
-groups = ["dev"]
-files = [
-    {file = "flake8-rst-docstrings-0.3.0.tar.gz", hash = "sha256:d1ce22b4bd37b73cd86b8d980e946ef198cfcc18ed82fedb674ceaa2f8d1afa4"},
-    {file = "flake8_rst_docstrings-0.3.0-py3-none-any.whl", hash = "sha256:f8c3c6892ff402292651c31983a38da082480ad3ba253743de52989bdc84ca1c"},
-]
-
-[package.dependencies]
-flake8 = ">=3"
-pygments = "*"
-restructuredtext-lint = "*"
-
-[package.extras]
-develop = ["build", "twine"]
-
 [[package]]
 name = "frozenlist"
 version = "1.4.1"
@@ -1034,36 +599,6 @@ smb = ["smbprotocol"]
 ssh = ["paramiko"]
 tqdm = ["tqdm"]
 
-[[package]]
-name = "furo"
-version = "2024.5.6"
-description = "A clean customisable Sphinx documentation theme."
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "furo-2024.5.6-py3-none-any.whl", hash = "sha256:490a00d08c0a37ecc90de03ae9227e8eb5d6f7f750edf9807f398a2bdf2358de"},
-    {file = "furo-2024.5.6.tar.gz", hash = "sha256:81f205a6605ebccbb883350432b4831c0196dd3d1bc92f61e1f459045b3d2b0b"},
-]
-
-[package.dependencies]
-beautifulsoup4 = "*"
-pygments = ">=2.7"
-sphinx = ">=6.0,<8.0"
-sphinx-basic-ng = ">=1.0.0.beta2"
-
-[[package]]
-name = "h11"
-version = "0.14.0"
-description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
-optional = false
-python-versions = ">=3.7"
-groups = ["dev"]
-files = [
-    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
-    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
-]
-
 [[package]]
 name = "huggingface-hub"
 version = "0.25.2"
@@ -1120,24 +655,12 @@ version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
     {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
     {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
 ]
 
-[[package]]
-name = "imagesize"
-version = "1.4.1"
-description = "Getting image size from png/jpeg/jpeg2000/gif file"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-groups = ["dev"]
-files = [
-    {file = "imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b"},
-    {file = "imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a"},
-]
-
 [[package]]
 name = "importlib-metadata"
 version = "7.1.0"
@@ -1145,7 +668,7 @@ description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_full_version < \"3.10.2\""
+markers = "python_version == \"3.9\""
 files = [
     {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
     {file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
@@ -1208,7 +731,7 @@ version = "3.1.4"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
     {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
     {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
@@ -1242,38 +765,13 @@ cli = ["fire"]
 docs = ["requests (>=2.0.0)"]
 typing = ["mypy (>=1.0.0)", "types-setuptools"]
 
-[[package]]
-name = "markdown-it-py"
-version = "3.0.0"
-description = "Python port of markdown-it. Markdown parsing, done right!"
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
-    {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"},
-]
-
-[package.dependencies]
-mdurl = ">=0.1,<1.0"
-
-[package.extras]
-benchmarking = ["psutil", "pytest", "pytest-benchmark"]
-code-style = ["pre-commit (>=3.0,<4.0)"]
-compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
-linkify = ["linkify-it-py (>=1,<3)"]
-plugins = ["mdit-py-plugins"]
-profiling = ["gprof2dot"]
-rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
-testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
-
 [[package]]
 name = "markupsafe"
 version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
     {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc"},
     {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72b6be590cc35924b02c78ef34b467da4ba07e4e0f0454a2c5907f473fc50ce5"},
@@ -1337,70 +835,6 @@ files = [
     {file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
 ]
 
-[[package]]
-name = "marshmallow"
-version = "3.21.2"
-description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
-optional = false
-python-versions = ">=3.8"
-groups = ["dev"]
-files = [
-    {file = "marshmallow-3.21.2-py3-none-any.whl", hash = "sha256:70b54a6282f4704d12c0a41599682c5c5450e843b9ec406308653b47c59648a1"},
-    {file = "marshmallow-3.21.2.tar.gz", hash = "sha256:82408deadd8b33d56338d2182d455db632c6313aa2af61916672146bb32edc56"},
-]
-
-[package.dependencies]
-packaging = ">=17.0"
-
-[package.extras]
-dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
-docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.3.7)", "sphinx-issues (==4.1.0)", "sphinx-version-warning (==1.1.2)"]
-tests = ["pytest", "pytz", "simplejson"]
-
-[[package]]
-name = "mccabe"
-version = "0.7.0"
-description = "McCabe checker, plugin for flake8"
-optional = false
-python-versions = ">=3.6"
-groups = ["dev"]
-files = [
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-
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@@ -1660,47 +1067,6 @@ files = [
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-description = "pytest: simple powerful testing with Python"
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+
+[[package]]
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+description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs"
 optional = false
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 [package.dependencies]
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-iniconfig = "*"
-packaging = "*"
-pluggy = ">=1.5,<2.0"
-tomli = {version = ">=1", markers = "python_version < \"3.11\""}
+execnet = ">=2.1"
+pytest = ">=7.0.0"
 
 [package.extras]
-dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+psutil = ["psutil (>=3.0)"]
+setproctitle = ["setproctitle"]
+testing = ["filelock"]
 
 [[package]]
 name = "python-dateutil"
@@ -2605,7 +1786,7 @@ version = "2.32.2"
 description = "Python HTTP for Humans."
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
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@@ -2621,39 +1802,6 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
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-[package.extras]
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-
 [[package]]
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 version = "0.18.6"
@@ -2857,59 +2005,6 @@ tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
 testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
 torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
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-
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-
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-
 [[package]]
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 version = "70.0.0"
@@ -2938,18 +2033,6 @@ files = [
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 ]
 
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-description = "Tool to Detect Surrounding Shell"
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-python-versions = ">=3.7"
-groups = ["dev"]
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-tests-binary = ["cmake ; python_version < \"3.11\"", "cmake ; python_version < \"4.0\" and python_version >= \"3.11\"", "ninja ; python_version < \"3.11\"", "ninja ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 ; python_version < \"3.11\"", "pybind11 ; python_version < \"4.0\" and python_version >= \"3.11\"", "scikit-build ; python_version < \"3.11\"", "scikit-build ; python_version < \"4.0\" and python_version >= \"3.11\""]
-tests-binary-strict = ["cmake (==3.21.2) ; python_version < \"3.11\"", "cmake (==3.25.0) ; python_version < \"4.0\" and python_version >= \"3.11\"", "ninja (==1.10.2) ; python_version < \"3.11\"", "ninja (==1.11.1) ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 (==2.10.3) ; python_version < \"4.0\" and python_version >= \"3.11\"", "pybind11 (==2.7.1) ; python_version < \"3.11\"", "scikit-build (==0.11.1) ; python_version < \"3.11\"", "scikit-build (==0.16.1) ; python_version < \"4.0\" and python_version >= \"3.11\""]
-tests-strict = ["pytest (==4.6.0) ; python_version < \"3.10.0\" and python_version >= \"3.7.0\"", "pytest (==4.6.0) ; python_version < \"3.7.0\" and python_version >= \"3.6.0\"", "pytest (==6.2.5) ; python_version >= \"3.10.0\"", "pytest-cov (==3.0.0) ; python_version >= \"3.6.0\"", "typing (==3.7.4) ; python_version <= \"3.4\""]
-
 [[package]]
 name = "yarl"
 version = "1.9.4"
@@ -4055,7 +2625,7 @@ description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_full_version < \"3.10.2\""
+markers = "python_version == \"3.9\""
 files = [
     {file = "zipp-3.19.0-py3-none-any.whl", hash = "sha256:96dc6ad62f1441bcaccef23b274ec471518daf4fbbc580341204936a5a3dddec"},
     {file = "zipp-3.19.0.tar.gz", hash = "sha256:952df858fb3164426c976d9338d3961e8e8b3758e2e059e0f754b8c4262625ee"},
@@ -4067,5 +2637,5 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more
 
 [metadata]
 lock-version = "2.1"
-python-versions = "^3.9"
-content-hash = "e3abc1c30948dee05da1c096336758d976d1483f14fb0092bad1e0311792210e"
+python-versions = ">=3.9,<4.0"
+content-hash = "1696c4e4114f781251f63430d7b9fe20ad496506fdddb3d07b8714456dc7953a"
diff --git a/pyproject.toml b/pyproject.toml
index 05d381ea..ffdc1d26 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,6 +18,7 @@ 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",
diff --git a/src/pytorch_ie/annotations.py b/src/pytorch_ie/annotations.py
index 3cfa66b0..9149a218 100644
--- a/src/pytorch_ie/annotations.py
+++ b/src/pytorch_ie/annotations.py
@@ -1,5 +1,5 @@
 # backward compatibility
-from pie_modules.annotations import (
+from pie_documents.annotations import (
     BinaryRelation,
     Label,
     LabeledMultiSpan,
diff --git a/src/pytorch_ie/documents.py b/src/pytorch_ie/documents.py
index 4b5509e2..69ae50ba 100644
--- a/src/pytorch_ie/documents.py
+++ b/src/pytorch_ie/documents.py
@@ -1,5 +1,5 @@
 # backwards compatibility
-from pie_modules.documents import (
+from pie_documents.documents import (
     DocumentWithLabel,
     DocumentWithMultiLabel,
     TextBasedDocument,
diff --git a/src/pytorch_ie/metrics/__init__.py b/src/pytorch_ie/metrics/__init__.py
index 1ded4fd8..5885a047 100644
--- a/src/pytorch_ie/metrics/__init__.py
+++ b/src/pytorch_ie/metrics/__init__.py
@@ -1,2 +1,2 @@
 # backwards compatibility
-from pie_modules.metrics import ConfusionMatrix, F1Metric, SQuADF1
+from pie_documents.metrics import ConfusionMatrix, F1Metric, SQuADF1
diff --git a/src/pytorch_ie/metrics/statistics/__init__.py b/src/pytorch_ie/metrics/statistics/__init__.py
index d2acb1d3..be9c913e 100644
--- a/src/pytorch_ie/metrics/statistics/__init__.py
+++ b/src/pytorch_ie/metrics/statistics/__init__.py
@@ -1,4 +1,4 @@
-from pie_modules.metrics.statistics import (
+from pie_documents.metrics.statistics import (
     DummyCollector,
     FieldLengthCollector,
     LabelCountCollector,
diff --git a/src/pytorch_ie/utils/span.py b/src/pytorch_ie/utils/span.py
index 347367e1..b8f9bd8d 100644
--- a/src/pytorch_ie/utils/span.py
+++ b/src/pytorch_ie/utils/span.py
@@ -13,14 +13,14 @@
     Tuple,
 )
 
-# backwards compatibility imports from pie_modules.utils.span
-from pie_modules.utils.span import have_overlap as has_overlap
-from pie_modules.utils.span import is_contained_in
+# backwards compatibility imports from pie_documents.utils.span
+from pie_documents.utils.span import have_overlap as has_overlap
+from pie_documents.utils.span import is_contained_in
 from transformers import PreTrainedTokenizer
 
 from pytorch_ie.annotations import LabeledSpan, Span
 
-# TODO: most of this should be superseded by pie_modules.utils.sequence_tagging,
+# TODO: most of this should be superseded by pie_documents.utils.sequence_tagging,
 #  remove respective content
 
 TypedSpan = Tuple[int, Tuple[int, int]]

From be37f64d583152c2588c12fb3093a2f22d62a8b6 Mon Sep 17 00:00:00 2001
From: Arne Binder <arne.binder@dfki.de>
Date: Tue, 23 Sep 2025 01:12:57 +0200
Subject: [PATCH 11/11] remove pandas from explizit dependencies

---
 poetry.lock    | 2 +-
 pyproject.toml | 2 --
 2 files changed, 1 insertion(+), 3 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index a5eac398..009d8624 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2638,4 +2638,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.9,<4.0"
-content-hash = "1696c4e4114f781251f63430d7b9fe20ad496506fdddb3d07b8714456dc7953a"
+content-hash = "2b1197ef088543dadf4f2048b6ca32cbf781698ffe7f78d79c0e78de388e9f15"
diff --git a/pyproject.toml b/pyproject.toml
index ffdc1d26..310c033e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,8 +23,6 @@ dependencies = [
     "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]