Repository: ku-nlp/kwja (language: python)

Issue:
support Python 3.12
Addresses #197


Discussion / hints:

Fix patch:
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 7885c24c..4bc9b3a6 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -5,6 +5,18 @@
 
 version: 2
 updates:
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "monthly"
+      timezone: "Asia/Tokyo"
+    groups:
+      dependencies:
+        patterns:
+          - "*"
+    target-branch: "dev"
+    versioning-strategy: lockfile-only
+
   - package-ecosystem: "github-actions"
     # Workflow files stored in the
     # default location of `.github/workflows`
@@ -12,4 +24,4 @@ updates:
     schedule:
       interval: "monthly"
       timezone: "Asia/Tokyo"
-    target-branch: "main"
+    target-branch: "dev"
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 87d06de4..94c141e4 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -7,16 +7,17 @@ jobs:
     name: Build the project
     runs-on: ${{ matrix.os }}
     strategy:
-      max-parallel: 4
+      max-parallel: 8
       fail-fast: false
       matrix:
         os: [ ubuntu-latest, macos-latest, windows-latest ]
-        python-version: [ "3.8", "3.9", "3.10", "3.11" ]
+        python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
+        id: setup-python
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install Poetry
@@ -24,7 +25,10 @@ jobs:
             pipx install poetry
             echo "$HOME/.local/bin" >> $GITHUB_PATH
       - name: Install dependencies
+        env:
+          POETRY_PYTHON: ${{ steps.setup-python.outputs.python-path }}
         run: |
+          poetry env use $POETRY_PYTHON
           poetry install --no-interaction --without dev,test
       - name: Build KWJA
         run: |
diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
index 58e40ddc..651c7d22 100644
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -6,10 +6,10 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     strategy:
-      max-parallel: 4
+      max-parallel: 5
       fail-fast: false
       matrix:
-        python-version: [ "3.8", "3.9", "3.10", "3.11" ]
+        python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index beb9edb4..829e3d94 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -2,14 +2,14 @@ default_language_version:
   python: python3.10
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
       - id: check-yaml
       - id: check-toml
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 23.9.0
+    rev: 23.11.0
     hooks:
       - id: black
   - repo: https://github.com/PyCQA/flake8
@@ -22,22 +22,22 @@ repos:
     hooks:
       - id: isort
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.5.1
+    rev: v1.7.0
     hooks:
       - id: mypy
         additional_dependencies:
-          - rhoknp==1.5.0
+          - rhoknp==1.6.0
           - hydra-core==1.3.2
-          - torch==2.0.0
-          - torchmetrics==1.1.0
-          - transformers==4.32.1
-          - tokenizers==0.13.3
-          - wandb==0.15.9
-          - typer==0.9.0
-          - types-PyYAML==6.0.12.11
-          - git+https://github.com/nobu-g/cohesion-tools.git@v0.5.2
+          - torch==2.1.1
+          - torchmetrics==1.2.0
+          - transformers==4.34.1
+          - tokenizers
+          - wandb
+          - typer
+          - types-PyYAML
+          - cohesion-tools==0.5.7
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.10.1
+    rev: v3.15.0
     hooks:
       - id: pyupgrade
         args:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7f4e14a6..239f4bb5 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [v2.3.0] - 2024-02-01
+### Added
+- Support Python 3.12.
+
+### Fixed
+- Preserve document IDs when they are given as input.
+
 ## [v2.2.0] - 2023-10-27
 ### Added
 - Support `jumanpp` and `knp` input formats. This functionality allows you to partly use tokenization results of `jumanpp` as input.
@@ -190,7 +197,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Removed
 - Remove an unnecessary dependency, `fugashi`.
 
-[Unreleased]: https://github.com/ku-nlp/kwja/compare/v2.2.0...HEAD
+[Unreleased]: https://github.com/ku-nlp/kwja/compare/v2.3.0...HEAD
+[2.3.0]: https://github.com/ku-nlp/kwja/compare/v2.2.0...v2.3.0
 [2.2.0]: https://github.com/ku-nlp/kwja/compare/v2.1.3...v2.2.0
 [2.1.3]: https://github.com/ku-nlp/kwja/compare/v2.1.2...v2.1.3
 [2.1.2]: https://github.com/ku-nlp/kwja/compare/v2.1.1...v2.1.2
diff --git a/poetry.lock b/poetry.lock
index 3312c962..711f7ed4 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,112 +1,100 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "aiohttp"
-version = "3.8.6"
+version = "3.9.3"
 description = "Async http client/server framework (asyncio)"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
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+    {file = "aiohttp-3.9.3.tar.gz", hash = "sha256:90842933e5d1ff760fae6caca4b2b3edba53ba8f4b71e95dacf2818a2aca06f7"},
 ]
 
 [package.dependencies]
 aiosignal = ">=1.1.2"
-async-timeout = ">=4.0.0a3,<5.0"
+async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
-charset-normalizer = ">=2.0,<4.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
 yarl = ">=1.0,<2.0"
 
 [package.extras]
-speedups = ["Brotli", "aiodns", "cchardet"]
+speedups = ["Brotli", "aiodns", "brotlicffi"]
 
 [[package]]
 name = "aiosignal"
@@ -185,21 +173,22 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "23.1.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
+dev = ["attrs[tests]", "pre-commit"]
 docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
 tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "backcall"
@@ -214,112 +203,112 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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+    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
+    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
 ]
 
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-version = "3.3.1"
+version = "3.3.2"
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 ]
 
 [[package]]
 name = "fsspec"
-version = "2023.10.0"
+version = "2023.12.2"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2023.10.0-py3-none-any.whl", hash = "sha256:346a8f024efeb749d2a5fca7ba8854474b1ff9af7c3faaf636a4548781136529"},
-    {file = "fsspec-2023.10.0.tar.gz", hash = "sha256:330c66757591df346ad3091a53bd907e15348c2ba17d63fd54f5c39c4457d2a5"},
+    {file = "fsspec-2023.12.2-py3-none-any.whl", hash = "sha256:d800d87f72189a745fa3d6b033b9dc4a34ad069f60ca60b943a63599f5501960"},
+    {file = "fsspec-2023.12.2.tar.gz", hash = "sha256:8548d39e8810b59c38014934f6b31e57f40c1b20f911f4cc2b85389c7e9bf0cb"},
 ]
 
 [package.dependencies]
@@ -654,20 +634,20 @@ smmap = ">=3.0.1,<6"
 
 [[package]]
 name = "gitpython"
-version = "3.1.40"
+version = "3.1.41"
 description = "GitPython is a Python library used to interact with Git repositories"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "GitPython-3.1.40-py3-none-any.whl", hash = "sha256:cf14627d5a8049ffbf49915732e5eddbe8134c3bdb9d476e6182b676fc573f8a"},
-    {file = "GitPython-3.1.40.tar.gz", hash = "sha256:22b126e9ffb671fdd0c129796343a02bf67bf2994b35449ffc9321aa755e18a4"},
+    {file = "GitPython-3.1.41-py3-none-any.whl", hash = "sha256:c36b6634d069b3f719610175020a9aed919421c87552185b085e04fbbdb10b7c"},
+    {file = "GitPython-3.1.41.tar.gz", hash = "sha256:ed66e624884f76df22c8e16066d567aaa5a37d5b5fa19db2c6df6f7156db9048"},
 ]
 
 [package.dependencies]
 gitdb = ">=4.0.1,<5"
 
 [package.extras]
-test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-instafail", "pytest-subtests", "pytest-sugar"]
+test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "sumtypes"]
 
 [[package]]
 name = "gprof2dot"
@@ -682,13 +662,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.18.0"
+version = "0.20.3"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.18.0-py3-none-any.whl", hash = "sha256:ee0b6b68acbf6aeb6d083ea081e981c277a1104b82ab67fdf6780ff5396830af"},
-    {file = "huggingface_hub-0.18.0.tar.gz", hash = "sha256:10eda12b9c1cfa800b4b7c096b3ace8843734c3f28d69d1c243743fb7d7a2e81"},
+    {file = "huggingface_hub-0.20.3-py3-none-any.whl", hash = "sha256:d988ae4f00d3e307b0c80c6a05ca6dbb7edba8bba3079f74cda7d9c2e562a7b6"},
+    {file = "huggingface_hub-0.20.3.tar.gz", hash = "sha256:94e7f8e074475fbc67d6a71957b678e1b4a74ff1b64a644fd6cbb83da962d05d"},
 ]
 
 [package.dependencies]
@@ -701,17 +681,16 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (==23.7)", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (<2.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (==23.7)", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (<2.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
-docs = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (==23.7)", "gradio", "hf-doc-builder", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (<2.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)", "watchdog"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-inference = ["aiohttp", "pydantic (<2.0)"]
-quality = ["black (==23.7)", "mypy (==1.5.1)", "ruff (>=0.0.241)"]
+inference = ["aiohttp", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.1.3)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic (<2.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["torch"]
-typing = ["pydantic (<2.0)", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
 [[package]]
 name = "hydra-core"
@@ -732,24 +711,24 @@ packaging = "*"
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"},
-    {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
+    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
+    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
 ]
 
 [[package]]
 name = "importlib-resources"
-version = "6.1.0"
+version = "6.1.1"
 description = "Read resources from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_resources-6.1.0-py3-none-any.whl", hash = "sha256:aa50258bbfa56d4e33fbd8aa3ef48ded10d1735f11532b8df95388cc6bdb7e83"},
-    {file = "importlib_resources-6.1.0.tar.gz", hash = "sha256:9d48dcccc213325e810fd723e7fbb45ccb39f6cf5c31f00cf2b965f5f10f3cb9"},
+    {file = "importlib_resources-6.1.1-py3-none-any.whl", hash = "sha256:e8bf90d8213b486f428c9c39714b920041cb02c184686a3dee24905aaa8105d6"},
+    {file = "importlib_resources-6.1.1.tar.gz", hash = "sha256:3893a00122eafde6894c59914446a512f728a0c1a45f9bb9b63721b6bacf0b4a"},
 ]
 
 [package.dependencies]
@@ -827,43 +806,40 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pa
 
 [[package]]
 name = "ipython"
-version = "8.16.1"
+version = "8.18.1"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "ipython-8.16.1-py3-none-any.whl", hash = "sha256:0852469d4d579d9cd613c220af7bf0c9cc251813e12be647cb9d463939db9b1e"},
-    {file = "ipython-8.16.1.tar.gz", hash = "sha256:ad52f58fca8f9f848e256c629eff888efc0528c12fe0f8ec14f33205f23ef938"},
+    {file = "ipython-8.18.1-py3-none-any.whl", hash = "sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397"},
+    {file = "ipython-8.18.1.tar.gz", hash = "sha256:ca6f079bb33457c66e233e4580ebfc4128855b4cf6370dddd73842a9563e8a27"},
 ]
 
 [package.dependencies]
-appnope = {version = "*", markers = "sys_platform == \"darwin\""}
-backcall = "*"
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 decorator = "*"
 exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 jedi = ">=0.16"
 matplotlib-inline = "*"
 pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
-pickleshare = "*"
-prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
+prompt-toolkit = ">=3.0.41,<3.1.0"
 pygments = ">=2.4.0"
 stack-data = "*"
 traitlets = ">=5"
 typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
 
 [package.extras]
-all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
+all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
 black = ["black"]
-doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
+doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
 kernel = ["ipykernel"]
 nbconvert = ["nbconvert"]
 nbformat = ["nbformat"]
 notebook = ["ipywidgets", "notebook"]
 parallel = ["ipyparallel"]
 qtconsole = ["qtconsole"]
-test = ["pytest (<7.1)", "pytest-asyncio", "testpath"]
-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pandas", "pytest (<7.1)", "pytest-asyncio", "testpath", "trio"]
+test = ["pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath", "trio"]
 
 [[package]]
 name = "jaconv"
@@ -910,13 +886,13 @@ pyknp = ["pyknp[pyknp] (>=0.6,<1.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.2"
+version = "3.1.3"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
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 [package.dependencies]
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 typing-extensions = "*"
 
 [package.extras]
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 docs = ["requests (>=2.0.0)"]
-typing = ["mypy (>=1.0.0)"]
-
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 [[package]]
 name = "markdown-it-py"
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-name = "nvidia-cuda-nvrtc-cu11"
-version = "11.7.99"
+name = "nvidia-cuda-nvrtc-cu12"
+version = "12.1.105"
 description = "NVRTC native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
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+    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed"},
 ]
 
-[package.dependencies]
-setuptools = "*"
-wheel = "*"
-
 [[package]]
-name = "nvidia-cuda-runtime-cu11"
-version = "11.7.99"
+name = "nvidia-cuda-runtime-cu12"
+version = "12.1.105"
 description = "CUDA Runtime native Libraries"
 optional = false
 python-versions = ">=3"
 files = [
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-[package.dependencies]
-setuptools = "*"
-wheel = "*"
-
 [[package]]
-name = "nvidia-cudnn-cu11"
-version = "8.5.0.96"
+name = "nvidia-cudnn-cu12"
+version = "8.9.2.26"
 description = "cuDNN runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [package.dependencies]
-setuptools = "*"
-wheel = "*"
+nvidia-cublas-cu12 = "*"
 
 [[package]]
-name = "nvidia-cufft-cu11"
-version = "10.9.0.58"
+name = "nvidia-cufft-cu12"
+version = "11.0.2.54"
 description = "CUFFT native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [[package]]
-name = "nvidia-curand-cu11"
-version = "10.2.10.91"
+name = "nvidia-curand-cu12"
+version = "10.3.2.106"
 description = "CURAND native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:eecb269c970fa599a2660c9232fa46aaccbf90d9170b96c462e13bcb4d129e2c"},
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 ]
 
-[package.dependencies]
-setuptools = "*"
-wheel = "*"
-
 [[package]]
-name = "nvidia-cusolver-cu11"
-version = "11.4.0.1"
+name = "nvidia-cusolver-cu12"
+version = "11.4.5.107"
 description = "CUDA solver native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:72fa7261d755ed55c0074960df5904b65e2326f7adce364cbe4945063c1be412"},
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+    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd"},
+    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-win_amd64.whl", hash = "sha256:74e0c3a24c78612192a74fcd90dd117f1cf21dea4822e66d89e8ea80e3cd2da5"},
 ]
 
 [package.dependencies]
-setuptools = "*"
-wheel = "*"
+nvidia-cublas-cu12 = "*"
+nvidia-cusparse-cu12 = "*"
+nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
-name = "nvidia-cusparse-cu11"
-version = "11.7.4.91"
+name = "nvidia-cusparse-cu12"
+version = "12.1.0.106"
 description = "CUSPARSE native runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
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+    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c"},
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 ]
 
 [package.dependencies]
-setuptools = "*"
-wheel = "*"
+nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
-name = "nvidia-nccl-cu11"
-version = "2.14.3"
+name = "nvidia-nccl-cu12"
+version = "2.19.3"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:5e5534257d1284b8e825bc3a182c6f06acd6eb405e9f89d49340e98cd8f136eb"},
+    {file = "nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:a9734707a2c96443331c1e48c717024aa6678a0e2a4cb66b2c364d18cee6b48d"},
 ]
 
 [[package]]
-name = "nvidia-nvtx-cu11"
-version = "11.7.91"
-description = "NVIDIA Tools Extension"
+name = "nvidia-nvjitlink-cu12"
+version = "12.3.101"
+description = "Nvidia JIT LTO Library"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:b22c64eee426a62fc00952b507d6d29cf62b4c9df7a480fcc417e540e05fd5ac"},
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+    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:64335a8088e2b9d196ae8665430bc6a2b7e6ef2eb877a9c735c804bd4ff6467c"},
+    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-win_amd64.whl", hash = "sha256:1b2e317e437433753530792f13eece58f0aec21a2b05903be7bffe58a606cbd1"},
 ]
 
-[package.dependencies]
-setuptools = "*"
-wheel = "*"
+[[package]]
+name = "nvidia-nvtx-cu12"
+version = "12.1.105"
+description = "NVIDIA Tools Extension"
+optional = false
+python-versions = ">=3"
+files = [
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+]
 
 [[package]]
 name = "omegaconf"
@@ -1609,25 +1602,15 @@ files = [
 qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
 testing = ["docopt", "pytest (<6.0.0)"]
 
-[[package]]
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-description = "File system general utilities"
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-python-versions = "*"
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-]
-
 [[package]]
 name = "pexpect"
-version = "4.8.0"
+version = "4.9.0"
 description = "Pexpect allows easy control of interactive console applications."
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [package.dependencies]
@@ -1646,13 +1629,13 @@ files = [
 
 [[package]]
 name = "pluggy"
-version = "1.3.0"
+version = "1.4.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -1661,13 +1644,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.39"
+version = "3.0.43"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -1675,49 +1658,47 @@ wcwidth = "*"
 
 [[package]]
 name = "protobuf"
-version = "4.24.4"
+version = "4.25.2"
 description = ""
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "psutil"
-version = "5.9.6"
+version = "5.9.8"
 description = "Cross-platform lib for process and system monitoring in Python."
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
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 [package.extras]
@@ -1766,27 +1747,28 @@ tests = ["pytest"]
 
 [[package]]
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 description = "Pygments is a syntax highlighting package written in Python."
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 [package.extras]
 plugins = ["importlib-metadata"]
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 description = "pytest: simple powerful testing with Python"
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 [package.dependencies]
@@ -1794,7 +1776,7 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
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 iniconfig = "*"
 packaging = "*"
-pluggy = ">=0.12,<2.0"
+pluggy = ">=1.3.0,<2.0"
 tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
@@ -1853,13 +1835,13 @@ six = ">=1.5"
 
 [[package]]
 name = "python-dotenv"
-version = "1.0.0"
+version = "1.0.1"
 description = "Read key-value pairs from a .env file and set them as environment variables"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -1867,44 +1849,44 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "pytorch-lightning"
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 description = "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 [package.extras]
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 [package.extras]
 all = ["safetensors[jax]", "safetensors[numpy]", "safetensors[paddlepaddle]", "safetensors[pinned-tf]", "safetensors[quality]", "safetensors[testing]", "safetensors[torch]"]
 dev = ["safetensors[all]"]
 jax = ["flax (>=0.6.3)", "jax (>=0.3.25)", "jaxlib (>=0.3.25)", "safetensors[numpy]"]
+mlx = ["mlx (>=0.0.9)"]
 numpy = ["numpy (>=1.21.6)"]
 paddlepaddle = ["paddlepaddle (>=2.4.1)", "safetensors[numpy]"]
 pinned-tf = ["safetensors[numpy]", "tensorflow (==2.11.0)"]
@@ -2393,6 +2388,48 @@ docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)"
 examples = ["matplotlib (>=3.1.3)", "pandas (>=1.0.5)", "plotly (>=5.14.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)"]
 tests = ["black (>=23.3.0)", "matplotlib (>=3.1.3)", "mypy (>=1.3)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "pooch (>=1.6.0)", "pyamg (>=4.0.0)", "pytest (>=7.1.2)", "pytest-cov (>=2.9.0)", "ruff (>=0.0.272)", "scikit-image (>=0.16.2)"]
 
+[[package]]
+name = "scikit-learn"
+version = "1.4.0"
+description = "A set of python modules for machine learning and data mining"
+optional = false
+python-versions = ">=3.9"
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@@ -2646,17 +2725,17 @@ test = ["pytest"]
 
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 [package.dependencies]
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 jinja2 = "*"
 networkx = "*"
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-nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu11 = {version = "10.9.0.58", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu11 = {version = "10.2.10.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu11 = {version = "11.4.0.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu11 = {version = "11.7.4.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu11 = {version = "2.14.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu11 = {version = "11.7.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
-triton = {version = "2.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-typing-extensions = "*"
+triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
+optree = ["optree (>=0.9.1)"]
 
 [[package]]
 name = "torchmetrics"
-version = "1.2.0"
+version = "1.3.0.post0"
 description = "PyTorch native Metrics"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "torchmetrics-1.2.0-py3-none-any.whl", hash = "sha256:da2cb18822b285786d082c40efb9e1d861aac425f58230234fe6ce233cf002f8"},
-    {file = "torchmetrics-1.2.0.tar.gz", hash = "sha256:7eb28340bde45e13187a9ad54a4a7010a50417815d8181a5df6131f116ffe1b7"},
+    {file = "torchmetrics-1.3.0.post0-py3-none-any.whl", hash = "sha256:9e691ff8e8b752ad191c896f98e4a6dea81fe91dda5b6916e5b7aeaed4c7e1ad"},
+    {file = "torchmetrics-1.3.0.post0.tar.gz", hash = "sha256:6d31aeabee964ff539425800164790b8670293f2fade9fcfee6fabbe3f45dd7e"},
 ]
 
 [package.dependencies]
 lightning-utilities = ">=0.8.0"
 numpy = ">1.20.0"
-torch = ">=1.8.1"
+packaging = ">17.1"
+torch = ">=1.10.0"
 typing-extensions = {version = "*", markers = "python_version < \"3.9\""}
 
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+all = ["SciencePlots (>=2.0.0)", "ipadic (>=1.0.0)", "matplotlib (>=3.3.0)", "mecab-ko (>=1.0.0)", "mecab-ko-dic (>=1.0.0)", "mecab-python3 (>=1.0.6)", "mypy (==1.8.0)", "nltk (>=3.6)", "piq (<=0.8.0)", "pycocotools (>2.0.0)", "pystoi (>=0.3.0)", "regex (>=2021.9.24)", "scipy (>1.0.0)", "sentencepiece (>=0.1.98)", "torch (==2.1.2)", "torch-fidelity (<=0.4.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>4.4.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
 audio = ["pystoi (>=0.3.0)", "torchaudio (>=0.10.0)"]
 detection = ["pycocotools (>2.0.0)", "torchvision (>=0.8)"]
-dev = ["SciencePlots (>=2.0.0)", "bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.3.1)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "faster-coco-eval (>=1.3.3)", "fire (<=0.5.0)", "huggingface-hub (<0.18)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "lpips (<=0.1.4)", "matplotlib (>=3.2.0)", "mir-eval (>=0.6)", "mypy (==1.5.1)", "netcal (>1.0.0)", "nltk (>=3.6)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "piq (<=0.8.0)", "psutil (<=5.9.5)", "pycocotools (>2.0.0)", "pystoi (>=0.3.0)", "pytest (==7.4.2)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==1.0.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "regex (>=2021.9.24)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)", "torch-fidelity (<=0.4.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>4.4.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
-image = ["lpips (<=0.1.4)", "scipy (>1.0.0)", "torch-fidelity (<=0.4.0)", "torchvision (>=0.8)"]
+dev = ["SciencePlots (>=2.0.0)", "bert-score (==0.3.13)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "faster-coco-eval (>=1.3.3)", "huggingface-hub (<0.21)", "ipadic (>=1.0.0)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "lpips (<=0.1.4)", "matplotlib (>=3.3.0)", "mecab-ko (>=1.0.0)", "mecab-ko-dic (>=1.0.0)", "mecab-python3 (>=1.0.6)", "mir-eval (>=0.6)", "monai (==1.3.0)", "mypy (==1.8.0)", "netcal (>1.0.0)", "nltk (>=3.6)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "piq (<=0.8.0)", "pycocotools (>2.0.0)", "pystoi (>=0.3.0)", "pytorch-msssim (==1.0.0)", "regex (>=2021.9.24)", "rouge-score (>0.1.0)", "sacrebleu (>=2.3.0)", "scikit-image (>=0.19.0)", "scipy (>1.0.0)", "sentencepiece (>=0.1.98)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch (==2.1.2)", "torch-complex (<=0.4.3)", "torch-fidelity (<=0.4.0)", "torchaudio (>=0.10.0)", "torchvision (>=0.8)", "tqdm (>=4.41.0)", "transformers (>4.4.0)", "transformers (>=4.10.0)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
+image = ["scipy (>1.0.0)", "torch-fidelity (<=0.4.0)", "torchvision (>=0.8)"]
 multimodal = ["piq (<=0.8.0)", "transformers (>=4.10.0)"]
-test = ["bert-score (==0.3.13)", "cloudpickle (>1.3)", "coverage (==7.3.1)", "dython (<=0.7.4)", "fairlearn", "fast-bss-eval (>=0.1.0)", "faster-coco-eval (>=1.3.3)", "fire (<=0.5.0)", "huggingface-hub (<0.18)", "jiwer (>=2.3.0)", "kornia (>=0.6.7)", "mir-eval (>=0.6)", "netcal (>1.0.0)", "numpy (<1.25.0)", "pandas (>1.0.0)", "pandas (>=1.4.0)", "phmdoctest (==1.4.0)", "psutil (<=5.9.5)", "pytest (==7.4.2)", "pytest-cov (==4.1.0)", "pytest-doctestplus (==1.0.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "pytorch-msssim (==1.0.0)", "requests (<=2.31.0)", "rouge-score (>0.1.0)", "sacrebleu (>=2.0.0)", "scikit-image (>=0.19.0)", "scikit-learn (>=1.1.1)", "scipy (>1.0.0)", "sewar (>=0.4.4)", "statsmodels (>0.13.5)", "torch-complex (<=0.4.3)"]
-text = ["nltk (>=3.6)", "regex (>=2021.9.24)", "tqdm (>=4.41.0)", "transformers (>4.4.0)"]
-typing = ["mypy (==1.5.1)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
-visual = ["SciencePlots (>=2.0.0)", "matplotlib (>=3.2.0)"]
+text = ["ipadic (>=1.0.0)", "mecab-ko (>=1.0.0)", "mecab-ko-dic (>=1.0.0)", "mecab-python3 (>=1.0.6)", "nltk (>=3.6)", "regex (>=2021.9.24)", "sentencepiece (>=0.1.98)", "tqdm (>=4.41.0)", "transformers (>4.4.0)"]
+typing = ["mypy (==1.8.0)", "torch (==2.1.2)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
+visual = ["SciencePlots (>=2.0.0)", "matplotlib (>=3.3.0)"]
 
 [[package]]
 name = "tqdm"
@@ -2897,33 +3052,33 @@ telegram = ["requests"]
 
 [[package]]
 name = "traitlets"
-version = "5.12.0"
+version = "5.14.1"
 description = "Traitlets Python configuration system"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "traitlets-5.12.0-py3-none-any.whl", hash = "sha256:81539f07f7aebcde2e4b5ab76727f53eabf18ad155c6ed7979a681411602fa47"},
-    {file = "traitlets-5.12.0.tar.gz", hash = "sha256:833273bf645d8ce31dcb613c56999e2e055b1ffe6d09168a164bcd91c36d5d35"},
+    {file = "traitlets-5.14.1-py3-none-any.whl", hash = "sha256:2e5a030e6eff91737c643231bfcf04a65b0132078dad75e4936700b213652e74"},
+    {file = "traitlets-5.14.1.tar.gz", hash = "sha256:8585105b371a04b8316a43d5ce29c098575c2e477850b62b848b964f1444527e"},
 ]
 
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=3.0.3)", "mypy (>=1.6.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
 
 [[package]]
 name = "transformers"
-version = "4.32.1"
+version = "4.36.2"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "transformers-4.32.1-py3-none-any.whl", hash = "sha256:b930d3dbd907a3f300cf49e54d63a56f8a0ab16b01a2c2a61ecff37c6de1da08"},
-    {file = "transformers-4.32.1.tar.gz", hash = "sha256:1edc8ae1de357d97c3d36b04412aa63d55e6fc0c4b39b419a7d380ed947d2252"},
+    {file = "transformers-4.36.2-py3-none-any.whl", hash = "sha256:462066c4f74ee52516f12890dcc9ec71d1a5e97998db621668455117a54330f6"},
+    {file = "transformers-4.36.2.tar.gz", hash = "sha256:d8068e897e47793281501e547d2bbdfc5b8556409c2cb6c3d9e2ca77d4c0b4ec"},
 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.15.1,<1.0"
+huggingface-hub = ">=0.19.3,<1.0"
 numpy = ">=1.17"
 packaging = ">=20.0"
 protobuf = {version = "*", optional = true, markers = "extra == \"sentencepiece\""}
@@ -2932,35 +3087,34 @@ regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.3.1"
 sentencepiece = {version = ">=0.1.91,<0.1.92 || >0.1.92", optional = true, markers = "extra == \"sentencepiece\""}
-tokenizers = ">=0.11.1,<0.11.3 || >0.11.3,<0.14"
+tokenizers = ">=0.14,<0.19"
 tqdm = ">=4.27"
 
 [package.extras]
-accelerate = ["accelerate (>=0.20.3)"]
-agents = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch (>=1.9,!=1.12.0)"]
-all = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision"]
+accelerate = ["accelerate (>=0.21.0)"]
+agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch (>=1.10,!=1.12.0)"]
+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch (>=1.10,!=1.12.0)", "torchaudio", "torchvision"]
 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
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 name = "typer"
@@ -3062,52 +3202,52 @@ files = [
 
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 name = "typing-extensions"
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 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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 name = "tzdata"
-version = "2023.3"
+version = "2023.4"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
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 name = "urllib3"
-version = "2.0.7"
+version = "2.2.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.extras]
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-secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.1.0)", "urllib3-secure-extra"]
+h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "wandb"
-version = "0.15.12"
+version = "0.16.2"
 description = "A CLI and library for interacting with the Weights & Biases API."
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -3115,7 +3255,6 @@ appdirs = ">=1.4.3"
 Click = ">=7.1,<8.0.0 || >8.0.0"
 docker-pycreds = ">=0.4.0"
 GitPython = ">=1.0.0,<3.1.29 || >3.1.29"
-pathtools = "*"
 protobuf = [
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     {version = ">=3.19.0,<4.21.0 || >4.21.0,<5", markers = "python_version > \"3.9\" or sys_platform != \"linux\""},
@@ -3130,124 +3269,125 @@ setuptools = "*"
 typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
 
 [package.extras]
-async = ["httpx (>=0.22.0)"]
+async = ["httpx (>=0.23.0)"]
 aws = ["boto3"]
 azure = ["azure-identity", "azure-storage-blob"]
 gcp = ["google-cloud-storage"]
 kubeflow = ["google-cloud-storage", "kubernetes", "minio", "sh"]
-launch = ["PyYAML (>=6.0.0)", "awscli", "azure-containerregistry", "azure-identity", "azure-storage-blob", "boto3", "botocore", "chardet", "google-auth", "google-cloud-artifact-registry", "google-cloud-compute", "google-cloud-storage", "iso8601", "kubernetes", "nbconvert", "nbformat", "optuna", "typing-extensions"]
-media = ["bokeh", "moviepy", "numpy", "pillow", "plotly", "rdkit-pypi", "soundfile"]
+launch = ["PyYAML (>=6.0.0)", "awscli", "azure-containerregistry", "azure-identity", "azure-storage-blob", "boto3", "botocore", "chardet", "google-auth", "google-cloud-aiplatform", "google-cloud-artifact-registry", "google-cloud-compute", "google-cloud-storage", "iso8601", "kubernetes", "kubernetes-asyncio", "nbconvert", "nbformat", "optuna", "pydantic", "typing-extensions"]
+media = ["bokeh", "moviepy", "numpy", "pillow", "plotly (>=5.18.0)", "rdkit-pypi", "soundfile"]
 models = ["cloudpickle"]
-nexus = ["wandb-core (>=0.16.0b1)"]
 perf = ["orjson"]
 sweeps = ["sweeps (>=0.2.0)"]
 
 [[package]]
 name = "wcwidth"
-version = "0.2.8"
+version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
 files = [
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-description = "A built-package format for Python"
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-python-versions = ">=3.7"
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-
-[package.extras]
-test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
-
 [[package]]
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 description = "Yet another URL library"
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 python-versions = ">=3.7"
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+    {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8397a3817d7dcdd14bb266283cd1d6fc7264a48c186b986f32e86d86d35fbac5"},
+    {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e0381b4ce23ff92f8170080c97678040fc5b08da85e9e292292aba67fdac6c34"},
+    {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:23d32a2594cb5d565d358a92e151315d1b2268bc10f4610d098f96b147370136"},
+    {file = "yarl-1.9.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ddb2a5c08a4eaaba605340fdee8fc08e406c56617566d9643ad8bf6852778fc7"},
+    {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:26a1dc6285e03f3cc9e839a2da83bcbf31dcb0d004c72d0730e755b33466c30e"},
+    {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:18580f672e44ce1238b82f7fb87d727c4a131f3a9d33a5e0e82b793362bf18b4"},
+    {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:29e0f83f37610f173eb7e7b5562dd71467993495e568e708d99e9d1944f561ec"},
+    {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:1f23e4fe1e8794f74b6027d7cf19dc25f8b63af1483d91d595d4a07eca1fb26c"},
+    {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:db8e58b9d79200c76956cefd14d5c90af54416ff5353c5bfd7cbe58818e26ef0"},
+    {file = "yarl-1.9.4-cp39-cp39-win32.whl", hash = "sha256:c7224cab95645c7ab53791022ae77a4509472613e839dab722a72abe5a684575"},
+    {file = "yarl-1.9.4-cp39-cp39-win_amd64.whl", hash = "sha256:824d6c50492add5da9374875ce72db7a0733b29c2394890aef23d533106e2b15"},
+    {file = "yarl-1.9.4-py3-none-any.whl", hash = "sha256:928cecb0ef9d5a7946eb6ff58417ad2fe9375762382f1bf5c55e61645f2c43ad"},
+    {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"},
 ]
 
 [package.dependencies]
@@ -3271,5 +3411,5 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.8,<3.12"
-content-hash = "518575779b9d1f50cbd30d5a49857c2f73029c772f402f678f0d0d83d1bb518e"
+python-versions = ">=3.8,<3.13"
+content-hash = "41d52b4a8afee9799c88139eb283ae0ef90e7e4ec45b7ece985ea39a5cc401d9"
diff --git a/pyproject.toml b/pyproject.toml
index 566c2a53..1a716c7c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "kwja"
-version = "2.2.0"
+version = "2.3.0"
 description = "A unified Japanese analyzer based on foundation models"
 authors = [
     "Hirokazu Kiyomaru <kiyomaru@i.kyoto-u.ac.jp>",
@@ -31,6 +31,7 @@ classifiers = [
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
     "Topic :: Scientific/Engineering",
     "Topic :: Text Processing",
 ]
@@ -46,29 +47,36 @@ exclude = [
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.8,<3.12"
-torch = ">=1.11,!=2.0.1,!=2.1.0"  # https://github.com/pytorch/pytorch/issues/100974
-transformers = { version = "~4.32.1", extras = ["sentencepiece"] }
-tokenizers = "^0.13.2"
-pytorch-lightning = "~2.0.0"  # As "lightning" comes with many extra dependencies, we stay with "pytorch-lightning"
+python = ">=3.8,<3.13"
+torch = ">=1.11,!=2.0.1,!=2.1.0"  # https://github.com/pytorch/pytorch/issues/100974ypmun
+numpy = [
+    { version = "~1.24.4", python = "<3.9" },
+    { version = ">=1.26", python = ">=3.9" },
+]
+transformers = { version = "~4.36.2", extras = ["sentencepiece"] }
+tokenizers = "^0.15.1"
+pytorch-lightning = "~2.1.0"  # As "lightning" comes with many extra dependencies, we stay with "pytorch-lightning"
 omegaconf = "^2.1"
 hydra-core = "^1.2"
-rhoknp = "~1.5.0"
+rhoknp = "~1.6.0"
 typer = ">=0.9.0"
 jinf = "^1.0.4"
 pure-cdb = "^4.0"
 rich = ">=12.4"
 pyyaml = "^6.0"
 regex = "^2023.8"
-cohesion-tools = "^0.5.4"
+cohesion-tools = "^0.5.7"
 importlib-resources = { version = "^6.0", python = "<3.9" }
 
 [tool.poetry.group.dev.dependencies]
 torchmetrics = "^1.0"
 seqeval = "^1.2"
-scikit-learn = "^1.3"
-Levenshtein = "^0.21.0"
-pandas = "^2.0"
+scikit-learn = [
+    { version = "^1.3", python = "<3.9" },
+    { version = "^1.4", python = ">=3.9" },
+]
+Levenshtein = ">=0.21.0"
+cohesion-tools = { version = "^0.5.7", extras = ["eval"] }
 python-dotenv = "^1.0"
 jaconv = "^0.3.4"
 ipython = [
@@ -78,15 +86,15 @@ ipython = [
 ipdb = "^0.13.13"
 types-attrs = "^19.1"
 types-pyyaml = "^6.0.12.9"
-wandb = "^0.15.0"
+wandb = "^0.16.0"
 
 [tool.poetry.group.test.dependencies]
 torchmetrics = "^1.0"
 seqeval = "^1.2"
-Levenshtein = "^0.21.0"
+Levenshtein = ">=0.21.0"
 pandas = "^2.0"
 jaconv = "^0.3.4"
-pytest = "^7.1"
+pytest = "^8.0"
 pytest-cov = "^4.0"
 pytest-profiling = "^1.7"
 
diff --git a/src/kwja/callbacks/base_module_writer.py b/src/kwja/callbacks/base_module_writer.py
index 44d691e3..b815748b 100644
--- a/src/kwja/callbacks/base_module_writer.py
+++ b/src/kwja/callbacks/base_module_writer.py
@@ -36,7 +36,7 @@ def write_on_batch_end(
         batch_idx: int,
         dataloader_idx: int,
     ) -> None:
-        raise NotImplementedError()
+        raise NotImplementedError
 
     def write_on_epoch_end(
         self,
diff --git a/src/kwja/callbacks/typo_module_writer.py b/src/kwja/callbacks/typo_module_writer.py
index f5ddfaa5..57ba4f44 100644
--- a/src/kwja/callbacks/typo_module_writer.py
+++ b/src/kwja/callbacks/typo_module_writer.py
@@ -1,5 +1,5 @@
 from pathlib import Path
-from typing import Any, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Union
 
 import pytorch_lightning as pl
 from transformers import PreTrainedTokenizerBase
@@ -42,13 +42,15 @@ def write_on_batch_end(
             dataloader = trainer.predict_dataloaders[dataloader_idx]
         dataset: Union[TypoDataset, TypoInferenceDataset] = dataloader.dataset
 
-        post_texts = []
+        post_texts: List[str] = []
+        doc_ids: List[str] = []
         for example_id, kdr_predictions, kdr_probabilities, ins_predictions, ins_probabilities in zip(
             *[v.tolist() for v in prediction.values()]
         ):
             if example_id in dataset.stash:
                 texts = dataset.stash.pop(example_id)
-                post_texts.extend(texts)
+                post_texts.extend([t[0] for t in texts])
+                doc_ids.extend([t[1] for t in texts])
 
             example: Union[TypoExample, TypoInferenceExample] = dataset.examples[example_id]
             seq_len: int = len(example.pre_text)
@@ -63,11 +65,18 @@ def write_on_batch_end(
             # the prediction of the dummy token at the end is used for insertion only.
             post_text = apply_edit_operations(example.pre_text, kdr_tags[1 : seq_len + 1], ins_tags[1 : seq_len + 2])
             post_texts.append(post_text)
+            doc_ids.append(example.doc_id)
 
         if batch_idx == len(dataloader) - 1:
             for texts in dataset.stash.values():
-                post_texts.extend(texts)
+                post_texts.extend([t[0] for t in texts])
+                doc_ids.extend([t[1] for t in texts])
             dataset.stash.clear()
 
-        output_string = "".join(post_text + "\nEOD\n" for post_text in post_texts)
+        output_string = ""
+        for text, doc_id in zip(post_texts, doc_ids):
+            if doc_id != "":
+                output_string += f"# D-ID:{doc_id}\n"
+            output_string += text + "\nEOD\n"
+
         self.write_output_string(output_string)
diff --git a/src/kwja/cli/cli.py b/src/kwja/cli/cli.py
index a9b577e0..e77f4098 100644
--- a/src/kwja/cli/cli.py
+++ b/src/kwja/cli/cli.py
@@ -22,6 +22,7 @@
 from kwja.cli.config import CLIConfig, Device, ModelSize, get_kwja_config_file
 from kwja.cli.utils import download_checkpoint, prepare_device
 from kwja.datamodule.datamodule import DataModule
+from kwja.datamodule.datasets.utils import add_doc_ids, add_sent_ids
 from kwja.modules import CharModule, Seq2SeqModule, TypoModule, WordModule
 from kwja.utils.constants import TRANSLATION_TABLE
 from kwja.utils.logging_util import filter_logs
@@ -108,7 +109,13 @@ def _load_datamodule(self, input_file: Path) -> DataModule:
         return datamodule
 
     def export_prediction(self) -> str:
-        return self.destination.read_text()
+        output_text = ""
+        for line in self.destination.read_text().strip().split("\n"):
+            if line.startswith("# D-ID:"):
+                pass
+            else:
+                output_text += line + "\n"
+        return output_text
 
 
 class CharModuleProcessor(BaseModuleProcessor):
@@ -211,14 +218,16 @@ def run(self, input_documents: List[Document], interactive: bool = False) -> str
         input_documents = [document for document in input_documents if document.text != ""]
         if len(input_documents) == 0:
             return ""
+        add_doc_ids(input_documents)
+        add_sent_ids(input_documents)
         if self.processors[0].input_format == InputFormat.RAW:
-            self.initial_destination.write_text(
-                "".join(normalize_text(input_document.text) + "\nEOD\n" for input_document in input_documents)
-            )
+            output_text = ""
+            for input_document in input_documents:
+                output_text += f"# D-ID:{input_document.doc_id}\n"
+                output_text += normalize_text(input_document.text) + "\nEOD\n"
+            self.initial_destination.write_text(output_text)
         elif self.processors[0].input_format == InputFormat.JUMANPP:
             self.initial_destination.write_text("".join(document.to_jumanpp() + "\n" for document in input_documents))
-        # elif self.processors[0].input_format == InputFormat.knp:
-        #     self.initial_destination.write_text("".join(document.to_knp() + "\n" for document in input_documents))
         else:
             raise AssertionError  # unreachable
 
@@ -277,7 +286,7 @@ def _load_document_from_text(text: str, input_format: InputFormat) -> Document:
 def _version_callback(value: bool) -> None:
     if value is True:
         print(f"KWJA {kwja.__version__}")
-        raise typer.Exit()
+        raise typer.Exit
 
 
 def _tasks_callback(value: str) -> str:
@@ -289,7 +298,7 @@ def _tasks_callback(value: str) -> str:
             tasks.append(candidate_task)
             values.remove(candidate_task)
     if len(values) == 1:
-        raise typer.BadParameter(f"invalid task is specified: {repr(values[0])}")
+        raise typer.BadParameter(f"invalid task is specified: {values[0]!r}")
     if len(values) > 1:
         raise typer.BadParameter(f"invalid tasks are specified: {', '.join(repr(v) for v in values)}")
     if len(tasks) == 0:
@@ -350,7 +359,7 @@ def main(
     input_documents: Optional[List[Document]] = None
     if text is not None and len(filename) > 0:
         logger.error("ERROR: Please provide text or filename, not both")
-        raise typer.Abort()
+        raise typer.Abort
     elif text is not None:
         input_documents = [_load_document_from_text(text, input_format)]
     elif len(filename) > 0:
@@ -358,7 +367,7 @@ def main(
         for path in filename:
             if path.exists() is False:
                 logger.error(f"ERROR: {path} does not exist")
-                raise typer.Abort()
+                raise typer.Abort
             with path.open() as f:
                 for document_text in _chunk_by_document(f, input_format):
                     input_documents.append(_load_document_from_text(document_text, input_format))
@@ -391,7 +400,7 @@ def main(
         output: str = processor.run(input_documents)
         print(output or "EOD\n", end="")
         processor.refresh()
-        raise typer.Exit()
+        raise typer.Exit
 
     # Interactive mode
     processor.load_all_modules()
diff --git a/src/kwja/cli/utils.py b/src/kwja/cli/utils.py
index 57e33f9f..8cbbf06a 100644
--- a/src/kwja/cli/utils.py
+++ b/src/kwja/cli/utils.py
@@ -90,6 +90,7 @@ def _get_model_version() -> str:
         ("2", "0"): "v2.0",
         ("2", "1"): "v2.1",
         ("2", "2"): "v2.2",
+        ("2", "3"): "v2.2",
     }
     version_fields = kwja.__version__.split(".")
     return version_map[(version_fields[0], version_fields[1])]
diff --git a/src/kwja/datamodule/datamodule.py b/src/kwja/datamodule/datamodule.py
index 2ce5a032..52e4054b 100644
--- a/src/kwja/datamodule/datamodule.py
+++ b/src/kwja/datamodule/datamodule.py
@@ -89,7 +89,7 @@ def token_dataclass_data_collator(batch_features: List[Any]) -> Dict[str, Union[
     first_features: Any = batch_features[0]
     assert is_dataclass(first_features), "Data must be a dataclass"
 
-    token_indices = torch.arange(max(sum(getattr(fs, "attention_mask")) for fs in batch_features))
+    token_indices = torch.arange(max(sum(fs.attention_mask) for fs in batch_features))
 
     batch: Dict[str, Union[Tensor, List[str]]] = {}
     for field in fields(first_features):
@@ -113,8 +113,8 @@ def word_dataclass_data_collator(batch_features: List[Any]) -> Dict[str, Union[T
     first_features: Any = batch_features[0]
     assert is_dataclass(first_features), "Data must be a dataclass"
 
-    token_indices = torch.arange(max(sum(getattr(fs, "attention_mask")) for fs in batch_features))
-    word_indices = torch.arange(max(sum(any(row) for row in getattr(fs, "subword_map")) for fs in batch_features))
+    token_indices = torch.arange(max(sum(fs.attention_mask) for fs in batch_features))
+    word_indices = torch.arange(max(sum(any(row) for row in fs.subword_map) for fs in batch_features))
 
     batch: Dict[str, Union[Tensor, List[str]]] = {}
     for field in fields(first_features):
diff --git a/src/kwja/datamodule/datasets/base.py b/src/kwja/datamodule/datasets/base.py
index f6ba33eb..a7e41fe8 100644
--- a/src/kwja/datamodule/datasets/base.py
+++ b/src/kwja/datamodule/datasets/base.py
@@ -1,4 +1,5 @@
 import logging
+import sys
 from abc import ABC
 from concurrent.futures import ProcessPoolExecutor
 from pathlib import Path
@@ -11,6 +12,8 @@
 from kwja.utils.logging_util import track
 from kwja.utils.sub_document import SequenceSplitter, SpanCandidate, to_sub_doc_id
 
+sys.setrecursionlimit(5000)
+
 logger = logging.getLogger(__name__)
 
 ExampleType = TypeVar("ExampleType")
diff --git a/src/kwja/datamodule/datasets/char_inference.py b/src/kwja/datamodule/datasets/char_inference.py
index 4dd654f1..1e7a065c 100644
--- a/src/kwja/datamodule/datasets/char_inference.py
+++ b/src/kwja/datamodule/datasets/char_inference.py
@@ -1,5 +1,4 @@
 import logging
-from datetime import datetime
 from typing import Dict, List, Optional
 
 from omegaconf import ListConfig
@@ -7,9 +6,9 @@
 from transformers import BatchEncoding, PreTrainedTokenizerBase
 from transformers.utils import PaddingStrategy
 
-import kwja
 from kwja.datamodule.datasets.base import BaseDataset, FullAnnotatedDocumentLoaderMixin
 from kwja.datamodule.datasets.char import CharModuleFeatures
+from kwja.datamodule.datasets.utils import add_doc_ids, add_sent_ids, create_documents_from_raw_texts
 from kwja.datamodule.examples import CharInferenceExample
 from kwja.utils.logging_util import track
 
@@ -26,7 +25,9 @@ def __init__(
         **_,
     ) -> None:
         super().__init__(tokenizer, max_seq_length)
-        documents = self._build_documents_from_texts(list(texts), doc_id_prefix)
+        documents = create_documents_from_raw_texts(texts)
+        add_doc_ids(documents, doc_id_prefix)
+        documents = self._add_tentative_sentence_boundary(documents)
         super(BaseDataset, self).__init__(documents, tokenizer, max_seq_length, -1)  # document_split_stride must be -1
         self.examples: List[CharInferenceExample] = self._load_examples(self.doc_id2document)
 
@@ -61,19 +62,8 @@ def encode(self, example: CharInferenceExample) -> CharModuleFeatures:
         )
 
     @staticmethod
-    def _build_documents_from_texts(texts: List[str], doc_id_prefix: Optional[str]) -> List[Document]:
+    def _add_tentative_sentence_boundary(documents: List[Document]) -> List[Document]:
         senter = RegexSenter()
-        # split text into sentences
-        documents: List[Document] = [
-            senter.apply_to_document(text) for text in track(texts, description="Loading documents")
-        ]
-        if doc_id_prefix is None:
-            doc_id_prefix = datetime.now().strftime("%Y%m%d%H%M")
-        doc_id_width = len(str(len(documents)))
-        sent_id_width = max((len(str(len(d.sentences))) for d in documents), default=0)
-        for doc_index, document in enumerate(documents):
-            document.doc_id = f"{doc_id_prefix}-{doc_index:0{doc_id_width}}"
-            for sent_index, sentence in enumerate(document.sentences):
-                sentence.sid = f"{document.doc_id}-{sent_index:0{sent_id_width}}"
-                sentence.misc_comment = f"kwja:{kwja.__version__}"
+        documents = [senter.apply_to_document(doc) if doc.is_senter_required() else doc for doc in documents]
+        add_sent_ids(documents)
         return documents
diff --git a/src/kwja/datamodule/datasets/typo.py b/src/kwja/datamodule/datasets/typo.py
index 4ffe22e3..d4c6bf81 100644
--- a/src/kwja/datamodule/datasets/typo.py
+++ b/src/kwja/datamodule/datasets/typo.py
@@ -52,7 +52,7 @@ def __init__(
         )
 
         self.examples: List[TypoExample] = self._load_examples(self.path)
-        self.stash: Dict[int, List[str]] = defaultdict(list)
+        self.stash: Dict[int, List[Tuple[str, str]]] = defaultdict(list)
         assert len(self) > 0
 
     @staticmethod
@@ -61,7 +61,7 @@ def _load_examples(example_dir: Path) -> List[TypoExample]:
         example_id = 0
         for path in track(sorted(example_dir.glob("**/*.jsonl")), description="Loading documents"):
             for line in path.read_text().strip().split("\n"):
-                examples.append(TypoExample(**json.loads(line), example_id=example_id))
+                examples.append(TypoExample(**json.loads(line), example_id=example_id, doc_id=""))
                 example_id += 1
         return examples
 
diff --git a/src/kwja/datamodule/datasets/typo_inference.py b/src/kwja/datamodule/datasets/typo_inference.py
index 93dc72d9..6e7c081a 100644
--- a/src/kwja/datamodule/datasets/typo_inference.py
+++ b/src/kwja/datamodule/datasets/typo_inference.py
@@ -1,12 +1,14 @@
 from collections import defaultdict
-from typing import Dict, List
+from typing import Dict, List, Tuple
 
 from omegaconf import ListConfig
+from rhoknp import Document
 from transformers import BatchEncoding, PreTrainedTokenizerBase
 from transformers.utils import PaddingStrategy
 
 from kwja.datamodule.datasets.base import BaseDataset
 from kwja.datamodule.datasets.typo import TypoModuleFeatures
+from kwja.datamodule.datasets.utils import create_documents_from_raw_texts
 from kwja.datamodule.examples import TypoInferenceExample
 from kwja.utils.constants import DUMMY_TOKEN
 from kwja.utils.logging_util import track
@@ -20,20 +22,20 @@ def __init__(
         max_seq_length: int,
     ) -> None:
         super().__init__(tokenizer, max_seq_length)
-
+        documents: List[Document] = create_documents_from_raw_texts(texts)
         self.examples: List[TypoInferenceExample] = []
-        self.stash: Dict[int, List[str]] = defaultdict(list)
+        self.stash: Dict[int, List[Tuple[str, str]]] = defaultdict(list)
         example_id = 0
-        for text in track(texts, description="Loading documents"):
-            text = text.strip()
+        for document in track(documents, description="Loading documents"):
+            text = document.text.strip()
             if len(self.tokenizer.tokenize(text)) == len(text) <= max_seq_length - 3:  # -3: [CLS], DUMMY_TOKEN, [SEP]
-                self.examples.append(TypoInferenceExample(example_id=example_id, pre_text=text))
+                self.examples.append(TypoInferenceExample(example_id=example_id, doc_id=document.doc_id, pre_text=text))
                 example_id += 1
             else:
-                self.stash[example_id].append(text)
+                self.stash[example_id].append((text, document.doc_id))
         if len(self.examples) == 0:
             # len(self.examples) == 0だとwriterが呼ばれないのでダミーを追加
-            self.examples.append(TypoInferenceExample(example_id=example_id, pre_text=""))
+            self.examples.append(TypoInferenceExample(example_id=example_id, pre_text="", doc_id="dummy"))
 
     def encode(self, example: TypoInferenceExample) -> TypoModuleFeatures:
         encoding: BatchEncoding = self.tokenizer(
diff --git a/src/kwja/datamodule/datasets/utils.py b/src/kwja/datamodule/datasets/utils.py
new file mode 100644
index 00000000..bd2be401
--- /dev/null
+++ b/src/kwja/datamodule/datasets/utils.py
@@ -0,0 +1,39 @@
+from datetime import datetime
+from typing import List, Optional, Sequence
+
+from rhoknp import Document
+
+
+def create_documents_from_raw_texts(texts: Sequence[str]) -> List[Document]:
+    documents: List[Document] = []
+    for text in texts:
+        raw_text = ""
+        doc_id = ""
+        for line in text.split("\n"):
+            if line.startswith("# D-ID:"):
+                doc_id = line.split()[1].split(":")[1]
+            else:
+                raw_text += line + "\n"
+        document = Document.from_raw_text(raw_text)
+        document.doc_id = doc_id
+        documents.append(document)
+    return documents
+
+
+def add_doc_ids(documents: Sequence[Document], doc_id_prefix: Optional[str] = None) -> None:
+    if doc_id_prefix is None:
+        doc_id_prefix = datetime.now().strftime("%Y%m%d%H%M")
+    doc_id_width = len(str(len(documents)))
+    for idx, document in enumerate(documents):
+        if document.doc_id == "":
+            document.doc_id = f"{doc_id_prefix}-{idx:0{doc_id_width}}"
+
+
+def add_sent_ids(documents: Sequence[Document]) -> None:
+    sent_id_width = max((len(str(len(doc.sentences))) for doc in documents if not doc.is_senter_required()), default=0)
+    for document in documents:
+        if document.is_senter_required():
+            continue
+        for idx, sentence in enumerate(document.sentences):
+            if sentence.sent_id == "":
+                sentence.sent_id = f"{document.doc_id}-{idx:0{sent_id_width}}"
diff --git a/src/kwja/datamodule/examples/typo.py b/src/kwja/datamodule/examples/typo.py
index ecefb524..401d63b8 100644
--- a/src/kwja/datamodule/examples/typo.py
+++ b/src/kwja/datamodule/examples/typo.py
@@ -5,6 +5,7 @@
 @dataclass(frozen=True)
 class TypoExample:
     example_id: int
+    doc_id: str
     pre_text: str
     post_text: str
     kdrs: List[str]
@@ -14,4 +15,5 @@ class TypoExample:
 @dataclass(frozen=True)
 class TypoInferenceExample:
     example_id: int
+    doc_id: str
     pre_text: str
diff --git a/src/kwja/metrics/base.py b/src/kwja/metrics/base.py
index 6feba9bc..e02c4b88 100644
--- a/src/kwja/metrics/base.py
+++ b/src/kwja/metrics/base.py
@@ -16,7 +16,7 @@ def __init__(self, max_seq_length: int) -> None:
             self.add_state(state_name, default=[], dist_reduce_fx="cat")
 
     def _pad(self, kwargs: Dict[str, torch.Tensor]) -> None:
-        raise NotImplementedError()
+        raise NotImplementedError
 
     def update(self, kwargs: Dict[str, torch.Tensor]) -> None:
         self._pad(kwargs)
diff --git a/src/kwja/modules/base.py b/src/kwja/modules/base.py
index cfdad3f1..5ea0b3bb 100644
--- a/src/kwja/modules/base.py
+++ b/src/kwja/modules/base.py
@@ -115,7 +115,7 @@ class _EmptyInit(TorchFunctionMode):
         model.load_state_dict(torch.load("checkpoint.pt"))
     """
 
-    def __init__(self, enabled: bool = True):
+    def __init__(self, enabled: bool = True) -> None:
         super().__init__()
         self.enabled = enabled
 
diff --git a/src/kwja/modules/char.py b/src/kwja/modules/char.py
index 36b8e93f..7d944929 100644
--- a/src/kwja/modules/char.py
+++ b/src/kwja/modules/char.py
@@ -50,7 +50,7 @@ def forward(self, batch: Any) -> Dict[str, torch.Tensor]:
             "word_norm_op_logits": self.word_norm_op_tagger(encoded.last_hidden_state),
         }
 
-    def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
+    def training_step(self, batch: Any) -> torch.Tensor:
         ret: Dict[str, torch.Tensor] = self(batch)
         sent_segmentation_loss = compute_token_mean_loss(
             ret["sent_segmentation_logits"], batch["sent_segmentation_labels"]
@@ -65,7 +65,7 @@ def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
         return sent_segmentation_loss + word_segmentation_loss + word_normalization_loss
 
     def validation_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"word_norm_op_labels": batch["word_norm_op_labels"]})
         metric = self.valid_corpus2metric[self.valid_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -89,7 +89,7 @@ def on_validation_epoch_end(self) -> None:
             self.log(f"valid/{key}", mean_score)
 
     def test_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"word_norm_op_labels": batch["word_norm_op_labels"]})
         metric = self.test_corpus2metric[self.test_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -112,7 +112,7 @@ def on_test_epoch_end(self) -> None:
             mean_score = mean(metrics_log[corpus][key] for corpus in self.test_corpora if key in metrics_log[corpus])
             self.log(f"test/{key}", mean_score)
 
-    def predict_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> Dict[str, torch.Tensor]:
+    def predict_step(self, batch: Any) -> Dict[str, torch.Tensor]:
         ret: Dict[str, torch.Tensor] = self(batch)
         return {
             "example_ids": batch["example_ids"],
diff --git a/src/kwja/modules/components/crf.py b/src/kwja/modules/components/crf.py
index 9e41a220..6f7518f0 100644
--- a/src/kwja/modules/components/crf.py
+++ b/src/kwja/modules/components/crf.py
@@ -1,5 +1,5 @@
 from math import sqrt
-from typing import Literal, Optional, Tuple
+from typing import List, Literal, Optional, Tuple
 
 import torch
 import torch.nn as nn
@@ -76,7 +76,7 @@ def _compute_numerator(self, emissions: torch.Tensor, tags: torch.Tensor, mask:
         tail_tags = tags[indices, tail_indices]
         max_tail_index = int(tail_indices.max())
 
-        score = self.start_transitions[head_tags] + emissions[indices, head_indices, head_tags]
+        score: torch.Tensor = self.start_transitions[head_tags] + emissions[indices, head_indices, head_tags]
         for j in range(min_head_index + 1, max_tail_index + 1):
             condition = torch.logical_and(mask[:, j] == 1, head_indices != j)
             next_score = score + self.transitions[tags[:, j - 1], tags[:, j]] + emissions[indices, j, tags[:, j]]
@@ -119,26 +119,30 @@ def viterbi_decode(self, emissions: torch.Tensor, mask: torch.Tensor) -> torch.T
         tail_indices = torch.amax(arange * mask, dim=1)
         max_tail_index = int(tail_indices.max())
 
-        score = self.start_transitions + emissions[indices, head_indices]  # (b, num_tags)
-        history = []
+        score: torch.Tensor = self.start_transitions + emissions[indices, head_indices]  # (b, num_tags)
+        history: List[torch.Tensor] = []
         for j in range(min_head_index + 1, max_tail_index + 1):
             condition = torch.logical_and(mask[:, j] == 1, head_indices != j)
-            broadcast_score = score.unsqueeze(2)  # (b, num_tags, 1)
-            broadcast_emissions = emissions[:, j].unsqueeze(1)  # (b, 1, num_tags)
-            next_score = broadcast_score + self.transitions + broadcast_emissions  # (b, num_tags, num_tags)
+            broadcast_score: torch.Tensor = score.unsqueeze(2)  # (b, num_tags, 1)
+            broadcast_emissions: torch.Tensor = emissions[:, j].unsqueeze(1)  # (b, 1, num_tags)
+            next_score: torch.Tensor = (
+                broadcast_score + self.transitions + broadcast_emissions
+            )  # (b, num_tags, num_tags)
             next_score, max_indices = next_score.max(dim=1)  # (b, num_tags)
             score = torch.where(condition.unsqueeze(1), next_score, score)  # (b, num_tags)
             history.append(max_indices)
         score += self.end_transitions  # (b, num_tags)
 
-        batch_best_tags = []
+        batch_best_tags: List[List[int]] = []
         for i in range(batch_size):
             head_index, tail_index = int(head_indices[i]), int(tail_indices[i])
             _, best_tag = score[i].max(dim=0)
-            best_tags = [best_tag.item()]
+            assert isinstance(best_tag_int := best_tag.item(), int)
+            best_tags: List[int] = [best_tag_int]
             for max_indices in history[head_index - min_head_index : tail_index - min_head_index][::-1]:
                 best_tag = max_indices[i][best_tags[-1]]
-                best_tags.append(best_tag.item())
+                assert isinstance(best_tag_int := best_tag.item(), int)
+                best_tags.append(best_tag_int)
             best_tags += [self.tags.index("O")] * head_index
             best_tags = best_tags[::-1]
             best_tags += [self.tags.index("O")] * (seq_len - tail_index - 1)
diff --git a/src/kwja/modules/components/deberta_v2.py b/src/kwja/modules/components/deberta_v2.py
index 049ad1bb..e9215d0e 100644
--- a/src/kwja/modules/components/deberta_v2.py
+++ b/src/kwja/modules/components/deberta_v2.py
@@ -35,7 +35,7 @@
 
 # Copied from transformers.models.deberta.modeling_deberta.DebertaAttention with Deberta->DebertaV2
 class DebertaV2Attention(nn.Module):
-    def __init__(self, config):
+    def __init__(self, config) -> None:
         super().__init__()
         self.self = DisentangledSelfAttention(config)
         self.output = DebertaV2SelfOutput(config)
@@ -72,7 +72,7 @@ def forward(
 
 # Copied from transformers.models.deberta.modeling_deberta.DebertaLayer with Deberta->DebertaV2
 class DebertaV2Layer(nn.Module):
-    def __init__(self, config):
+    def __init__(self, config) -> None:
         super().__init__()
         self.attention = DebertaV2Attention(config)
         self.intermediate = DebertaV2Intermediate(config)
@@ -108,7 +108,7 @@ def forward(
 class DebertaV2Encoder(nn.Module):
     """Modified BertEncoder with relative position bias support"""
 
-    def __init__(self, config):
+    def __init__(self, config) -> None:
         super().__init__()
 
         self.layer = nn.ModuleList([DebertaV2Layer(config) for _ in range(config.num_hidden_layers)])
@@ -277,7 +277,7 @@ class DisentangledSelfAttention(nn.Module):
 
     """
 
-    def __init__(self, config):
+    def __init__(self, config) -> None:
         super().__init__()
         if config.hidden_size % config.num_attention_heads != 0:
             raise ValueError(
@@ -497,7 +497,7 @@ def disentangled_attention_bias(self, query_layer, key_layer, relative_pos, rel_
 )
 # Copied from transformers.models.deberta.modeling_deberta.DebertaModel with Deberta->DebertaV2
 class DebertaV2Model(DebertaV2PreTrainedModel):
-    def __init__(self, config):
+    def __init__(self, config) -> None:
         super().__init__(config)
 
         self.embeddings = DebertaV2Embeddings(config)
@@ -587,6 +587,7 @@ def forward(
             query_states = encoded_layers[-1]
             rel_embeddings = self.encoder.get_rel_embedding()
             attention_mask = self.encoder.get_attention_mask(attention_mask)
+            assert special_token_indices is not None
             rel_pos = self.encoder.get_rel_pos(embedding_output, special_token_indices)
             for layer in layers[1:]:
                 query_states = layer(
diff --git a/src/kwja/modules/functions/loss.py b/src/kwja/modules/functions/loss.py
index bdbebd80..893301c7 100644
--- a/src/kwja/modules/functions/loss.py
+++ b/src/kwja/modules/functions/loss.py
@@ -35,6 +35,7 @@ def compute_multi_label_token_mean_loss(
     if input_.isnan().any().item() is True:
         return torch.tensor(float("nan"), dtype=input_.dtype, device=input_.device)
     else:
+        target = torch.where(mask, target, torch.zeros_like(target))
         losses = nn.functional.binary_cross_entropy(input_, target.float(), reduction="none")  # (b, seq, num_features)
         # features の軸は和をとる
         losses = (losses * mask).sum(dim=2)  # (b, seq)
diff --git a/src/kwja/modules/seq2seq.py b/src/kwja/modules/seq2seq.py
index a87f1cab..9f90909c 100644
--- a/src/kwja/modules/seq2seq.py
+++ b/src/kwja/modules/seq2seq.py
@@ -43,7 +43,7 @@ def forward(self, batch: Any) -> Dict[str, torch.Tensor]:
         )
         return {"loss": output.loss, "logits": output.logits}
 
-    def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
+    def training_step(self, batch: Any) -> torch.Tensor:
         ret: Dict[str, torch.Tensor] = self(batch)
         self.log("train/loss", ret["loss"])
         return ret["loss"]
@@ -84,7 +84,7 @@ def on_test_epoch_end(self) -> None:
             mean_score = mean(metrics_log[corpus][key] for corpus in self.test_corpora if key in metrics_log[corpus])
             self.log(f"test/{key}", mean_score)
 
-    def predict_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> Any:
+    def predict_step(self, batch: Any) -> Dict[str, Any]:
         generations = self.encoder_decoder.generate(
             input_ids=batch["input_ids"],
             attention_mask=batch["attention_mask"],
diff --git a/src/kwja/modules/typo.py b/src/kwja/modules/typo.py
index a2c8560b..a119a128 100644
--- a/src/kwja/modules/typo.py
+++ b/src/kwja/modules/typo.py
@@ -44,7 +44,7 @@ def forward(self, batch: Any) -> Dict[str, torch.Tensor]:
             "ins_logits": self.ins_tagger(encoded.last_hidden_state),
         }
 
-    def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
+    def training_step(self, batch: Any) -> torch.Tensor:
         ret: Dict[str, torch.Tensor] = self(batch)
         kdr_loss = compute_token_mean_loss(ret["kdr_logits"], batch["kdr_labels"])
         self.log("train/kdr_loss", kdr_loss)
@@ -53,7 +53,7 @@ def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
         return kdr_loss + ins_loss
 
     def validation_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"kdr_labels": batch["kdr_labels"], "ins_labels": batch["ins_labels"]})
         metric = self.valid_corpus2metric[self.valid_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -73,7 +73,7 @@ def on_validation_epoch_end(self) -> None:
             self.log(f"valid/{key}", mean_score)
 
     def test_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"kdr_labels": batch["kdr_labels"], "ins_labels": batch["ins_labels"]})
         metric = self.test_corpus2metric[self.test_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -92,7 +92,7 @@ def on_test_epoch_end(self) -> None:
             mean_score = mean(metrics_log[corpus][key] for corpus in self.test_corpora if key in metrics_log[corpus])
             self.log(f"test/{key}", mean_score)
 
-    def predict_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> Dict[str, torch.Tensor]:
+    def predict_step(self, batch: Any) -> Dict[str, torch.Tensor]:
         ret: Dict[str, torch.Tensor] = self(batch)
         kdr_probabilities = ret["kdr_logits"].softmax(dim=2)
         kdr_max_probabilities, kdr_predictions = kdr_probabilities.max(dim=2)
diff --git a/src/kwja/modules/word.py b/src/kwja/modules/word.py
index f792d378..cf415ffb 100644
--- a/src/kwja/modules/word.py
+++ b/src/kwja/modules/word.py
@@ -155,7 +155,7 @@ def forward(self, batch: Any) -> Dict[str, torch.Tensor]:
             "discourse_logits": self.discourse_relation_analyzer(pooled),
         }
 
-    def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
+    def training_step(self, batch: Any) -> torch.Tensor:
         ret: Dict[str, torch.Tensor] = self(batch)
         loss_log: Dict[str, torch.Tensor] = {}
         if WordTask.READING_PREDICTION in self.training_tasks:
@@ -200,7 +200,7 @@ def training_step(self, batch: Any, batch_idx: int) -> torch.Tensor:
         return torch.stack(list(loss_log.values())).sum()
 
     def validation_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"discourse_labels": batch["discourse_labels"]})
         metric = self.valid_corpus2metric[self.valid_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -208,10 +208,9 @@ def validation_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -
     def on_validation_epoch_end(self) -> None:
         metrics_log: Dict[str, Dict[str, float]] = {}
         for corpus, metric in self.valid_corpus2metric.items():
-            dataset = self.trainer.val_dataloaders[corpus].dataset
             metric.set_properties(
                 {
-                    "dataset": dataset,
+                    "dataset": self.trainer.val_dataloaders[corpus].dataset,
                     "reading_id2reading": self.reading_id2reading,
                     "training_tasks": self.training_tasks,
                 }
@@ -235,7 +234,7 @@ def on_validation_epoch_end(self) -> None:
             self.log(f"valid/{key}", mean_score)
 
     def test_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None:
-        kwargs = self.predict_step(batch, batch_idx, dataloader_idx=dataloader_idx)
+        kwargs = self.predict_step(batch)
         kwargs.update({"discourse_labels": batch["discourse_labels"]})
         metric = self.test_corpus2metric[self.test_corpora[dataloader_idx]]
         metric.update(kwargs)
@@ -243,10 +242,9 @@ def test_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> None
     def on_test_epoch_end(self) -> None:
         metrics_log: Dict[str, Dict[str, float]] = {}
         for corpus, metric in self.test_corpus2metric.items():
-            dataset = self.trainer.test_dataloaders[corpus].dataset
             metric.set_properties(
                 {
-                    "dataset": dataset,
+                    "dataset": self.trainer.test_dataloaders[corpus].dataset,
                     "reading_id2reading": self.reading_id2reading,
                     "training_tasks": self.training_tasks,
                 }
@@ -269,7 +267,7 @@ def on_test_epoch_end(self) -> None:
             mean_score = mean(metrics_log[corpus][key] for corpus in self.test_corpora if key in metrics_log[corpus])
             self.log(f"test/{key}", mean_score)
 
-    def predict_step(self, batch: Any, batch_idx: int, dataloader_idx: int = 0) -> Dict[str, torch.Tensor]:
+    def predict_step(self, batch: Any) -> Dict[str, torch.Tensor]:
         ret: Dict[str, torch.Tensor] = self(batch)
         ne_predictions = self.crf.viterbi_decode(ret["ne_logits"], batch["ne_mask"])
         discourse_probabilities = ret["discourse_logits"].softmax(dim=3)
diff --git a/src/kwja/utils/kanjidic.py b/src/kwja/utils/kanjidic.py
index 2173fe41..be9007f3 100644
--- a/src/kwja/utils/kanjidic.py
+++ b/src/kwja/utils/kanjidic.py
@@ -5,7 +5,7 @@
 
 
 class KanjiDic:
-    def __init__(self, fpath: str):
+    def __init__(self, fpath: str) -> None:
         self.entries: Dict[str, Any] = {
             "°": {
                 "reading": ["ど"],
diff --git a/src/kwja/utils/reading_prediction.py b/src/kwja/utils/reading_prediction.py
index 0d0a1455..c4369f58 100644
--- a/src/kwja/utils/reading_prediction.py
+++ b/src/kwja/utils/reading_prediction.py
@@ -149,7 +149,7 @@ class Node:
                     #     kanji_reading = kanji_reading.split(".")[0]
                     if j + len(kanji_reading) > len(reading):
                         continue
-                    reading_part = reading[j : j + len(kanji_reading)]  # noqa: E203
+                    reading_part = reading[j : j + len(kanji_reading)]
                     if reading_part == kanji_reading:
                         node = Node(i=i, j=j, wI=1, wJ=len(kanji_reading), cost=0)
                         td_lattice[i][j].append(node)
@@ -243,7 +243,7 @@ class Node:
         boundaries.pop(0)
         while True:
             wI, wJ = seg.pop(0)
-            subreading += reading[posJ : posJ + wJ]  # noqa: E203
+            subreading += reading[posJ : posJ + wJ]
             posI += wI
             posJ += wJ
             if posI == boundaries[0]:
diff --git a/src/kwja/utils/word_normalization.py b/src/kwja/utils/word_normalization.py
index 225b8594..757db3ff 100644
--- a/src/kwja/utils/word_normalization.py
+++ b/src/kwja/utils/word_normalization.py
@@ -42,9 +42,9 @@ def get_word_norm_op_tags(surf: str, normalized: str) -> List[str]:
         raise ValueError(f"failed to construct normalization labels to convert {surf} to {normalized}")
     d = np.inf * np.ones((surf_len, normalized_len), dtype=np.int32)
     dops: List[List[str]] = []
-    for i in range(surf_len):
+    for _ in range(surf_len):
         dops.append([])
-        for j in range(normalized_len):
+        for _ in range(normalized_len):
             dops[-1].append("_")
     d[0, 0] = 0
     dops[0][0] = ""
@@ -170,9 +170,10 @@ def get_normalized(surf: str, ops: List[str], strict: bool = True) -> str:
 
 
 class SentenceDenormalizer:
-    def __init__(self):
+    def __init__(self) -> None:
         self.mn = MorphemeNormalizer()
         self.md = MorphemeDenormalizer()
+        self._rng = np.random.default_rng()
 
     def denormalize(self, sentence: Sentence, p=0.5) -> None:
         prob = p
@@ -181,7 +182,7 @@ def denormalize(self, sentence: Sentence, p=0.5) -> None:
                 continue
             surf2 = self.md.denormalize(morpheme)
             if surf2 != morpheme.text:
-                if np.random.rand() < prob:
+                if self._rng.random() < prob:
                     morpheme.text = surf2
                     prob *= 0.1
             else:
@@ -195,6 +196,9 @@ def _is_normal_morpheme(self, morpheme):
 
 
 class MorphemeDenormalizer:
+    def __init__(self) -> None:
+        self._rng = np.random.default_rng()
+
     def denormalize(self, morpheme: Morpheme) -> str:
         return self._denormalize(morpheme.surf)
 
@@ -304,11 +308,10 @@ def _denormalize(self, surf: str) -> str:
             return surf2
         probs = np.array(list(map(lambda x: x[1], cands)))
         probs /= probs.sum()
-        idx = np.random.choice(len(probs), p=probs)
+        idx = self._rng.choice(len(probs), p=probs)
         return cands[idx][0]
 
-    @staticmethod
-    def _denormalize_deterministic(surf, var_prolonged=False) -> str:
+    def _denormalize_deterministic(self, surf, var_prolonged=False) -> str:
         # S
         if surf[-1] in UPPER2LOWER:
             surf2 = surf[:-1] + UPPER2LOWER[surf[-1]]
@@ -320,7 +323,7 @@ def _denormalize_deterministic(surf, var_prolonged=False) -> str:
             surf2 = surf[:pos] + c + surf[pos + 1 :]
             return surf2
         # P, E
-        if var_prolonged and np.random.rand() < 0.1:
+        if var_prolonged and self._rng.random() < 0.1:
             prolonged = "〜"
         else:
             prolonged = "ー"


Test patch:
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index e2557d86..13aafcd1 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -7,10 +7,10 @@ jobs:
     name: Run tests with pytest
     runs-on: ubuntu-latest
     strategy:
-      max-parallel: 4
+      max-parallel: 5
       fail-fast: false
       matrix:
-        python-version: [ "3.8", "3.9", "3.10", "3.11" ]
+        python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
@@ -47,7 +47,7 @@ jobs:
       max-parallel: 4
       fail-fast: false
       matrix:
-        python-version: [ "3.8", "3.9", "3.10", "3.11" ]
+        python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ]
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
diff --git a/tests/callbacks/test_word_module_writer.py b/tests/callbacks/test_word_module_writer.py
index f3d97adb..b67ef8fd 100644
--- a/tests/callbacks/test_word_module_writer.py
+++ b/tests/callbacks/test_word_module_writer.py
@@ -387,7 +387,7 @@ def test_write_on_batch_end(word_tokenizer: PreTrainedTokenizerBase, dataset_kwa
     with tempfile.TemporaryDirectory() as tmp_dir:
         writer = WordModuleWriter(AMBIG_SURF_SPECS, destination=tmp_dir / Path("word_prediction.knp"))
         writer.jumandic = build_dummy_jumandic()
-        writer.write_on_batch_end(trainer, module, prediction, None, ..., 0, 0)  # noqa
+        writer.write_on_batch_end(trainer, module, prediction, None, ..., 0, 0)  # type: ignore
         assert isinstance(writer.destination, Path), "destination isn't set"
         assert writer.destination.read_text() == dedent(
             f"""\
diff --git a/tests/cli/test_cli.py b/tests/cli/test_cli.py
index f91aba05..e3677a78 100644
--- a/tests/cli/test_cli.py
+++ b/tests/cli/test_cli.py
@@ -1,4 +1,5 @@
 import io
+import re
 import tempfile
 import textwrap
 from typing import List, Set, Tuple
@@ -14,21 +15,83 @@
 
 
 def test_version():
-    _ = runner.invoke(app, args=["--version"])
+    ret = runner.invoke(app, args=["--version"])
+    assert re.match(r"KWJA \d+\.\d+\.\d+", ret.stdout) is not None
 
 
-def test_device():
-    ret = runner.invoke(app, args=["--device", "tpu"])
-    assert isinstance(ret.exception, SystemExit)
+def test_device_validation():
+    devices: List[str] = ["", "auto", "cpu", "gpu", "INVALID"]
+    base_args: List[str] = ["--model-size", "tiny", "--text", ""]
+    for device in devices:
+        ret = runner.invoke(app, args=[*base_args, "--device", device])
+        if device not in {"auto", "cpu", "gpu"}:
+            assert isinstance(ret.exception, SystemExit)
+        else:
+            assert ret.exception is None
+
+
+def test_task_combination_validation():
+    tasks: List[str] = [
+        "",
+        "dummy",
+        "typo",
+        "typo,char",
+        "typo,char,seq2seq",
+        "typo,char,word",
+        "typo,char,seq2seq,word",
+        "char",
+        "char,seq2seq",
+        "char,word",
+        "char,seq2seq,word",
+        "seq2seq",
+        "seq2seq,word",
+        "word",
+    ]
+    valid_tasks_raw_input: Set[Tuple[str, ...]] = {
+        ("typo",),
+        ("typo", "char"),
+        ("typo", "char", "seq2seq"),
+        ("typo", "char", "word"),
+        ("typo", "char", "seq2seq", "word"),
+        ("char",),
+        ("char", "seq2seq"),
+        ("char", "word"),
+        ("char", "seq2seq", "word"),
+    }
+    valid_tasks_jumanpp_input: Set[Tuple[str, ...]] = valid_tasks_raw_input | {
+        ("seq2seq",),
+        ("seq2seq", "word"),
+        ("word",),
+    }
+    base_args: List[str] = ["--model-size", "tiny", "--text", ""]
+    for task in tasks:
+        ret = runner.invoke(app, args=[*base_args, "--task", task, "--input-format", "raw"])
+        if tuple(task.split(",")) not in valid_tasks_raw_input:
+            assert isinstance(ret.exception, SystemExit)
+        ret = runner.invoke(app, args=[*base_args, "--task", task, "--input-format", "jumanpp"])
+        if tuple(task.split(",")) not in valid_tasks_jumanpp_input:
+            assert isinstance(ret.exception, SystemExit)
+
+
+def test_input_format_validation():
+    input_formats: List[str] = ["", "raw", "jumanpp", "knp", "INVALID"]
+    base_args: List[str] = ["--model-size", "tiny", "--text", ""]
+    for input_format in input_formats:
+        ret = runner.invoke(app, args=[*base_args, "--input-format", input_format])
+        if input_format not in {"raw", "jumanpp", "knp"}:
+            assert isinstance(ret.exception, SystemExit)
+        else:
+            assert ret.exception is None
 
 
 def test_text_input():
     ret = runner.invoke(app, args=["--model-size", "tiny", "--text", "おはよう"])
     assert ret.exception is None
+    assert Document.from_knp(ret.stdout).text == "おはよう"
 
 
 @pytest.mark.parametrize(
-    "text, output",
+    ("text", "output"),
     [
         ("", "EOD\n"),
         # ("EOD", "EOD\nEOD\n"),  # TODO
@@ -104,44 +167,171 @@ def test_sanity():
         )
 
 
-def test_task_combination_validation():
-    tasks: List[str] = [
-        "",
-        "dummy",
-        "typo",
-        "typo,char",
-        "typo,char,seq2seq",
+@pytest.mark.parametrize(
+    "tasks",
+    [
+        "word",
+        "seq2seq",
+        "char,word",
+        "char,seq2seq",
+        "seq2seq,word",
         "typo,char,word",
+        "typo,char,seq2seq",
+        "char,seq2seq,word",
         "typo,char,seq2seq,word",
-        "char",
-        "char,seq2seq",
+    ],
+)
+def test_input_format_jumanpp(tasks: str):
+    jumanpp_text = textwrap.dedent(
+        """\
+        こんにちは こんにちは こんにちは 感動詞 12 * 0 * 0 * 0 "代表表記:こんにちは/こんにちは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        こんばんは こんばんは こんばんは 感動詞 12 * 0 * 0 * 0 "代表表記:今晩は/こんばんは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        """
+    )
+    ret = runner.invoke(
+        app, args=["--model-size", "tiny", "--tasks", tasks, "--text", jumanpp_text, "--input-format", "jumanpp"]
+    )
+    assert ret.exception is None
+    documents: List[Document] = []
+    for out_text in chunk_by_document(io.StringIO(ret.stdout)):
+        if tasks.split(",")[-1] == "word":
+            documents.append(Document.from_knp(out_text))
+        else:
+            documents.append(Document.from_jumanpp(out_text))
+    assert len(documents) == 1
+    document = documents[0]
+    doc_id = document.doc_id
+    assert doc_id != ""  # current datetime
+    sentences = document.sentences
+    for sentence in sentences:
+        assert sentence.sent_id.startswith(doc_id)
+        assert sentence.doc_id == doc_id
+    if "typo" not in tasks:
+        assert document.text == "こんにちは。こんばんは。"
+    if tasks.split(",")[0] in ("word", "seq2seq"):
+        # sentence boundaries are kept
+        assert len(sentences) == 2
+        assert sentences[0].text == "こんにちは。"
+        assert sentences[0].sent_id.startswith(doc_id)
+        assert sentences[1].text == "こんばんは。"
+        assert sentences[1].sent_id.startswith(doc_id)
+
+
+@pytest.mark.parametrize(
+    "tasks",
+    [
+        "word",
+        "seq2seq",
         "char,word",
+        "char,seq2seq",
+        "seq2seq,word",
+        "typo,char,word",
+        "typo,char,seq2seq",
         "char,seq2seq,word",
+        "typo,char,seq2seq,word",
+    ],
+)
+def test_input_format_jumanpp_with_sid(tasks: str):
+    jumanpp_text = textwrap.dedent(
+        """\
+        # S-ID:test-0 kwja:0.1.0
+        こんにちは こんにちは こんにちは 感動詞 12 * 0 * 0 * 0 "代表表記:こんにちは/こんにちは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        # S-ID:test-1 kwja:0.1.0
+        こんばんは こんばんは こんばんは 感動詞 12 * 0 * 0 * 0 "代表表記:今晩は/こんばんは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        """
+    )
+    ret = runner.invoke(
+        app, args=["--model-size", "tiny", "--tasks", tasks, "--text", jumanpp_text, "--input-format", "jumanpp"]
+    )
+    assert ret.exception is None
+    documents: List[Document] = []
+    for out_text in chunk_by_document(io.StringIO(ret.stdout)):
+        if tasks.split(",")[-1] == "word":
+            documents.append(Document.from_knp(out_text))
+        else:
+            documents.append(Document.from_jumanpp(out_text))
+    assert len(documents) == 1
+    document = documents[0]
+    doc_id = document.doc_id
+    assert doc_id == "test"
+    sentences = document.sentences
+    for sentence in sentences:
+        assert sentence.sent_id.startswith(doc_id)
+        assert sentence.doc_id == doc_id
+    if "typo" not in tasks:
+        assert document.text == "こんにちは。こんばんは。"
+    if tasks.split(",")[0] in ("word", "seq2seq"):
+        # sentence boundaries are kept
+        assert len(sentences) == 2
+        assert sentences[0].text == "こんにちは。"
+        assert sentences[0].sent_id == "test-0"
+        assert sentences[1].text == "こんばんは。"
+        assert sentences[1].sent_id == "test-1"
+
+
+@pytest.mark.parametrize(
+    "tasks",
+    [
+        "word",
         "seq2seq",
+        "char,word",
+        "char,seq2seq",
         "seq2seq,word",
-        "word",
-    ]
-    valid_tasks_raw_input: Set[Tuple[str, ...]] = {
-        ("typo",),
-        ("typo", "char"),
-        ("typo", "char", "seq2seq"),
-        ("typo", "char", "word"),
-        ("typo", "char", "seq2seq", "word"),
-        ("char",),
-        ("char", "seq2seq"),
-        ("char", "word"),
-        ("char", "seq2seq", "word"),
-    }
-    valid_tasks_jumanpp_input: Set[Tuple[str, ...]] = valid_tasks_raw_input | {
-        ("seq2seq",),
-        ("seq2seq", "word"),
-        ("word",),
-    }
-    base_args: List[str] = ["--model-size", "tiny", "--text", "おはよう"]
-    for task in tasks:
-        ret = runner.invoke(app, args=base_args + ["--task", task, "--input-format", "raw"])
-        if tuple(task.split(",")) not in valid_tasks_raw_input:
-            assert isinstance(ret.exception, SystemExit)
-        ret = runner.invoke(app, args=base_args + ["--task", task, "--input-format", "jumanpp"])
-        if tuple(task.split(",")) not in valid_tasks_jumanpp_input:
-            assert isinstance(ret.exception, SystemExit)
+        "typo,char,word",
+        "typo,char,seq2seq",
+        "char,seq2seq,word",
+        "typo,char,seq2seq,word",
+    ],
+)
+def test_input_format_knp(tasks: str):
+    knp_text = textwrap.dedent(
+        """\
+        # S-ID:test-0 kwja:0.1.0
+        * -1D
+        + -1D
+        こんにちは こんにちは こんにちは 感動詞 12 * 0 * 0 * 0 "代表表記:こんにちは/こんにちは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        # S-ID:test-1 kwja:0.1.0
+        * -1D
+        + -1D
+        こんばんは こんばんは こんばんは 感動詞 12 * 0 * 0 * 0 "代表表記:今晩は/こんばんは"
+        。 。 。 特殊 1 句点 1 * 0 * 0 "代表表記:。/。"
+        EOS
+        """
+    )
+    ret = runner.invoke(
+        app, args=["--model-size", "tiny", "--tasks", tasks, "--text", knp_text, "--input-format", "knp"]
+    )
+    assert ret.exception is None
+    documents: List[Document] = []
+    for out_text in chunk_by_document(io.StringIO(ret.stdout)):
+        if tasks.split(",")[-1] == "word":
+            documents.append(Document.from_knp(out_text))
+        else:
+            documents.append(Document.from_jumanpp(out_text))
+    assert len(documents) == 1
+    document = documents[0]
+    doc_id = document.doc_id
+    assert doc_id == "test"
+    sentences = document.sentences
+    for sentence in sentences:
+        assert sentence.sent_id.startswith(doc_id)
+        assert sentence.doc_id == doc_id
+    if "typo" not in tasks:
+        assert documents[0].text == "こんにちは。こんばんは。"
+    if tasks.split(",")[0] in ("word", "seq2seq"):
+        # sentence boundaries are kept
+        assert len(sentences) == 2
+        assert sentences[0].text == "こんにちは。"
+        assert sentences[0].sent_id == "test-0"
+        assert sentences[1].text == "こんばんは。"
+        assert sentences[1].sent_id == "test-1"
diff --git a/tests/conftest.py b/tests/conftest.py
index 6174beff..cfbd12fa 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -12,12 +12,12 @@
     base_path.symlink_to(base_path.parent / "base_template.yaml")
 
 
-@pytest.fixture
+@pytest.fixture()
 def data_dir() -> Path:
     return Path(__file__).parent / "data"
 
 
-@pytest.fixture
+@pytest.fixture()
 def typo_tokenizer() -> PreTrainedTokenizerBase:
     return AutoTokenizer.from_pretrained(
         "ku-nlp/deberta-v2-tiny-japanese-char-wwm",
@@ -26,7 +26,7 @@ def typo_tokenizer() -> PreTrainedTokenizerBase:
     )
 
 
-@pytest.fixture
+@pytest.fixture()
 def seq2seq_tokenizer() -> PreTrainedTokenizerBase:
     return AutoTokenizer.from_pretrained(
         "google/mt5-small",
@@ -34,42 +34,42 @@ def seq2seq_tokenizer() -> PreTrainedTokenizerBase:
     )
 
 
-@pytest.fixture
+@pytest.fixture()
 def char_tokenizer() -> PreTrainedTokenizerBase:
     return AutoTokenizer.from_pretrained("ku-nlp/deberta-v2-tiny-japanese-char-wwm", do_word_tokenize=False)
 
 
-@pytest.fixture
+@pytest.fixture()
 def word_tokenizer(special_tokens: List[str]) -> PreTrainedTokenizerBase:
     return AutoTokenizer.from_pretrained("ku-nlp/deberta-v2-tiny-japanese", additional_special_tokens=special_tokens)
 
 
-@pytest.fixture
+@pytest.fixture()
 def cohesion_tasks() -> List[str]:
     return ["pas_analysis", "bridging_reference_resolution", "coreference_resolution"]
 
 
-@pytest.fixture
+@pytest.fixture()
 def exophora_referents() -> List[str]:
     return ["著者", "読者", "不特定:人", "不特定:物"]
 
 
-@pytest.fixture
+@pytest.fixture()
 def pas_cases() -> List[str]:
     return ["ガ", "ヲ", "ニ", "ガ２"]
 
 
-@pytest.fixture
+@pytest.fixture()
 def br_cases() -> List[str]:
     return ["ノ"]
 
 
-@pytest.fixture
+@pytest.fixture()
 def special_tokens(exophora_referents: List[str]) -> List[str]:
     return [f"[{e}]" for e in exophora_referents] + ["[NULL]", "[NA]", "[ROOT]"]
 
 
-@pytest.fixture
+@pytest.fixture()
 def dataset_kwargs(
     cohesion_tasks: List[str],
     exophora_referents: List[str],
diff --git a/tests/datamodule/datasets/test_word_dataset.py b/tests/datamodule/datasets/test_word_dataset.py
index b6d041a5..fac5b160 100644
--- a/tests/datamodule/datasets/test_word_dataset.py
+++ b/tests/datamodule/datasets/test_word_dataset.py
@@ -23,7 +23,7 @@
 )
 
 
-@pytest.fixture
+@pytest.fixture()
 def split_into_words_word_tokenizer(special_tokens: List[str]) -> PreTrainedTokenizerBase:
     return AutoTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese", additional_special_tokens=special_tokens)
 
diff --git a/tests/modules/components/test_crf.py b/tests/modules/components/test_crf.py
index f76970ce..8b4800e1 100644
--- a/tests/modules/components/test_crf.py
+++ b/tests/modules/components/test_crf.py
@@ -29,7 +29,7 @@ def test_init() -> None:
 
 
 @pytest.mark.parametrize(
-    "batch_size, seq_length, reduction",
+    ("batch_size", "seq_length", "reduction"),
     [
         (2, 3, "token_mean"),
         (2, 3, "mean"),
@@ -54,7 +54,7 @@ def test_forward(batch_size: int, seq_length: int, reduction: str) -> None:
 
 
 @pytest.mark.parametrize(
-    "batch_size, seq_length, reduction",
+    ("batch_size", "seq_length", "reduction"),
     [
         (2, 3, "token_mean"),
         (2, 3, "mean"),
@@ -73,7 +73,7 @@ def test_loss_mask(batch_size: int, seq_length: int, reduction: str) -> None:
 
 
 @pytest.mark.parametrize(
-    "batch_size, seq_length, target_span",
+    ("batch_size", "seq_length", "target_span"),
     [
         (2, 3, (0, 3)),
         (2, 3, (1, 2)),
@@ -86,7 +86,7 @@ def test_viterbi_decode(batch_size: int, seq_length: int, target_span: Tuple[int
     crf.transitions.data = torch.zeros_like(crf.transitions)
     crf.end_transitions.data = torch.zeros_like(crf.end_transitions)
 
-    ne_index = [i for i, tag in enumerate(NE_TAGS) if tag.startswith("B-")][0]
+    ne_index = next(i for i, tag in enumerate(NE_TAGS) if tag.startswith("B-"))
     emissions = torch.zeros((batch_size, seq_length, crf.num_tags), dtype=torch.float)
     emissions[:, :, ne_index] = 1.0
     mask = torch.full((batch_size, seq_length), False, dtype=torch.bool)
diff --git a/tests/modules/components/test_head.py b/tests/modules/components/test_head.py
index c2e5bfa7..14850eb3 100644
--- a/tests/modules/components/test_head.py
+++ b/tests/modules/components/test_head.py
@@ -10,7 +10,7 @@
 
 
 @pytest.mark.parametrize(
-    "num_labels, hidden_size, hidden_dropout_prob",
+    ("num_labels", "hidden_size", "hidden_dropout_prob"),
     [
         (2, 3, 0.0),
         (10, 2, 0.1),
@@ -25,7 +25,7 @@ def test_sequential_labeling_head(num_labels: int, hidden_size: int, hidden_drop
 
 
 @pytest.mark.parametrize(
-    "num_labels, hidden_size, hidden_dropout_prob, rank",
+    ("num_labels", "hidden_size", "hidden_dropout_prob", "rank"),
     [
         (2, 3, 0.0, 4),
         (10, 2, 0.1, 2),
@@ -42,7 +42,7 @@ def test_lora_sequential_multi_labeling_head(
 
 
 @pytest.mark.parametrize(
-    "num_labels, hidden_size, hidden_dropout_prob",
+    ("num_labels", "hidden_size", "hidden_dropout_prob"),
     [
         (5, 3, 0.0),
         (1, 2, 0.1),
@@ -57,7 +57,7 @@ def test_word_selection_head(num_labels: int, hidden_size: int, hidden_dropout_p
 
 
 @pytest.mark.parametrize(
-    "num_labels, hidden_size, hidden_dropout_prob",
+    ("num_labels", "hidden_size", "hidden_dropout_prob"),
     [
         (5, 3, 0.0),
         (1, 2, 0.1),
diff --git a/tests/modules/components/test_logits_processor.py b/tests/modules/components/test_logits_processor.py
index 2a5c4edf..2218915e 100644
--- a/tests/modules/components/test_logits_processor.py
+++ b/tests/modules/components/test_logits_processor.py
@@ -90,7 +90,7 @@ def test_get_target_morpheme(data_dir: Path) -> None:
         test_case_path: Path = data_dir / "modules" / "permitted_tokens.json"
         with open(test_case_path) as f:
             test_cases = json.load(f)
-        for test_id, test_case in test_cases.items():
+        for test_case in test_cases.values():
             processor = ForcedLogitsProcessor(
                 surfs=[test_case["surfs"]],
                 num_beams=1,
@@ -107,7 +107,7 @@ def test_get_target_morpheme(data_dir: Path) -> None:
 
 
 @pytest.mark.parametrize(
-    "input_tokens, surfs, expected_remaining_surf",
+    ("input_tokens", "surfs", "expected_remaining_surf"),
     [
         (["<pad>", "<extra_id_0>"], ["研究", "する"], "研究"),
         (["<pad>", "<extra_id_0>", "研"], ["研究", "する"], "究"),
@@ -172,7 +172,7 @@ def test_get_remaining_surf(input_tokens: List[str], surfs: List[str], expected_
 
 
 @pytest.mark.parametrize(
-    "surfs, permitted_tokens",
+    ("surfs", "permitted_tokens"),
     [
         (["研究", "を", "する"], ["研究", "研"]),
         ([FULL_SPACE_TOKEN, "研究", "を", "する"], [FULL_SPACE_TOKEN]),
@@ -226,7 +226,7 @@ def test_get_generated_surf(data_dir: Path) -> None:
                     char2tokens=char2tokens,
                 )
                 tgt_tokens: List[str] = formatter.get_tgt_tokens(sentence)
-                tgt_input_ids: List[int] = tokenizer.convert_tokens_to_ids(tgt_tokens) + [tokenizer.eos_token_id]
+                tgt_input_ids: List[int] = [*tokenizer.convert_tokens_to_ids(tgt_tokens), tokenizer.eos_token_id]
                 assert processor.surfs[0] == processor._get_generated_surf(tgt_input_ids)
 
 
@@ -249,7 +249,7 @@ def test_get_mask(data_dir: Path) -> None:
         test_case_path: Path = data_dir / "modules" / "permitted_tokens.json"
         with open(test_case_path) as f:
             test_cases = json.load(f)
-        for test_id, test_case in test_cases.items():
+        for test_case in test_cases.values():
             assert test_case["target_morpheme"] in ["surf", "reading", "lemma", "canon", "init"]
             processor = ForcedLogitsProcessor(
                 surfs=[test_case["surfs"]],
diff --git a/tests/modules/components/test_pooling.py b/tests/modules/components/test_pooling.py
index c5125931..ff81bf92 100644
--- a/tests/modules/components/test_pooling.py
+++ b/tests/modules/components/test_pooling.py
@@ -130,5 +130,5 @@ def test_average_pooling():
 
 
 def test_error():
-    with pytest.raises(ValueError):
-        _ = pool_subwords(sequence_output, subword_map, None)  # type: ignore
+    with pytest.raises(ValueError, match="Unknown pooling strategy: INVALID"):
+        _ = pool_subwords(sequence_output, subword_map, "INVALID")  # type: ignore
diff --git a/tests/modules/functions/test_loss.py b/tests/modules/functions/test_loss.py
index cba9ed2f..92845038 100644
--- a/tests/modules/functions/test_loss.py
+++ b/tests/modules/functions/test_loss.py
@@ -6,7 +6,7 @@
 
 
 @pytest.mark.parametrize(
-    "input_, target, expected",
+    ("input_", "target", "expected"),
     [
         (
             torch.tensor([[1.0, 0.0]], dtype=torch.float),  # (1, 2)
@@ -20,7 +20,7 @@ def test_compute_token_mean_loss(input_: torch.Tensor, target: torch.Tensor, exp
 
 
 @pytest.mark.parametrize(
-    "input_, target, expected",
+    ("input_", "target", "expected"),
     [
         (
             torch.tensor([[[0.5, 0.5], [1.0, 0.5]]], dtype=torch.float),  # (1, 2, 2)
@@ -38,7 +38,7 @@ def test_compute_multi_label_token_mean_loss(
 
 
 @pytest.mark.parametrize(
-    "logits, mask, expected",
+    ("logits", "mask", "expected"),
     [
         (
             torch.tensor([1.0, 1.0, 1.0], dtype=torch.float),  # (3,)
diff --git a/tests/modules/test_base_module.py b/tests/modules/test_base_module.py
index 9383e515..7444c9b1 100644
--- a/tests/modules/test_base_module.py
+++ b/tests/modules/test_base_module.py
@@ -5,7 +5,7 @@
 
 
 @pytest.mark.parametrize(
-    "item, keys_to_ignore, expected",
+    ("item", "keys_to_ignore", "expected"),
     [
         (
             DictConfig({"key_0": "value_0", "key_1": "value_1"}),
diff --git a/tests/utils/test_reading_prediction.py b/tests/utils/test_reading_prediction.py
index db175afc..c6eadd63 100644
--- a/tests/utils/test_reading_prediction.py
+++ b/tests/utils/test_reading_prediction.py
@@ -9,7 +9,7 @@
 
 
 @pytest.mark.parametrize(
-    "readings, tokens, subword_map, expected_output",
+    ("readings", "tokens", "subword_map", "expected_output"),
     [
         (
             ["[UNK]", "せい", "じょう", "[ID]", "にゅうりょく"],
diff --git a/tests/utils/test_seq2seq_format.py b/tests/utils/test_seq2seq_format.py
index de309612..f90851a0 100644
--- a/tests/utils/test_seq2seq_format.py
+++ b/tests/utils/test_seq2seq_format.py
@@ -149,7 +149,7 @@ def test_get_src_tokens(data_dir: Path, seq2seq_tokenizer: PreTrainedTokenizerFa
             sent = Sentence.from_jumanpp(f.read())
             expected_src_tokens: List[str] = []
             for morphemes in src_tokens[idx]:
-                expected_src_tokens.extend(morphemes.split(" ") + [MORPHEME_SPLIT_TOKEN])
+                expected_src_tokens.extend([*morphemes.split(" "), MORPHEME_SPLIT_TOKEN])
             assert [
                 x[1:] if x.startswith("▁") else x for x in seq2seq_formatter.get_src_tokens(sent)
             ] == expected_src_tokens[:-1]
diff --git a/tests/utils/test_sub_document.py b/tests/utils/test_sub_document.py
index 70cdc10b..77f4ddc4 100644
--- a/tests/utils/test_sub_document.py
+++ b/tests/utils/test_sub_document.py
@@ -94,7 +94,7 @@ def test_split_conditions_auto_stride(case: Dict[str, Any]):
     splitter = SequenceSplitter(sequence_lengths, max_length, stride=-1)
     sequence_ids = list(range(len(sequence_lengths)))
     concatenated_ids = []
-    for idx, item in enumerate(splitter.split_into_spans(return_candidates=True)):
+    for item in splitter.split_into_spans(return_candidates=True):
         assert isinstance(item, tuple)
         span: SpanCandidate
         candidates: List[SpanCandidate]
diff --git a/tests/utils/test_word_normalization.py b/tests/utils/test_word_normalization.py
index 1990a244..8ce07a46 100644
--- a/tests/utils/test_word_normalization.py
+++ b/tests/utils/test_word_normalization.py
@@ -71,12 +71,12 @@
 ]
 
 
-@pytest.mark.parametrize("surf,ops,expected", wellformed_list)
+@pytest.mark.parametrize(("surf", "ops", "expected"), wellformed_list)
 def test_gen_normalized_surf(surf, ops, expected):
     assert get_normalized(surf, ops, strict=True) == expected
 
 
-@pytest.mark.parametrize("surf,expected,normalized", wellformed_list)
+@pytest.mark.parametrize(("surf", "expected", "normalized"), wellformed_list)
 def test_get_normalization_opns(surf, expected, normalized):
     word_norm_op_tags = get_word_norm_op_tags(surf, normalized)
     assert len(word_norm_op_tags) == len(expected)
@@ -90,13 +90,13 @@ def test_get_normalization_opns(surf, expected, normalized):
 ]
 
 
-@pytest.mark.parametrize("surf,ops,expected", malformed_list)
+@pytest.mark.parametrize(("surf", "ops", "expected"), malformed_list)
 def test_gen_normalized_surf_malformed(surf, ops, expected):
     with pytest.raises(ValueError):
         get_normalized(surf, ops, strict=True)
 
 
-@pytest.mark.parametrize("surf,ops,expected", malformed_list)
+@pytest.mark.parametrize(("surf", "ops", "expected"), malformed_list)
 def test_gen_normalized_surf_malformed_loose(surf, ops, expected):
     assert get_normalized(surf, ops, strict=False) == expected
 
@@ -112,7 +112,7 @@ def test_morpheme_normalizer():
 
 
 @pytest.mark.parametrize(
-    "surf,expected",
+    ("surf", "expected"),
     [
         ("なあ", "なぁ"),
         ("さあ", "さぁ"),