diff --git a/.gitignore b/.gitignore
index 995bb6b..e037d8f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -161,6 +161,8 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 
+.jj
+scratchpad.ipynb
 datasets/
 lightning_logs/
 logs/
diff --git a/poetry.lock b/poetry.lock
index 0126971..bde4d1c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
+[[package]]
+name = "about-time"
+version = "4.2.1"
+description = "Easily measure timing and throughput of code blocks, with beautiful human friendly representations."
+optional = false
+python-versions = ">=3.7, <4"
+files = [
+    {file = "about-time-4.2.1.tar.gz", hash = "sha256:6a538862d33ce67d997429d14998310e1dbfda6cb7d9bbfbf799c4709847fece"},
+    {file = "about_time-4.2.1-py3-none-any.whl", hash = "sha256:8bbf4c75fe13cbd3d72f49a03b02c5c7dca32169b6d49117c257e7eb3eaee341"},
+]
+
 [[package]]
 name = "absl-py"
 version = "2.1.0"
@@ -151,6 +162,21 @@ typing-extensions = ">=4"
 [package.extras]
 tz = ["backports.zoneinfo"]
 
+[[package]]
+name = "alive-progress"
+version = "3.1.5"
+description = "A new kind of Progress Bar, with real-time throughput, ETA, and very cool animations!"
+optional = false
+python-versions = ">=3.7, <4"
+files = [
+    {file = "alive-progress-3.1.5.tar.gz", hash = "sha256:42e399a66c8150dc507602dff7b7953f105ef11faf97ddaa6d27b1cbf45c4c98"},
+    {file = "alive_progress-3.1.5-py3-none-any.whl", hash = "sha256:347220c1858e3abe137fa0746895668c04df09c5261a13dc03f05795e8a29be5"},
+]
+
+[package.dependencies]
+about-time = "4.2.1"
+grapheme = "0.6.0"
+
 [[package]]
 name = "ansicon"
 version = "1.89.0"
@@ -162,6 +188,26 @@ files = [
     {file = "ansicon-1.89.0.tar.gz", hash = "sha256:e4d039def5768a47e4afec8e89e83ec3ae5a26bf00ad851f914d1240b444d2b1"},
 ]
 
+[[package]]
+name = "anyio"
+version = "4.3.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
+    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
+]
+
+[package.dependencies]
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
+
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -173,6 +219,82 @@ files = [
     {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
 ]
 
+[[package]]
+name = "argon2-cffi"
+version = "23.1.0"
+description = "Argon2 for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"},
+    {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"},
+]
+
+[package.dependencies]
+argon2-cffi-bindings = "*"
+
+[package.extras]
+dev = ["argon2-cffi[tests,typing]", "tox (>4)"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"]
+tests = ["hypothesis", "pytest"]
+typing = ["mypy"]
+
+[[package]]
+name = "argon2-cffi-bindings"
+version = "21.2.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9524464572e12979364b7d600abf96181d3541da11e23ddf565a32e70bd4dc0d"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b746dba803a79238e925d9046a63aa26bf86ab2a2fe74ce6b009a1c3f5c8f2ae"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58ed19212051f49a523abb1dbe954337dc82d947fb6e5a0da60f7c8471a8476c"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:bd46088725ef7f58b5a1ef7ca06647ebaf0eb4baff7d1d0d177c6cc8744abd86"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_i686.whl", hash = "sha256:8cd69c07dd875537a824deec19f978e0f2078fdda07fd5c42ac29668dda5f40f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:f1152ac548bd5b8bcecfb0b0371f082037e47128653df2e8ba6e914d384f3c3e"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win32.whl", hash = "sha256:603ca0aba86b1349b147cab91ae970c63118a0f30444d4bc80355937c950c082"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl", hash = "sha256:b2ef1c30440dbbcba7a5dc3e319408b59676e2e039e2ae11a8775ecf482b192f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e415e3f62c8d124ee16018e491a009937f8cf7ebf5eb430ffc5de21b900dad93"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3e385d1c39c520c08b53d63300c3ecc28622f076f4c2b0e6d7e796e9f6502194"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2c3e3cc67fdb7d82c4718f19b4e7a87123caf8a93fde7e23cf66ac0337d3cb3f"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6a22ad9800121b71099d0fb0a65323810a15f2e292f2ba450810a7316e128ee5"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f9f8b450ed0547e3d473fdc8612083fd08dd2120d6ac8f73828df9b7d45bb351"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:93f9bf70084f97245ba10ee36575f0c3f1e7d7724d67d8e5b08e61787c320ed7"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3b9ef65804859d335dc6b31582cad2c5166f0c3e7975f324d9ffaa34ee7e6583"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d4966ef5848d820776f5f562a7d45fdd70c2f330c961d0d745b784034bd9f48d"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20ef543a89dee4db46a1a6e206cd015360e5a75822f76df533845c3cbaf72670"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed2937d286e2ad0cc79a7087d3c272832865f779430e0cc2b4f3718d3159b0cb"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:5e00316dabdaea0b2dd82d141cc66889ced0cdcbfa599e8b471cf22c620c329a"},
+]
+
+[package.dependencies]
+cffi = ">=1.0.1"
+
+[package.extras]
+dev = ["cogapp", "pre-commit", "pytest", "wheel"]
+tests = ["pytest"]
+
+[[package]]
+name = "arrow"
+version = "1.3.0"
+description = "Better dates & times for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"},
+    {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"},
+]
+
+[package.dependencies]
+python-dateutil = ">=2.7.0"
+types-python-dateutil = ">=2.8.10"
+
+[package.extras]
+doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
+
 [[package]]
 name = "asttokens"
 version = "2.4.1"
@@ -191,6 +313,17 @@ six = ">=1.12.0"
 astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
 test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 
+[[package]]
+name = "async-lru"
+version = "2.0.4"
+description = "Simple LRU cache for asyncio"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "async-lru-2.0.4.tar.gz", hash = "sha256:b8a59a5df60805ff63220b2a0c5b5393da5521b113cd5465a44eb037d81a5627"},
+    {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"},
+]
+
 [[package]]
 name = "attrs"
 version = "23.2.0"
@@ -210,6 +343,20 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 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 = "babel"
+version = "2.15.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "Babel-2.15.0-py3-none-any.whl", hash = "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb"},
+    {file = "babel-2.15.0.tar.gz", hash = "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413"},
+]
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.12.3"
@@ -231,6 +378,24 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "bleach"
+version = "6.1.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "bleach-6.1.0-py3-none-any.whl", hash = "sha256:3225f354cfc436b9789c66c4ee030194bee0568fbf9cbdad3bc8b5c26c5f12b6"},
+    {file = "bleach-6.1.0.tar.gz", hash = "sha256:0a31f1837963c41d46bbf1331b8778e1308ea0791db03cc4e7357b97cf42a8fe"},
+]
+
+[package.dependencies]
+six = ">=1.9.0"
+webencodings = "*"
+
+[package.extras]
+css = ["tinycss2 (>=1.1.0,<1.3)"]
+
 [[package]]
 name = "blessed"
 version = "1.20.0"
@@ -643,6 +808,21 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.6"
+description = "Easily serialize dataclasses to and from JSON."
+optional = false
+python-versions = "<4.0,>=3.7"
+files = [
+    {file = "dataclasses_json-0.6.6-py3-none-any.whl", hash = "sha256:e54c5c87497741ad454070ba0ed411523d46beb5da102e221efb873801b0ba85"},
+    {file = "dataclasses_json-0.6.6.tar.gz", hash = "sha256:0c09827d26fffda27f1be2fed7a7a01a29c5ddcd2eb6393ad5ebf9d77e9deae8"},
+]
+
+[package.dependencies]
+marshmallow = ">=3.18.0,<4.0.0"
+typing-inspect = ">=0.4.0,<1"
+
 [[package]]
 name = "debugpy"
 version = "1.8.1"
@@ -685,6 +865,17 @@ files = [
     {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
 ]
 
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+description = "XML bomb protection for Python stdlib modules"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
+    {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"},
+]
+
 [[package]]
 name = "docker-pycreds"
 version = "0.4.0"
@@ -861,6 +1052,17 @@ ufo = ["fs (>=2.2.0,<3)"]
 unicode = ["unicodedata2 (>=15.1.0)"]
 woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
+[[package]]
+name = "fqdn"
+version = "1.5.1"
+description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers"
+optional = false
+python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
+files = [
+    {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"},
+    {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
+]
+
 [[package]]
 name = "frozenlist"
 version = "1.4.1"
@@ -1037,6 +1239,19 @@ gitdb = ">=4.0.1,<5"
 doc = ["sphinx (==4.3.2)", "sphinx-autodoc-typehints", "sphinx-rtd-theme", "sphinxcontrib-applehelp (>=1.0.2,<=1.0.4)", "sphinxcontrib-devhelp (==1.0.2)", "sphinxcontrib-htmlhelp (>=2.0.0,<=2.0.1)", "sphinxcontrib-qthelp (==1.0.3)", "sphinxcontrib-serializinghtml (==1.1.5)"]
 test = ["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", "typing-extensions"]
 
+[[package]]
+name = "grapheme"
+version = "0.6.0"
+description = "Unicode grapheme helpers"
+optional = false
+python-versions = "*"
+files = [
+    {file = "grapheme-0.6.0.tar.gz", hash = "sha256:44c2b9f21bbe77cfb05835fec230bd435954275267fea1858013b102f8603cca"},
+]
+
+[package.extras]
+test = ["pytest", "sphinx", "sphinx-autobuild", "twine", "wheel"]
+
 [[package]]
 name = "greenlet"
 version = "3.0.3"
@@ -1166,6 +1381,62 @@ files = [
 [package.extras]
 protobuf = ["grpcio-tools (>=1.63.0)"]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
+[[package]]
+name = "httpx"
+version = "0.27.0"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"},
+    {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
 [[package]]
 name = "idna"
 version = "3.7"
@@ -1272,6 +1543,41 @@ qtconsole = ["qtconsole"]
 test = ["pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"]
 test-extra = ["curio", "ipython[test]", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"]
 
+[[package]]
+name = "ipywidgets"
+version = "8.1.2"
+description = "Jupyter interactive widgets"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "ipywidgets-8.1.2-py3-none-any.whl", hash = "sha256:bbe43850d79fb5e906b14801d6c01402857996864d1e5b6fa62dd2ee35559f60"},
+    {file = "ipywidgets-8.1.2.tar.gz", hash = "sha256:d0b9b41e49bae926a866e613a39b0f0097745d2b9f1f3dd406641b4a57ec42c9"},
+]
+
+[package.dependencies]
+comm = ">=0.1.3"
+ipython = ">=6.1.0"
+jupyterlab-widgets = ">=3.0.10,<3.1.0"
+traitlets = ">=4.3.1"
+widgetsnbextension = ">=4.0.10,<4.1.0"
+
+[package.extras]
+test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
+
+[[package]]
+name = "isoduration"
+version = "20.11.0"
+description = "Operations with ISO 8601 durations"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"},
+    {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"},
+]
+
+[package.dependencies]
+arrow = ">=0.15.0"
+
 [[package]]
 name = "jedi"
 version = "0.19.1"
@@ -1322,6 +1628,28 @@ files = [
 [package.dependencies]
 ansicon = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "json5"
+version = "0.9.25"
+description = "A Python implementation of the JSON5 data format."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"},
+    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
+]
+
+[[package]]
+name = "jsonpointer"
+version = "2.4"
+description = "Identify specific nodes in a JSON document (RFC 6901)"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
+files = [
+    {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
+    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.22.0"
@@ -1335,9 +1663,17 @@ files = [
 
 [package.dependencies]
 attrs = ">=22.2.0"
+fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""}
 jsonschema-specifications = ">=2023.03.6"
 referencing = ">=0.28.4"
+rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
 rpds-py = ">=0.7.1"
+uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -1357,6 +1693,26 @@ files = [
 [package.dependencies]
 referencing = ">=0.31.0"
 
+[[package]]
+name = "jupyter"
+version = "1.0.0"
+description = "Jupyter metapackage. Install all the Jupyter components in one go."
+optional = false
+python-versions = "*"
+files = [
+    {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"},
+    {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"},
+    {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"},
+]
+
+[package.dependencies]
+ipykernel = "*"
+ipywidgets = "*"
+jupyter-console = "*"
+nbconvert = "*"
+notebook = "*"
+qtconsole = "*"
+
 [[package]]
 name = "jupyter-client"
 version = "8.6.1"
@@ -1379,6 +1735,30 @@ traitlets = ">=5.3"
 docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
 test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
 
+[[package]]
+name = "jupyter-console"
+version = "6.6.3"
+description = "Jupyter terminal console"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jupyter_console-6.6.3-py3-none-any.whl", hash = "sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485"},
+    {file = "jupyter_console-6.6.3.tar.gz", hash = "sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539"},
+]
+
+[package.dependencies]
+ipykernel = ">=6.14"
+ipython = "*"
+jupyter-client = ">=7.0.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+prompt-toolkit = ">=3.0.30"
+pygments = "*"
+pyzmq = ">=17"
+traitlets = ">=5.4"
+
+[package.extras]
+test = ["flaky", "pexpect", "pytest"]
+
 [[package]]
 name = "jupyter-core"
 version = "5.7.2"
@@ -1399,6 +1779,179 @@ traitlets = ">=5.3"
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
 test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"]
 
+[[package]]
+name = "jupyter-events"
+version = "0.10.0"
+description = "Jupyter Event System library"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_events-0.10.0-py3-none-any.whl", hash = "sha256:4b72130875e59d57716d327ea70d3ebc3af1944d3717e5a498b8a06c6c159960"},
+    {file = "jupyter_events-0.10.0.tar.gz", hash = "sha256:670b8229d3cc882ec782144ed22e0d29e1c2d639263f92ca8383e66682845e22"},
+]
+
+[package.dependencies]
+jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]}
+python-json-logger = ">=2.0.4"
+pyyaml = ">=5.3"
+referencing = "*"
+rfc3339-validator = "*"
+rfc3986-validator = ">=0.1.1"
+traitlets = ">=5.3"
+
+[package.extras]
+cli = ["click", "rich"]
+docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontrib-spelling"]
+test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "rich"]
+
+[[package]]
+name = "jupyter-lsp"
+version = "2.2.5"
+description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter-lsp-2.2.5.tar.gz", hash = "sha256:793147a05ad446f809fd53ef1cd19a9f5256fd0a2d6b7ce943a982cb4f545001"},
+    {file = "jupyter_lsp-2.2.5-py3-none-any.whl", hash = "sha256:45fbddbd505f3fbfb0b6cb2f1bc5e15e83ab7c79cd6e89416b248cb3c00c11da"},
+]
+
+[package.dependencies]
+jupyter-server = ">=1.1.2"
+
+[[package]]
+name = "jupyter-server"
+version = "2.14.0"
+description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server-2.14.0-py3-none-any.whl", hash = "sha256:fb6be52c713e80e004fac34b35a0990d6d36ba06fd0a2b2ed82b899143a64210"},
+    {file = "jupyter_server-2.14.0.tar.gz", hash = "sha256:659154cea512083434fd7c93b7fe0897af7a2fd0b9dd4749282b42eaac4ae677"},
+]
+
+[package.dependencies]
+anyio = ">=3.1.0"
+argon2-cffi = ">=21.1"
+jinja2 = ">=3.0.3"
+jupyter-client = ">=7.4.4"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+jupyter-events = ">=0.9.0"
+jupyter-server-terminals = ">=0.4.4"
+nbconvert = ">=6.4.4"
+nbformat = ">=5.3.0"
+overrides = ">=5.0"
+packaging = ">=22.0"
+prometheus-client = ">=0.9"
+pywinpty = {version = ">=2.0.1", markers = "os_name == \"nt\""}
+pyzmq = ">=24"
+send2trash = ">=1.8.2"
+terminado = ">=0.8.3"
+tornado = ">=6.2.0"
+traitlets = ">=5.6.0"
+websocket-client = ">=1.7"
+
+[package.extras]
+docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0,<9)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
+
+[[package]]
+name = "jupyter-server-terminals"
+version = "0.5.3"
+description = "A Jupyter Server Extension Providing Terminals."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server_terminals-0.5.3-py3-none-any.whl", hash = "sha256:41ee0d7dc0ebf2809c668e0fc726dfaf258fcd3e769568996ca731b6194ae9aa"},
+    {file = "jupyter_server_terminals-0.5.3.tar.gz", hash = "sha256:5ae0295167220e9ace0edcfdb212afd2b01ee8d179fe6f23c899590e9b8a5269"},
+]
+
+[package.dependencies]
+pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""}
+terminado = ">=0.8.3"
+
+[package.extras]
+docs = ["jinja2", "jupyter-server", "mistune (<4.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
+test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
+
+[[package]]
+name = "jupyterlab"
+version = "4.2.1"
+description = "JupyterLab computational environment"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab-4.2.1-py3-none-any.whl", hash = "sha256:6ac6e3827b3c890e6e549800e8a4f4aaea6a69321e2240007902aa7a0c56a8e4"},
+    {file = "jupyterlab-4.2.1.tar.gz", hash = "sha256:a10fb71085a6900820c62d43324005046402ffc8f0fde696103e37238a839507"},
+]
+
+[package.dependencies]
+async-lru = ">=1.0.0"
+httpx = ">=0.25.0"
+ipykernel = ">=6.5.0"
+jinja2 = ">=3.0.3"
+jupyter-core = "*"
+jupyter-lsp = ">=2.0.0"
+jupyter-server = ">=2.4.0,<3"
+jupyterlab-server = ">=2.27.1,<3"
+notebook-shim = ">=0.2"
+packaging = "*"
+tornado = ">=6.2.0"
+traitlets = "*"
+
+[package.extras]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
+test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
+upgrade-extension = ["copier (>=8,<10)", "jinja2-time (<0.3)", "pydantic (<2.0)", "pyyaml-include (<2.0)", "tomli-w (<2.0)"]
+
+[[package]]
+name = "jupyterlab-pygments"
+version = "0.3.0"
+description = "Pygments theme using JupyterLab CSS variables"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780"},
+    {file = "jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d"},
+]
+
+[[package]]
+name = "jupyterlab-server"
+version = "2.27.2"
+description = "A set of server components for JupyterLab and JupyterLab like applications."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jupyterlab_server-2.27.2-py3-none-any.whl", hash = "sha256:54aa2d64fd86383b5438d9f0c032f043c4d8c0264b8af9f60bd061157466ea43"},
+    {file = "jupyterlab_server-2.27.2.tar.gz", hash = "sha256:15cbb349dc45e954e09bacf81b9f9bcb10815ff660fb2034ecd7417db3a7ea27"},
+]
+
+[package.dependencies]
+babel = ">=2.10"
+jinja2 = ">=3.0.3"
+json5 = ">=0.9.0"
+jsonschema = ">=4.18.0"
+jupyter-server = ">=1.21,<3"
+packaging = ">=21.3"
+requests = ">=2.31"
+
+[package.extras]
+docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi (>0.8)"]
+openapi = ["openapi-core (>=0.18.0,<0.19.0)", "ruamel-yaml"]
+test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0,<8)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
+
+[[package]]
+name = "jupyterlab-widgets"
+version = "3.0.10"
+description = "Jupyter interactive widgets for JupyterLab"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jupyterlab_widgets-3.0.10-py3-none-any.whl", hash = "sha256:dd61f3ae7a5a7f80299e14585ce6cf3d6925a96c9103c978eda293197730cb64"},
+    {file = "jupyterlab_widgets-3.0.10.tar.gz", hash = "sha256:04f2ac04976727e4f9d0fa91cdc2f1ab860f965e504c29dbd6a65c882c9d04c0"},
+]
+
 [[package]]
 name = "jupytext"
 version = "1.16.2"
@@ -1427,6 +1980,26 @@ test-functional = ["pytest", "pytest-randomly", "pytest-xdist"]
 test-integration = ["ipykernel", "jupyter-server (!=2.11)", "nbconvert", "pytest", "pytest-randomly", "pytest-xdist"]
 test-ui = ["calysto-bash"]
 
+[[package]]
+name = "kaggle"
+version = "1.6.14"
+description = "Kaggle API"
+optional = false
+python-versions = "*"
+files = [
+    {file = "kaggle-1.6.14.tar.gz", hash = "sha256:583532bdeca3c9e0cafc4931112c6737b5e68f187ab59ee77dffdf09fdf9dbd9"},
+]
+
+[package.dependencies]
+bleach = "*"
+certifi = ">=2023.7.22"
+python-dateutil = "*"
+python-slugify = "*"
+requests = "*"
+six = ">=1.10"
+tqdm = "*"
+urllib3 = "*"
+
 [[package]]
 name = "kiwisolver"
 version = "1.4.5"
@@ -1762,6 +2335,25 @@ files = [
     {file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
 ]
 
+[[package]]
+name = "marshmallow"
+version = "3.21.2"
+description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "marshmallow-3.21.2-py3-none-any.whl", hash = "sha256:70b54a6282f4704d12c0a41599682c5c5450e843b9ec406308653b47c59648a1"},
+    {file = "marshmallow-3.21.2.tar.gz", hash = "sha256:82408deadd8b33d56338d2182d455db632c6313aa2af61916672146bb32edc56"},
+]
+
+[package.dependencies]
+packaging = ">=17.0"
+
+[package.extras]
+dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
+docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.3.7)", "sphinx-issues (==4.1.0)", "sphinx-version-warning (==1.1.2)"]
+tests = ["pytest", "pytz", "simplejson"]
+
 [[package]]
 name = "matplotlib"
 version = "3.8.4"
@@ -1868,6 +2460,17 @@ files = [
     {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
 ]
 
+[[package]]
+name = "mistune"
+version = "3.0.2"
+description = "A sane and fast Markdown parser with useful plugins and renderers"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mistune-3.0.2-py3-none-any.whl", hash = "sha256:71481854c30fdbc938963d3605b72501f5c10a9320ecd412c121c163a1c7d205"},
+    {file = "mistune-3.0.2.tar.gz", hash = "sha256:fc7f93ded930c92394ef2cb6f04a8aabab4117a91449e72dcc8dfa646a508be8"},
+]
+
 [[package]]
 name = "mkl"
 version = "2021.4.0"
@@ -2002,6 +2605,76 @@ files = [
     {file = "multidict-6.0.5.tar.gz", hash = "sha256:f7e301075edaf50500f0b341543c41194d8df3ae5caf4702f2095f3ca73dd8da"},
 ]
 
+[[package]]
+name = "mypy-extensions"
+version = "1.0.0"
+description = "Type system extensions for programs checked with the mypy type checker."
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d"},
+    {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"},
+]
+
+[[package]]
+name = "nbclient"
+version = "0.10.0"
+description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "nbclient-0.10.0-py3-none-any.whl", hash = "sha256:f13e3529332a1f1f81d82a53210322476a168bb7090a0289c795fe9cc11c9d3f"},
+    {file = "nbclient-0.10.0.tar.gz", hash = "sha256:4b3f1b7dba531e498449c4db4f53da339c91d449dc11e9af3a43b4eb5c5abb09"},
+]
+
+[package.dependencies]
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+nbformat = ">=5.1"
+traitlets = ">=5.4"
+
+[package.extras]
+dev = ["pre-commit"]
+docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
+test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
+
+[[package]]
+name = "nbconvert"
+version = "7.16.4"
+description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "nbconvert-7.16.4-py3-none-any.whl", hash = "sha256:05873c620fe520b6322bf8a5ad562692343fe3452abda5765c7a34b7d1aa3eb3"},
+    {file = "nbconvert-7.16.4.tar.gz", hash = "sha256:86ca91ba266b0a448dc96fa6c5b9d98affabde2867b363258703536807f9f7f4"},
+]
+
+[package.dependencies]
+beautifulsoup4 = "*"
+bleach = "!=5.0.0"
+defusedxml = "*"
+jinja2 = ">=3.0"
+jupyter-core = ">=4.7"
+jupyterlab-pygments = "*"
+markupsafe = ">=2.0"
+mistune = ">=2.0.3,<4"
+nbclient = ">=0.5.0"
+nbformat = ">=5.7"
+packaging = "*"
+pandocfilters = ">=1.4.1"
+pygments = ">=2.4.1"
+tinycss2 = "*"
+traitlets = ">=5.1"
+
+[package.extras]
+all = ["flaky", "ipykernel", "ipython", "ipywidgets (>=7.5)", "myst-parser", "nbsphinx (>=0.2.12)", "playwright", "pydata-sphinx-theme", "pyqtwebengine (>=5.15)", "pytest (>=7)", "sphinx (==5.0.2)", "sphinxcontrib-spelling", "tornado (>=6.1)"]
+docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sphinx-theme", "sphinx (==5.0.2)", "sphinxcontrib-spelling"]
+qtpdf = ["pyqtwebengine (>=5.15)"]
+qtpng = ["pyqtwebengine (>=5.15)"]
+serve = ["tornado (>=6.1)"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
+webpdf = ["playwright"]
+
 [[package]]
 name = "nbformat"
 version = "5.10.4"
@@ -2052,6 +2725,46 @@ doc = ["myst-nb (>=1.0)", "numpydoc (>=1.7)", "pillow (>=9.4)", "pydata-sphinx-t
 extra = ["lxml (>=4.6)", "pydot (>=2.0)", "pygraphviz (>=1.12)", "sympy (>=1.10)"]
 test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
+[[package]]
+name = "notebook"
+version = "7.2.0"
+description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "notebook-7.2.0-py3-none-any.whl", hash = "sha256:b4752d7407d6c8872fc505df0f00d3cae46e8efb033b822adacbaa3f1f3ce8f5"},
+    {file = "notebook-7.2.0.tar.gz", hash = "sha256:34a2ba4b08ad5d19ec930db7484fb79746a1784be9e1a5f8218f9af8656a141f"},
+]
+
+[package.dependencies]
+jupyter-server = ">=2.4.0,<3"
+jupyterlab = ">=4.2.0,<4.3"
+jupyterlab-server = ">=2.27.1,<3"
+notebook-shim = ">=0.2,<0.3"
+tornado = ">=6.2.0"
+
+[package.extras]
+dev = ["hatch", "pre-commit"]
+docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
+
+[[package]]
+name = "notebook-shim"
+version = "0.2.4"
+description = "A shim layer for notebook traits and config"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "notebook_shim-0.2.4-py3-none-any.whl", hash = "sha256:411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef"},
+    {file = "notebook_shim-0.2.4.tar.gz", hash = "sha256:b4b2cfa1b65d98307ca24361f5b30fe785b53c3fd07b7a47e89acb5e6ac638cb"},
+]
+
+[package.dependencies]
+jupyter-server = ">=1.8,<3"
+
+[package.extras]
+test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"]
+
 [[package]]
 name = "numpy"
 version = "1.26.4"
@@ -2266,6 +2979,17 @@ document = ["ase", "cmaes (>=0.10.0)", "fvcore", "lightgbm", "matplotlib (!=3.6.
 optional = ["boto3", "cmaes (>=0.10.0)", "google-cloud-storage", "matplotlib (!=3.6.0)", "pandas", "plotly (>=4.9.0)", "redis", "scikit-learn (>=0.24.2)", "scipy", "torch"]
 test = ["coverage", "fakeredis[lua]", "kaleido", "moto", "pytest", "scipy (>=1.9.2)", "torch"]
 
+[[package]]
+name = "overrides"
+version = "7.7.0"
+description = "A decorator to automatically detect mismatch when overriding a method."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "overrides-7.7.0-py3-none-any.whl", hash = "sha256:c7ed9d062f78b8e4c1a7b70bd8796b35ead4d9f510227ef9c5dc7626c60d7e49"},
+    {file = "overrides-7.7.0.tar.gz", hash = "sha256:55158fa3d93b98cc75299b1e67078ad9003ca27945c76162c1c0766d6f91820a"},
+]
+
 [[package]]
 name = "packaging"
 version = "24.0"
@@ -2277,6 +3001,17 @@ files = [
     {file = "packaging-24.0.tar.gz", hash = "sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9"},
 ]
 
+[[package]]
+name = "pandocfilters"
+version = "1.5.1"
+description = "Utilities for writing pandoc filters in python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "pandocfilters-1.5.1-py2.py3-none-any.whl", hash = "sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc"},
+    {file = "pandocfilters-1.5.1.tar.gz", hash = "sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e"},
+]
+
 [[package]]
 name = "parso"
 version = "0.8.4"
@@ -2292,6 +3027,20 @@ files = [
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
 testing = ["docopt", "pytest"]
 
+[[package]]
+name = "periodic-table-dataclasses"
+version = "1.0"
+description = "Python library of Periodic-Table-JSON"
+optional = false
+python-versions = "*"
+files = [
+    {file = "periodic_table_dataclasses-1.0-py3-none-any.whl", hash = "sha256:367b7f57a6db8eb20e49c0d75f00f820f78a6b6b08edb023f6c29812b4b99a85"},
+    {file = "periodic_table_dataclasses-1.0.tar.gz", hash = "sha256:4cd0b5055b747fbb2b3333fee90df191d3025cf030a41d8beda996e68a1fc97b"},
+]
+
+[package.dependencies]
+dataclasses-json = "*"
+
 [[package]]
 name = "pexpect"
 version = "4.9.0"
@@ -2407,6 +3156,45 @@ files = [
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.1)", "sphinx-autodoc-typehints (>=1.24)"]
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
+[[package]]
+name = "polars"
+version = "0.20.28"
+description = "Blazingly fast DataFrame library"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "polars-0.20.28-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:18eb471826edaf00b9f4ff0885d19b824e48b4a16521ee173e24ef17691b623e"},
+    {file = "polars-0.20.28-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:2258ab7ee65e1cfc86f9e762ae10c9959e79f8650f121d30404bef2a266922e0"},
+    {file = "polars-0.20.28-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:53b2d164ae9645fffb54920eed91e0a48f72fcc3dc9414c9e67871cdcf94533d"},
+    {file = "polars-0.20.28-cp38-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:4524bc108ddacd337c096abeabcd3310f42f10ba0f53c52d3ac5c9a17a9e71af"},
+    {file = "polars-0.20.28-cp38-abi3-win_amd64.whl", hash = "sha256:eae3549c3748e4323ca038314484215823bc7c3f764bb685ea1080e132fd29fd"},
+    {file = "polars-0.20.28.tar.gz", hash = "sha256:ac3a59032b88a7e036eebe03f393f4f7e24f5197a5311f51b9f2b59458031fc6"},
+]
+
+[package.extras]
+adbc = ["adbc-driver-manager", "adbc-driver-sqlite"]
+all = ["polars[adbc,async,cloudpickle,connectorx,deltalake,fastexcel,fsspec,gevent,iceberg,numpy,pandas,plot,pyarrow,pydantic,sqlalchemy,timezone,xlsx2csv,xlsxwriter]"]
+async = ["nest-asyncio"]
+cloudpickle = ["cloudpickle"]
+connectorx = ["connectorx (>=0.3.2)"]
+deltalake = ["deltalake (>=0.15.0)"]
+fastexcel = ["fastexcel (>=0.9)"]
+fsspec = ["fsspec"]
+gevent = ["gevent"]
+iceberg = ["pyiceberg (>=0.5.0)"]
+matplotlib = ["matplotlib"]
+numpy = ["numpy (>=1.16.0)"]
+openpyxl = ["openpyxl (>=3.0.0)"]
+pandas = ["pandas", "pyarrow (>=7.0.0)"]
+plot = ["hvplot (>=0.9.1)"]
+pyarrow = ["pyarrow (>=7.0.0)"]
+pydantic = ["pydantic"]
+pyxlsb = ["pyxlsb (>=1.0)"]
+sqlalchemy = ["pandas", "sqlalchemy"]
+timezone = ["backports-zoneinfo", "tzdata"]
+xlsx2csv = ["xlsx2csv (>=0.8.0)"]
+xlsxwriter = ["xlsxwriter"]
+
 [[package]]
 name = "pretty-errors"
 version = "1.2.25"
@@ -2421,6 +3209,20 @@ files = [
 [package.dependencies]
 colorama = "*"
 
+[[package]]
+name = "prometheus-client"
+version = "0.20.0"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "prometheus_client-0.20.0-py3-none-any.whl", hash = "sha256:cde524a85bce83ca359cc837f28b8c0db5cac7aa653a588fd7e84ba061c329e7"},
+    {file = "prometheus_client-0.20.0.tar.gz", hash = "sha256:287629d00b147a32dcb2be0b9df905da599b2d82f80377083ec8463309a4bb89"},
+]
+
+[package.extras]
+twisted = ["twisted"]
+
 [[package]]
 name = "prompt-toolkit"
 version = "3.0.43"
@@ -2583,6 +3385,34 @@ files = [
 [package.dependencies]
 six = ">=1.5"
 
+[[package]]
+name = "python-json-logger"
+version = "2.0.7"
+description = "A python library adding a json log formatter"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "python-json-logger-2.0.7.tar.gz", hash = "sha256:23e7ec02d34237c5aa1e29a070193a4ea87583bb4e7f8fd06d3de8264c4b2e1c"},
+    {file = "python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd"},
+]
+
+[[package]]
+name = "python-slugify"
+version = "8.0.4"
+description = "A Python slugify application that also handles Unicode"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856"},
+    {file = "python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8"},
+]
+
+[package.dependencies]
+text-unidecode = ">=1.3"
+
+[package.extras]
+unidecode = ["Unidecode (>=1.1.1)"]
+
 [[package]]
 name = "pytorch-lightning"
 version = "2.2.4"
@@ -2637,6 +3467,21 @@ files = [
     {file = "pywin32-306-cp39-cp39-win_amd64.whl", hash = "sha256:39b61c15272833b5c329a2989999dcae836b1eed650252ab1b7bfbe1d59f30f4"},
 ]
 
+[[package]]
+name = "pywinpty"
+version = "2.0.13"
+description = "Pseudo terminal support for Windows from Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pywinpty-2.0.13-cp310-none-win_amd64.whl", hash = "sha256:697bff211fb5a6508fee2dc6ff174ce03f34a9a233df9d8b5fe9c8ce4d5eaf56"},
+    {file = "pywinpty-2.0.13-cp311-none-win_amd64.whl", hash = "sha256:b96fb14698db1284db84ca38c79f15b4cfdc3172065b5137383910567591fa99"},
+    {file = "pywinpty-2.0.13-cp312-none-win_amd64.whl", hash = "sha256:2fd876b82ca750bb1333236ce98488c1be96b08f4f7647cfdf4129dfad83c2d4"},
+    {file = "pywinpty-2.0.13-cp38-none-win_amd64.whl", hash = "sha256:61d420c2116c0212808d31625611b51caf621fe67f8a6377e2e8b617ea1c1f7d"},
+    {file = "pywinpty-2.0.13-cp39-none-win_amd64.whl", hash = "sha256:71cb613a9ee24174730ac7ae439fd179ca34ccb8c5349e8d7b72ab5dea2c6f4b"},
+    {file = "pywinpty-2.0.13.tar.gz", hash = "sha256:c34e32351a3313ddd0d7da23d27f835c860d32fe4ac814d372a3ea9594f41dde"},
+]
+
 [[package]]
 name = "pyxdg"
 version = "0.28"
@@ -2808,6 +3653,48 @@ files = [
 [package.dependencies]
 cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
+[[package]]
+name = "qtconsole"
+version = "5.5.2"
+description = "Jupyter Qt console"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "qtconsole-5.5.2-py3-none-any.whl", hash = "sha256:42d745f3d05d36240244a04e1e1ec2a86d5d9b6edb16dbdef582ccb629e87e0b"},
+    {file = "qtconsole-5.5.2.tar.gz", hash = "sha256:6b5fb11274b297463706af84dcbbd5c92273b1f619e6d25d08874b0a88516989"},
+]
+
+[package.dependencies]
+ipykernel = ">=4.1"
+jupyter-client = ">=4.1"
+jupyter-core = "*"
+packaging = "*"
+pygments = "*"
+pyzmq = ">=17.1"
+qtpy = ">=2.4.0"
+traitlets = "<5.2.1 || >5.2.1,<5.2.2 || >5.2.2"
+
+[package.extras]
+doc = ["Sphinx (>=1.3)"]
+test = ["flaky", "pytest", "pytest-qt"]
+
+[[package]]
+name = "qtpy"
+version = "2.4.1"
+description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "QtPy-2.4.1-py3-none-any.whl", hash = "sha256:1c1d8c4fa2c884ae742b069151b0abe15b3f70491f3972698c683b8e38de839b"},
+    {file = "QtPy-2.4.1.tar.gz", hash = "sha256:a5a15ffd519550a1361bdc56ffc07fda56a6af7292f17c7b395d4083af632987"},
+]
+
+[package.dependencies]
+packaging = "*"
+
+[package.extras]
+test = ["pytest (>=6,!=7.0.0,!=7.0.1)", "pytest-cov (>=3.0.0)", "pytest-qt"]
+
 [[package]]
 name = "referencing"
 version = "0.35.1"
@@ -2933,6 +3820,31 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "rfc3339-validator"
+version = "0.1.4"
+description = "A pure python RFC3339 validator"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "rfc3339_validator-0.1.4-py2.py3-none-any.whl", hash = "sha256:24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa"},
+    {file = "rfc3339_validator-0.1.4.tar.gz", hash = "sha256:138a2abdf93304ad60530167e51d2dfb9549521a836871b88d7f4695d0022f6b"},
+]
+
+[package.dependencies]
+six = "*"
+
+[[package]]
+name = "rfc3986-validator"
+version = "0.1.1"
+description = "Pure python rfc3986 validator"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "rfc3986_validator-0.1.1-py2.py3-none-any.whl", hash = "sha256:2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9"},
+    {file = "rfc3986_validator-0.1.1.tar.gz", hash = "sha256:3d44bde7921b3b9ec3ae4e3adca370438eccebc676456449b145d533b240d055"},
+]
+
 [[package]]
 name = "rich"
 version = "13.3.1"
@@ -3059,6 +3971,144 @@ files = [
     {file = "rpds_py-0.18.1.tar.gz", hash = "sha256:dc48b479d540770c811fbd1eb9ba2bb66951863e448efec2e2c102625328e92f"},
 ]
 
+[[package]]
+name = "safetensors"
+version = "0.4.3"
+description = ""
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "safetensors-0.4.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:dcf5705cab159ce0130cd56057f5f3425023c407e170bca60b4868048bae64fd"},
+    {file = "safetensors-0.4.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:bb4f8c5d0358a31e9a08daeebb68f5e161cdd4018855426d3f0c23bb51087055"},
+    {file = "safetensors-0.4.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70a5319ef409e7f88686a46607cbc3c428271069d8b770076feaf913664a07ac"},
+    {file = "safetensors-0.4.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fb9c65bd82f9ef3ce4970dc19ee86be5f6f93d032159acf35e663c6bea02b237"},
+    {file = "safetensors-0.4.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:edb5698a7bc282089f64c96c477846950358a46ede85a1c040e0230344fdde10"},
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+    {file = "safetensors-0.4.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:018b691383026a2436a22b648873ed11444a364324e7088b99cd2503dd828400"},
+    {file = "safetensors-0.4.3-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:309b10dbcab63269ecbf0e2ca10ce59223bb756ca5d431ce9c9eeabd446569da"},
+    {file = "safetensors-0.4.3-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:b277482120df46e27a58082df06a15aebda4481e30a1c21eefd0921ae7e03f65"},
+    {file = "safetensors-0.4.3.tar.gz", hash = "sha256:2f85fc50c4e07a21e95c24e07460fe6f7e2859d0ce88092838352b798ce711c2"},
+]
+
+[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)"]
+quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"]
+tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
+testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
+torch = ["safetensors[numpy]", "torch (>=1.10)"]
+
+[[package]]
+name = "send2trash"
+version = "1.8.3"
+description = "Send file to trash natively under Mac OS X, Windows and Linux"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+files = [
+    {file = "Send2Trash-1.8.3-py3-none-any.whl", hash = "sha256:0c31227e0bd08961c7665474a3d1ef7193929fedda4233843689baa056be46c9"},
+    {file = "Send2Trash-1.8.3.tar.gz", hash = "sha256:b18e7a3966d99871aefeb00cfbcfdced55ce4871194810fc71f4aa484b953abf"},
+]
+
+[package.extras]
+nativelib = ["pyobjc-framework-Cocoa", "pywin32"]
+objc = ["pyobjc-framework-Cocoa"]
+win32 = ["pywin32"]
+
 [[package]]
 name = "sentry-sdk"
 version = "2.1.1"
@@ -3269,6 +4319,17 @@ files = [
     {file = "smmap-5.0.1.tar.gz", hash = "sha256:dceeb6c0028fdb6734471eb07c0cd2aae706ccaecab45965ee83f11c8d3b1f62"},
 ]
 
+[[package]]
+name = "sniffio"
+version = "1.3.1"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
+    {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
+]
+
 [[package]]
 name = "soupsieve"
 version = "2.5"
@@ -3446,6 +4507,38 @@ files = [
     {file = "tensorboard_data_server-0.7.2-py3-none-manylinux_2_31_x86_64.whl", hash = "sha256:ef687163c24185ae9754ed5650eb5bc4d84ff257aabdc33f0cc6f74d8ba54530"},
 ]
 
+[[package]]
+name = "terminado"
+version = "0.18.1"
+description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "terminado-0.18.1-py3-none-any.whl", hash = "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0"},
+    {file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"},
+]
+
+[package.dependencies]
+ptyprocess = {version = "*", markers = "os_name != \"nt\""}
+pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
+tornado = ">=6.1.0"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
+
+[[package]]
+name = "text-unidecode"
+version = "1.3"
+description = "The most basic Text::Unidecode port"
+optional = false
+python-versions = "*"
+files = [
+    {file = "text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93"},
+    {file = "text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8"},
+]
+
 [[package]]
 name = "timg"
 version = "1.1.6"
@@ -3460,6 +4553,24 @@ files = [
 [package.dependencies]
 pillow = "*"
 
+[[package]]
+name = "tinycss2"
+version = "1.3.0"
+description = "A tiny CSS parser"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tinycss2-1.3.0-py3-none-any.whl", hash = "sha256:54a8dbdffb334d536851be0226030e9505965bb2f30f21a4a82c55fb2a80fae7"},
+    {file = "tinycss2-1.3.0.tar.gz", hash = "sha256:152f9acabd296a8375fbca5b84c961ff95971fcfc32e79550c8df8e29118c54d"},
+]
+
+[package.dependencies]
+webencodings = ">=0.4"
+
+[package.extras]
+doc = ["sphinx", "sphinx_rtd_theme"]
+test = ["pytest", "ruff"]
+
 [[package]]
 name = "torch"
 version = "2.3.0"
@@ -3675,6 +4786,17 @@ rich = ">=10.11.0"
 shellingham = ">=1.3.0"
 typing-extensions = ">=3.7.4.3"
 
+[[package]]
+name = "types-python-dateutil"
+version = "2.9.0.20240316"
+description = "Typing stubs for python-dateutil"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-python-dateutil-2.9.0.20240316.tar.gz", hash = "sha256:5d2f2e240b86905e40944dd787db6da9263f0deabef1076ddaed797351ec0202"},
+    {file = "types_python_dateutil-2.9.0.20240316-py3-none-any.whl", hash = "sha256:6b8cb66d960771ce5ff974e9dd45e38facb81718cc1e208b10b1baccbfdbee3b"},
+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.11.0"
@@ -3686,6 +4808,21 @@ files = [
     {file = "typing_extensions-4.11.0.tar.gz", hash = "sha256:83f085bd5ca59c80295fc2a82ab5dac679cbe02b9f33f7d83af68e241bea51b0"},
 ]
 
+[[package]]
+name = "typing-inspect"
+version = "0.9.0"
+description = "Runtime inspection utilities for typing module."
+optional = false
+python-versions = "*"
+files = [
+    {file = "typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f"},
+    {file = "typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78"},
+]
+
+[package.dependencies]
+mypy-extensions = ">=0.3.0"
+typing-extensions = ">=3.7.4"
+
 [[package]]
 name = "uc-micro-py"
 version = "1.0.3"
@@ -3718,6 +4855,20 @@ fsspec = ">=2022.1.0"
 dev = ["adlfs", "aiohttp", "cheroot", "gcsfs", "moto[s3,server] (<5)", "mypy (==1.8.0)", "packaging", "pydantic", "pydantic-settings", "pylint (==2.17.4)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-mock (==3.12.0)", "pytest-sugar (==0.9.7)", "requests", "s3fs", "webdav4[fsspec]", "wsgidav"]
 tests = ["mypy (==1.8.0)", "packaging", "pylint (==2.17.4)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-mock (==3.12.0)", "pytest-sugar (==0.9.7)"]
 
+[[package]]
+name = "uri-template"
+version = "1.3.0"
+description = "RFC 6570 URI Template Processor"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"},
+    {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"},
+]
+
+[package.extras]
+dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
+
 [[package]]
 name = "urllib3"
 version = "2.2.1"
@@ -3788,6 +4939,48 @@ files = [
     {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
 ]
 
+[[package]]
+name = "webcolors"
+version = "1.13"
+description = "A library for working with the color formats defined by HTML and CSS."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "webcolors-1.13-py3-none-any.whl", hash = "sha256:29bc7e8752c0a1bd4a1f03c14d6e6a72e93d82193738fa860cbff59d0fcc11bf"},
+    {file = "webcolors-1.13.tar.gz", hash = "sha256:c225b674c83fa923be93d235330ce0300373d02885cef23238813b0d5668304a"},
+]
+
+[package.extras]
+docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"]
+tests = ["pytest", "pytest-cov"]
+
+[[package]]
+name = "webencodings"
+version = "0.5.1"
+description = "Character encoding aliases for legacy web content"
+optional = false
+python-versions = "*"
+files = [
+    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
+    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
+]
+
+[[package]]
+name = "websocket-client"
+version = "1.8.0"
+description = "WebSocket client for Python with low level API options"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"},
+    {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
+optional = ["python-socks", "wsaccel"]
+test = ["websockets"]
+
 [[package]]
 name = "werkzeug"
 version = "3.0.3"
@@ -3805,6 +4998,17 @@ MarkupSafe = ">=2.1.1"
 [package.extras]
 watchdog = ["watchdog (>=2.3)"]
 
+[[package]]
+name = "widgetsnbextension"
+version = "4.0.10"
+description = "Jupyter interactive widgets for Jupyter Notebook"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "widgetsnbextension-4.0.10-py3-none-any.whl", hash = "sha256:d37c3724ec32d8c48400a435ecfa7d3e259995201fbefa37163124a9fcb393cc"},
+    {file = "widgetsnbextension-4.0.10.tar.gz", hash = "sha256:64196c5ff3b9a9183a8e699a4227fb0b7002f252c814098e66c4d1cd0644688f"},
+]
+
 [[package]]
 name = "yarl"
 version = "1.9.4"
@@ -3911,4 +5115,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "8bf3620a195c51ef0b5bf1cc4e98299c43e4b288cd00f38c167764fb917522f8"
+content-hash = "74e84f457ce411d0612153d658f0e43f92f140297fcc1812501b74e7757fedc3"
diff --git a/pyproject.toml b/pyproject.toml
index 42fafb6..a63d622 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,6 +22,12 @@ euporie = "^2.8.2"
 ipykernel = "^6.29.4"
 tensorboard = "^2.16.2"
 typer = "^0.12.3"
+kaggle = "^1.6.14"
+periodic-table-dataclasses = "^1.0"
+polars = "^0.20.28"
+jupyter = "^1.0.0"
+safetensors = "^0.4.3"
+alive-progress = "^3.1.5"
 
 
 [build-system]
diff --git a/symbolic_nn_tests/dataloader.py b/symbolic_nn_tests/dataloader.py
index 5ad0142..55ab1c4 100644
--- a/symbolic_nn_tests/dataloader.py
+++ b/symbolic_nn_tests/dataloader.py
@@ -1,26 +1,18 @@
 from pathlib import Path
 from torchvision.datasets import Caltech256
 from torchvision.transforms import ToTensor
-from torch.utils.data import random_split
-from torch.utils.data import BatchSampler
+from torch.utils.data import DataLoader, random_split
 
 
 PROJECT_ROOT = Path(__file__).parent.parent
+DATASET_DIR = PROJECT_ROOT / "datasets/"
 
 
-def get_dataset(
+def create_dataset(
     split: (float, float, float) = (0.7, 0.1, 0.2),
     dataset=Caltech256,
-    batch_size: int = 128,
-    drop_last: bool = False,
     **kwargs,
 ):
-    _kwargs = {
-        "transform": ToTensor(),
-    }
-    _kwargs.update(kwargs)
-    ds = dataset(PROJECT_ROOT / "datasets/", download=True, **_kwargs)
-    train, val, test = (
-        BatchSampler(i, batch_size, drop_last) for i in random_split(ds, split)
-    )
+    ds = dataset(DATASET_DIR, download=True, transform=ToTensor())
+    train, val, test = (DataLoader(i, **kwargs) for i in random_split(ds, split))
     return train, val, test
diff --git a/symbolic_nn_tests/experiment1/model.py b/symbolic_nn_tests/experiment1/model.py
index b164471..a3bfa11 100644
--- a/symbolic_nn_tests/experiment1/model.py
+++ b/symbolic_nn_tests/experiment1/model.py
@@ -1,4 +1,5 @@
 from functools import lru_cache
+import torch
 from torch import nn
 
 
@@ -9,17 +10,35 @@ model = nn.Sequential(
 )
 
 
+def collate(batch):
+    x, y = zip(*batch)
+    x = [i[0] for i in x]
+    y = [torch.tensor(i) for i in y]
+    x = torch.stack(x).to("cuda")
+    y = torch.tensor(y).to("cuda")
+    return x, y
+
+
 # This is just a quick, lazy way to ensure all models are trained on the same dataset
 @lru_cache(maxsize=1)
 def get_singleton_dataset():
     from torchvision.datasets import QMNIST
 
-    from symbolic_nn_tests.dataloader import get_dataset
+    from symbolic_nn_tests.dataloader import create_dataset
 
-    return get_dataset(dataset=QMNIST)
+    return create_dataset(
+        dataset=QMNIST, collate_fn=collate, batch_size=128, shuffle=True
+    )
 
 
-def main(loss_func=nn.functional.cross_entropy, logger=None, **kwargs):
+def oh_vs_cat_cross_entropy(y_bin, y_cat):
+    return nn.functional.cross_entropy(
+        y_bin,
+        nn.functional.one_hot(y_cat),
+    )
+
+
+def main(loss_func=oh_vs_cat_cross_entropy, logger=None, **kwargs):
     import lightning as L
 
     from symbolic_nn_tests.train import TrainingWrapper
diff --git a/symbolic_nn_tests/experiment1/semantic_loss.py b/symbolic_nn_tests/experiment1/semantic_loss.py
index ade67ed..5c4a633 100644
--- a/symbolic_nn_tests/experiment1/semantic_loss.py
+++ b/symbolic_nn_tests/experiment1/semantic_loss.py
@@ -10,7 +10,10 @@ def create_semantic_cross_entropy(semantic_matrix):
         semantic_penalty = (abs_diff * penalty_tensor).sum()
         return ce_loss * semantic_penalty
 
-    return semantic_cross_entropy
+    def oh_vs_cat_semantic_cross_entropy(input_oh, target_cat):
+        return semantic_cross_entropy(input_oh, torch.nn.functional.one_hot(target_cat))
+
+    return oh_vs_cat_semantic_cross_entropy
 
 
 # NOTE: This similarity matrix defines loss scaling factors for misclassification
diff --git a/symbolic_nn_tests/experiment2/__init__.py b/symbolic_nn_tests/experiment2/__init__.py
new file mode 100644
index 0000000..e845b79
--- /dev/null
+++ b/symbolic_nn_tests/experiment2/__init__.py
@@ -0,0 +1,75 @@
+LEARNING_RATE = 10e-5
+
+
+def test(loss_func, version, tensorboard=True, wandb=True):
+    from .model import main as test_model
+
+    logger = []
+
+    if tensorboard:
+        from lightning.pytorch.loggers import TensorBoardLogger
+
+        tb_logger = TensorBoardLogger(
+            save_dir=".",
+            name="logs/comparison",
+            version=version,
+        )
+        logger.append(tb_logger)
+
+    if wandb:
+        import wandb as _wandb
+        from lightning.pytorch.loggers import WandbLogger
+
+        wandb_logger = WandbLogger(
+            project="Symbolic_NN_Tests",
+            name=version,
+            dir="wandb",
+        )
+        logger.append(wandb_logger)
+
+    test_model(logger=logger, loss_func=loss_func, lr=LEARNING_RATE)
+
+    if wandb:
+        _wandb.finish()
+
+
+def run(tensorboard: bool = True, wandb: bool = True):
+    from . import semantic_loss
+    from torch import nn
+
+    test(
+        nn.functional.cross_entropy,
+        "cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
+    test(
+        semantic_loss.similarity_cross_entropy,
+        "similarity_cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
+    test(
+        semantic_loss.hasline_cross_entropy,
+        "hasline_cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
+    test(
+        semantic_loss.hasloop_cross_entropy,
+        "hasloop_cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
+    test(
+        semantic_loss.multisemantic_cross_entropy,
+        "multisemantic_cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
+    test(
+        semantic_loss.garbage_cross_entropy,
+        "garbage_cross_entropy",
+        tensorboard=tensorboard,
+        wandb=wandb,
+    )
diff --git a/symbolic_nn_tests/experiment2/dataset.py b/symbolic_nn_tests/experiment2/dataset.py
new file mode 100644
index 0000000..4b91a12
--- /dev/null
+++ b/symbolic_nn_tests/experiment2/dataset.py
@@ -0,0 +1,244 @@
+import kaggle
+import polars as pl
+import shutil
+from functools import lru_cache
+from periodic_table import PeriodicTable
+import numpy as np
+import torch
+from torch.utils.data import TensorDataset
+import pickle
+from multiprocessing import Pool
+from symbolic_nn_tests.dataloader import DATASET_DIR
+import warnings
+from tqdm.auto import tqdm
+
+
+warnings.filterwarnings(action="ignore", category=UserWarning)
+
+
+PUBCHEM_DIR = DATASET_DIR / "PubChem"
+
+ORBITALS = {
+    "s": (0, 2),
+    "p": (1, 6),
+    "d": (2, 10),
+    "f": (3, 14),
+}
+
+
+def collate(batch):
+    x0_in, x1_in, y_in = list(zip(*batch))
+    x0_out = torch.nested.as_nested_tensor(list(x0_in))
+    x1_out = torch.nested.as_nested_tensor(list(x1_in))
+    y_out = torch.as_tensor(y_in)
+    return (x0_out, x1_out), y_out
+
+
+def pubchem(*args, **kwargs):
+    PUBCHEM_DIR.mkdir(exist_ok=True, parents=True)
+    return get_dataset()
+
+
+def get_dataset():
+    if not (
+        "pubchem_x0.pickle"
+        and "pubchem_x1.pickle"
+        and "pubchem_y.pickle" in (x.name for x in PUBCHEM_DIR.iterdir())
+    ):
+        construct_dataset("pubchem")
+    else:
+        print("Pre-existing dataset detected!")
+    print("Dataset loaded!")
+    return TensorDataset(*load_dataset("pubchem"))
+
+
+def construct_dataset(filename):
+    print("Constructing dataset...")
+    df = construct_ds_dataframe(filename)
+    save_dataframe_to_dataset(df, PUBCHEM_DIR / f"{filename}.pickle")
+    print("Dataset constructed!")
+
+
+def construct_ds_dataframe(filename):
+    print("Constructing dataset dataframe...")
+    df = add_molecule_encodings(construct_raw_dataset(filename))
+    # NOTE: This kind of checkpointing will be used throughout the construction process It doesn't
+    # take much disk space, it lets the GC collect out-of-scope data from the construction process
+    # and it makes it easier to debug if construction fails
+    parquet_file = PUBCHEM_DIR / f"{filename}.parquet"
+    df.write_parquet(parquet_file)
+    print("Dataset dataframe constructed!")
+    return pl.read_parquet(parquet_file)
+
+
+def construct_raw_dataset(filename):
+    print("Constructing raw dataset...")
+    df = collate_dataset()
+    parquet_file = PUBCHEM_DIR / f"{filename}_raw.parquet"
+    df.write_parquet(parquet_file)
+    print("Raw dataset constructed!")
+    return pl.read_parquet(parquet_file)
+
+
+def collate_dataset():
+    print("Collating dataset...")
+    if not (PUBCHEM_DIR.exists() and len(tuple(PUBCHEM_DIR.glob("*.json")))):
+        fetch_dataset()
+
+    df = pl.concat(
+        map(pl.read_json, PUBCHEM_DIR.glob("*.json")),
+    ).drop("id")
+    print("dataset collated!")
+    return df
+
+
+def fetch_dataset():
+    print("Fetching dataset...")
+    kaggle.api.dataset_download_files(
+        "burakhmmtgl/predict-molecular-properties", quiet=False, path=DATASET_DIR
+    )
+    shutil.unpack_archive(DATASET_DIR / "predict-molecular-properties.zip", PUBCHEM_DIR)
+    print("Dataset fetched!")
+
+
+@lru_cache(maxsize=1)
+def get_periodic_table():
+    return PeriodicTable()
+
+
+def add_molecule_encodings(df):
+    atom_properties, atom_electrons = encode_molecules(df["atoms"])
+    return df.with_columns(
+        atom_properties=atom_properties, atom_electrons=atom_electrons
+    )
+
+
+def encode_molecules(series):
+    # Yes, it is gross and RAM inefficient to do it this way but i dont have all day...
+    with Pool() as p:
+        molecules = p.map(encode_molecule, series)
+    properties, electrons = zip(*molecules)
+    return pl.Series(properties), pl.Series(electrons)
+
+
+def encode_molecule(molecule):
+    properties, electrons = zip(*_encode_molecule(molecule))
+    properties = pl.Series(properties)
+    return properties, electrons
+
+
+def _encode_molecule(molecule):
+    for atom in molecule:
+        properties, electrons = encode_atom(atom["type"])
+        yield np.array([*properties, *atom["xyz"]]), pl.Series(electrons)
+
+
+def encode_atom(atom):
+    element = get_periodic_table().search_symbol(atom)
+    return (
+        np.array(
+            [
+                # n and z need to be scaled somehow to normalize to approximately 1
+                # Because this is kind arbitrary i've decided to scale relative to
+                # Fermium (n = 100)
+                element.atomic / 100.0,
+                element.atomic_mass / 257.0,
+                element.electron_affinity / 350.0,  # Highest known is just below 350
+                element.electronegativity_pauling
+                / 4.0,  # Max theoretical val is 4.0 here
+            ],
+        ),
+        encode_electron_config(element.electron_configuration),
+    )
+
+
+def encode_electron_config(config):
+    return np.array([encode_orbital(x) for x in config.split()])
+
+
+def encode_orbital(orbital):
+    shell, subshell, *n = orbital
+    shell = int(shell)
+    n = int("".join(n))
+    azimuthal, capacity = ORBITALS[subshell]
+    return np.array(
+        [
+            1.0
+            / shell,  # This is the simplest way to normalize shell, as shells become less distinct as n increases
+            azimuthal / 4.0,  # This is simply normalizing the azimuthal quantum number
+            n / capacity,  # Basically encoding this as a proportion of "fullness"
+        ],
+    )
+
+
+def save_dataframe_to_dataset(df, filename):
+    print("Saving dataset to tensors...")
+    with (filename.parent / f"{filename.stem}_x0{filename.suffix}").open("wb") as f:
+        pickle.dump(properties_to_tensor(df).float(), f)
+    with (filename.parent / f"{filename.stem}_x1{filename.suffix}").open("wb") as f:
+        pickle.dump(electrons_to_tensor(df).float(), f)
+    with (filename.parent / f"{filename.stem}_y{filename.suffix}").open("wb") as f:
+        pickle.dump(df["En"].to_torch().float(), f)
+    del df
+    print("Tensors saved!")
+
+
+def chunked_df(df, n):
+    chunk_size = (len(df) // n) + 1
+    chunk_boundaries = [*range(0, len(df), chunk_size), len(df)]
+    chunk_ranges = list(zip(chunk_boundaries[:-1], chunk_boundaries[1:]))
+    yield from (df[i:j] for i, j in chunk_ranges)
+
+
+def properties_to_tensor(df):
+    with Pool() as p:
+        out = torch.cat(
+            p.map(
+                property_chunk_to_torch, chunked_df(df["atom_properties"], p._processes)
+            )
+        )
+    return out
+
+
+def property_chunk_to_torch(chunk):
+    return torch.nested.nested_tensor([properties_to_torch(x) for x in chunk])
+
+
+def properties_to_torch(p):
+    return torch.stack(tuple(map(pl.Series.to_torch, p)))
+
+
+def electrons_to_tensor(df):
+    return torch.nested.nested_tensor(
+        [
+            molecule_electrons_to_torch(e)
+            for e in tqdm(df["atom_electrons"], desc="Converting molecules to orbitals")
+        ]
+    )
+
+
+def molecule_electrons_to_torch(e):
+    return torch.stack([atom_electrons_to_torch(x) for x in e])
+
+
+def atom_electrons_to_torch(e):
+    # pytorch doesn't like doubly nested tensors, and the unnocupied orbitals still exist here even if
+    # they're empty, so it makes sense to pad here instead. No elements in the dataset exceed an
+    # azimuthal of 3, so we only need to pad to length 10. Also: i'm realising here that the orbital
+    # info will be unecessary if we have to pad here anyway
+    return pad_tensor_to(torch.tensor(tuple(x[-1] for x in e)), 10)
+
+
+def pad_tensor_to(t, length):
+    return torch.nn.functional.pad(t, (0, length - t.shape[0]))
+
+
+def load_dataset(filename):
+    filepath = PUBCHEM_DIR / f"{filename}.pickle"
+    with (filepath.parent / f"{filepath.stem}_x0{filepath.suffix}").open("rb") as f:
+        x0 = pickle.load(f)
+    with (filepath.parent / f"{filepath.stem}_x1{filepath.suffix}").open("rb") as f:
+        x1 = pickle.load(f)
+    with (filepath.parent / f"{filepath.stem}_y{filepath.suffix}").open("rb") as f:
+        y = pickle.load(f)
+    return x0, x1, y
diff --git a/symbolic_nn_tests/experiment2/model.py b/symbolic_nn_tests/experiment2/model.py
new file mode 100644
index 0000000..a436e8f
--- /dev/null
+++ b/symbolic_nn_tests/experiment2/model.py
@@ -0,0 +1,76 @@
+from functools import lru_cache
+import torch
+from torch import nn
+
+
+class Model(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+        self.x0_encoder = nn.TransformerEncoderLayer(7, 7)
+        self.x1_encoder = nn.TransformerEncoderLayer(10, 10)
+        self.encode_x0 = self.create_xval_encoding_fn(self.x0_encoder)
+        self.encode_x1 = self.create_xval_encoding_fn(self.x1_encoder)
+        self.ff = nn.Sequential(
+            nn.Linear(17, 256),
+            nn.ReLU(),
+            nn.Linear(256, 128),
+            nn.ReLU(),
+            nn.Linear(128, 64),
+            nn.ReLU(),
+            nn.Linear(64, 32),
+            nn.ReLU(),
+            nn.Linear(32, 16),
+            nn.ReLU(),
+            nn.Linear(16, 8),
+            nn.ReLU(),
+            nn.Linear(8, 1),
+        )
+
+    @staticmethod
+    def create_xval_encoding_fn(layer):
+        def encoding_fn(xbatch):
+            return torch.stack([layer(x)[-1] for x in xbatch])
+
+        return encoding_fn
+
+    def forward(self, x):
+        x0, x1 = x
+        x0 = self.encode_x0(x0)
+        x1 = self.encode_x1(x1)
+        x = torch.cat([x0, x1], dim=1)
+        y = self.ff(x)
+        return y
+
+
+# This is just a quick, lazy way to ensure all models are trained on the same dataset
+@lru_cache(maxsize=1)
+def get_singleton_dataset():
+    from symbolic_nn_tests.dataloader import create_dataset
+    from symbolic_nn_tests.experiment2.dataset import collate, pubchem
+
+    return create_dataset(
+        dataset=pubchem, collate_fn=collate, batch_size=128, shuffle=True
+    )
+
+
+def main(loss_func=nn.functional.smooth_l1_loss, logger=None, **kwargs):
+    import lightning as L
+
+    from symbolic_nn_tests.train import TrainingWrapper
+
+    if logger is None:
+        from lightning.pytorch.loggers import TensorBoardLogger
+
+        logger = TensorBoardLogger(save_dir=".", name="logs/ffnn")
+
+    train, val, test = get_singleton_dataset()
+    lmodel = TrainingWrapper(Model(), loss_func=loss_func)
+    lmodel.configure_optimizers(optimizer=torch.optim.NAdam, **kwargs)
+    trainer = L.Trainer(max_epochs=20, logger=logger)
+    trainer.fit(model=lmodel, train_dataloaders=train, val_dataloaders=val)
+    trainer.test(dataloaders=test)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/symbolic_nn_tests/experiment2/semantic_loss.py b/symbolic_nn_tests/experiment2/semantic_loss.py
new file mode 100644
index 0000000..aaa3285
--- /dev/null
+++ b/symbolic_nn_tests/experiment2/semantic_loss.py
@@ -0,0 +1 @@
+import torch
diff --git a/symbolic_nn_tests/train.py b/symbolic_nn_tests/train.py
index fe76f02..a82969f 100644
--- a/symbolic_nn_tests/train.py
+++ b/symbolic_nn_tests/train.py
@@ -1,37 +1,26 @@
-import torch
 from torch import nn, optim
 import lightning as L
 
 
-def collate_batch(batch):
-    x, y = zip(*batch)
-    x = [i[0] for i in x]
-    y = [torch.tensor(i) for i in y]
-    x = torch.stack(x).to("cuda")
-    y = torch.tensor(y).to("cuda")
-    return x, y
-
-
 class TrainingWrapper(L.LightningModule):
-    def __init__(self, model, loss_func=nn.functional.cross_entropy):
+    def __init__(self, model, loss_func=nn.functional.mse_loss, accuracy=None):
         super().__init__()
         self.model = model
         self.loss_func = loss_func
+        self.accuracy = accuracy
 
     def _forward_step(self, batch, batch_idx, label=""):
-        x, y = collate_batch(batch)
+        x, y = batch
         y_pred = self.model(x)
-        batch_size = x.shape[0]
-        one_hot_y = nn.functional.one_hot(y).type(torch.float64)
-        loss = self.loss_func(y_pred, one_hot_y)
-        acc = torch.sum(y_pred.argmax(dim=1) == y) / batch_size
-        self.log(f"{label}{'_' if label else ''}loss", loss, batch_size=batch_size)
-        self.log(f"{label}{'_' if label else ''}acc", acc, batch_size=batch_size)
-        return loss, acc
+        loss = self.loss_func(y_pred, y)
+        self.log(f"{label}{'_' if label else ''}loss", loss)
+        if self.accuracy is not None:
+            acc = self.accuracy(y_pred, y)
+            self.log(f"{label}{'_' if label else ''}acc", acc)
+        return loss
 
     def training_step(self, batch, batch_idx):
-        loss, _ = self._forward_step(batch, batch_idx, label="train")
-        return loss
+        return self._forward_step(batch, batch_idx, label="train")
 
     def validation_step(self, batch, batch_idx):
         self._forward_step(batch, batch_idx, label="val")