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{
  "text": "Right now I'm trying to train word embeddings using pytorch. for obvious reasons I want to use a GPU, but right now lightning throws an ImportError. I followed a guide made by Josh Starmer. On the CPU it runs perfectly. \n\nI'm using a SageMaker ml.g4dn.xlarge instance, so it's using an Nvidia T4.\n\nMy code is the following:\n\n    import torch # PyTorch\n    import torch.nn as nn\n    \n    from torch.optim import Adam # for backpropagation\n    from torch.distributions.uniform import Uniform # for initializing weights\n    from torch.utils.data import TensorDataset, DataLoader\n    \n    import lightning as L\n    \n    import pandas as pd\n    import matplotlib.pyplot as plt\n    import seaborn as sns\n    \n    inputs = torch.tensor([[1.,0.,0.,0.],\n                           [0.,1.,0.,0.],\n                           [0.,0.,1.,0.],\n                           [0.,0.,0.,1.]])\n    labels = torch.tensor([[0.,1.,0.,0.],\n                           [0.,0.,1.,0.],\n                           [0.,0.,0.,1.],\n                           [0.,1.,0.,0.]])\n    dataset = TensorDataset(inputs, labels)\n    dataloader = DataLoader(dataset)\n    \n    # using PyTorch Linear()\n    class WordEmbeddingWithLinear(L.LightningModule):\n    \n        def __init__(self):\n    \n            super().__init__()\n            # in_features=4, out_features=2 -> connecting 4 inputs to 2 nodes\n            # 4 Weights for each of 2 nodes in the hidden layer\n            self.input_to_hidden = nn.Linear(in_features=4, out_features=2, bias=False)\n            # in_features=4, out_features=2 -> connecting 2 nodes to 4 outputs\n            # 2 Weights for each of 4 outputs\n            self.hidden_to_output = nn.Linear(in_features=2, out_features=4, bias=False)\n            #CrossEntropyLoss, includes SoftMax\n            self.loss = nn.CrossEntropyLoss()\n    \n        def forward(self, input):\n            # pass input to Linear Object and save sums in \"hidden\"\n            hidden = self.input_to_hidden(input)\n            # activation functions are identity functions -> activation functions can be ignored\n            # hidden_to_output calculates the output values of the activation functions\n            output_values = self.hidden_to_output(hidden)\n            return output_values\n    \n        def configure_optimizers(self):\n            return Adam(self.parameters(), lr=0.1)\n    \n            # Calculate loss (cross entropy loss), takes batch of training data plus index of batch\n        def training_step(self, batch, batch_idx):\n            input_i, label_i = batch\n            # run input through the network up to the SoftMax function\n            output_i = self.forward(input_i)\n            # run through SoftMax and quantify the difference between SoftMax and ideal values\n            loss = self.loss(output_i, label_i)\n            \n            return loss\n    \n    \n    \n    modelLinear = WordEmbeddingWithLinear()\n    \n    \n    trainer = L.Trainer(max_epochs=100)\n    trainer.fit(modelLinear, train_dataloaders=dataloader)\n    \n\nAt this point it crashes with the following Message\n\n    GPU available: True (cuda), used: True\n    TPU available: False, using: 0 TPU cores\n    IPU available: False, using: 0 IPUs\n    HPU available: False, using: 0 HPUs\n    \n    ---------------------------------------------------------------------------\n    ImportError                               Traceback (most recent call last)\n    Cell In[51], line 2\n          1 trainer = L.Trainer(max_epochs=100)\n    ----> 2 trainer.fit(modelLinear, train_dataloaders=dataloader)\n    \n    File ~/.conda/envs/mamba_gpu/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py:538, in Trainer.fit(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)\n        504 def fit(\n        505     self,\n        506     model: \"pl.LightningModule\",\n       (...)\n        510     ckpt_path: Optional[_PATH] = None,\n        511 ) -> None:\n        512     r\"\"\"Runs the full optimization routine.\n        513 \n        514     Args:\n       (...)\n        536 \n        537     \"\"\"\n    --> 538     model = _maybe_unwrap_optimized(model)\n        539     self.strategy._lightning_module = model\n        540     _verify_strategy_supports_compile(model, self.strategy)\n    \n    File ~/.conda/envs/mamba_gpu/lib/python3.10/site-packages/lightning/pytorch/utilities/compile.py:125, in _maybe_unwrap_optimized(model)\n        123         raise TypeError(f\"`model` must be a `LightningModule`, got `{type(model).__qualname__}`\")\n        124     return model\n    --> 125 from torch._dynamo import OptimizedModule\n        127 if isinstance(model, OptimizedModule):\n        128     return from_compiled(model)\n    \n    File ~/.conda/envs/mamba_gpu/lib/python3.10/site-packages/torch/_dynamo/__init__.py:2\n          1 import torch\n    ----> 2 from . import allowed_functions, convert_frame, eval_frame, resume_execution\n          3 from .backends.registry import list_backends, register_backend\n          4 from .convert_frame import replay\n    \n    File ~/.conda/envs/mamba_gpu/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py:44\n         34 from .eval_frame import always_optimize_code_objects, skip_code, TorchPatcher\n         35 from .exc import (\n         36     augment_exc_message,\n         37     BackendCompilerFailed,\n       (...)\n         42     Unsupported,\n         43 )\n    ---> 44 from .guards import CheckFunctionManager, GuardedCode\n         45 from .hooks import Hooks\n         46 from .output_graph import OutputGraph\n    \n    File ~/.conda/envs/mamba_gpu/lib/python3.10/site-packages/torch/_dynamo/guards.py:48\n         45 from torch.utils.weak import TensorWeakRef, WeakIdRef\n         47 from . import config, convert_frame, mutation_guard\n    ---> 48 from .eval_frame import set_guard_error_hook, set_guard_fail_hook\n         49 from .exc import unimplemented\n         50 from .source import TypeSource\n    \n    ImportError: cannot import name 'set_guard_fail_hook' from 'torch._dynamo.eval_frame' (/home/sagemaker-user/.conda/envs/mamba_gpu/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py)\n\nI have no idea what seems to be incompatible.\n\nHere's a YAML from my mamba environment:\n\n    name: mamba_gpu\n    channels:\n      - conda-forge\n    dependencies:\n      - _libgcc_mutex=0.1=conda_forge\n      - _openmp_mutex=4.5=2_gnu\n      - alsa-lib=1.2.11=hd590300_1\n      - archspec=0.2.3=pyhd8ed1ab_0\n      - asttokens=2.4.1=pyhd8ed1ab_0\n      - attr=2.5.1=h166bdaf_1\n      - boltons=24.0.0=pyhd8ed1ab_0\n      - brotli=1.1.0=hd590300_1\n      - brotli-bin=1.1.0=hd590300_1\n      - brotli-python=1.1.0=py310hc6cd4ac_1\n      - bzip2=1.0.8=hd590300_5\n      - c-ares=1.28.1=hd590300_0\n      - ca-certificates=2024.2.2=hbcca054_0\n      - cairo=1.18.0=h3faef2a_0\n      - certifi=2024.2.2=pyhd8ed1ab_0\n      - cffi=1.16.0=py310h2fee648_0\n      - charset-normalizer=3.3.2=pyhd8ed1ab_0\n      - colorama=0.4.6=pyhd8ed1ab_0\n      - comm=0.2.2=pyhd8ed1ab_0\n      - conda=24.3.0=py310hff52083_0\n      - conda-libmamba-solver=24.1.0=pyhd8ed1ab_0\n      - conda-package-handling=2.2.0=pyh38be061_0\n      - conda-package-streaming=0.9.0=pyhd8ed1ab_0\n      - contourpy=1.2.1=py310hd41b1e2_0\n      - cycler=0.12.1=pyhd8ed1ab_0\n      - dbus=1.13.6=h5008d03_3\n      - debugpy=1.8.1=py310hc6cd4ac_0\n      - decorator=5.1.1=pyhd8ed1ab_0\n      - distro=1.9.0=pyhd8ed1ab_0\n      - exceptiongroup=1.2.0=pyhd8ed1ab_2\n      - executing=2.0.1=pyhd8ed1ab_0\n      - expat=2.6.2=h59595ed_0\n      - filelock=3.13.4=pyhd8ed1ab_0\n      - fmt=10.2.1=h00ab1b0_0\n      - font-ttf-dejavu-sans-mono=2.37=hab24e00_0\n      - font-ttf-inconsolata=3.000=h77eed37_0\n      - font-ttf-source-code-pro=2.038=h77eed37_0\n      - font-ttf-ubuntu=0.83=h77eed37_1\n      - fontconfig=2.14.2=h14ed4e7_0\n      - fonts-conda-ecosystem=1=0\n      - fonts-conda-forge=1=0\n      - fonttools=4.51.0=py310h2372a71_0\n      - freetype=2.12.1=h267a509_2\n      - gettext=0.22.5=h59595ed_2\n      - gettext-tools=0.22.5=h59595ed_2\n      - glib=2.80.0=hf2295e7_5\n      - glib-tools=2.80.0=hde27a5a_5\n      - gmp=6.3.0=h59595ed_1\n      - gmpy2=2.1.2=py310h3ec546c_1\n      - graphite2=1.3.13=h59595ed_1003\n      - gst-plugins-base=1.24.1=hfa15dee_1\n      - gstreamer=1.24.1=h98fc4e7_1\n      - harfbuzz=8.3.0=h3d44ed6_0\n      - icu=73.2=h59595ed_0\n      - idna=3.7=pyhd8ed1ab_0\n      - importlib-metadata=7.1.0=pyha770c72_0\n      - importlib_metadata=7.1.0=hd8ed1ab_0\n      - ipykernel=6.29.3=pyhd33586a_0\n      - ipython=8.22.2=pyh707e725_0\n      - jedi=0.19.1=pyhd8ed1ab_0\n      - jinja2=3.1.3=pyhd8ed1ab_0\n      - jsonpatch=1.33=pyhd8ed1ab_0\n      - jsonpointer=2.4=py310hff52083_3\n      - jupyter_client=8.6.1=pyhd8ed1ab_0\n      - jupyter_core=5.7.2=py310hff52083_0\n      - keyutils=1.6.1=h166bdaf_0\n      - kiwisolver=1.4.5=py310hd41b1e2_1\n      - krb5=1.21.2=h659d440_0\n      - lame=3.100=h166bdaf_1003\n      - lcms2=2.16=hb7c19ff_0\n      - ld_impl_linux-64=2.40=h41732ed_0\n      - lerc=4.0.0=h27087fc_0\n      - libabseil=20230802.1=cxx17_h59595ed_0\n      - libarchive=3.7.2=h2aa1ff5_1\n      - libasprintf=0.22.5=h661eb56_2\n      - libasprintf-devel=0.22.5=h661eb56_2\n      - libblas=3.9.0=22_linux64_openblas\n      - libbrotlicommon=1.1.0=hd590300_1\n      - libbrotlidec=1.1.0=hd590300_1\n      - libbrotlienc=1.1.0=hd590300_1\n      - libcap=2.69=h0f662aa_0\n      - libcblas=3.9.0=22_linux64_openblas\n      - libclang-cpp15=15.0.7=default_h127d8a8_5\n      - libclang13=18.1.3=default_h5d6823c_0\n      - libcups=2.3.3=h4637d8d_4\n      - libcurl=8.7.1=hca28451_0\n      - libdeflate=1.20=hd590300_0\n      - libedit=3.1.20191231=he28a2e2_2\n      - libev=4.33=hd590300_2\n      - libevent=2.1.12=hf998b51_1\n      - libexpat=2.6.2=h59595ed_0\n      - libffi=3.4.2=h7f98852_5\n      - libflac=1.4.3=h59595ed_0\n      - libgcc-ng=13.2.0=h807b86a_5\n      - libgcrypt=1.10.3=hd590300_0\n      - libgettextpo=0.22.5=h59595ed_2\n      - libgettextpo-devel=0.22.5=h59595ed_2\n      - libgfortran-ng=13.2.0=h69a702a_5\n      - libgfortran5=13.2.0=ha4646dd_5\n      - libglib=2.80.0=hf2295e7_5\n      - libgomp=13.2.0=h807b86a_5\n      - libgpg-error=1.48=h71f35ed_0\n      - libiconv=1.17=hd590300_2\n      - libjpeg-turbo=3.0.0=hd590300_1\n      - liblapack=3.9.0=22_linux64_openblas\n      - libllvm15=15.0.7=hb3ce162_4\n      - libllvm18=18.1.3=h2448989_0\n      - libmamba=1.5.8=had39da4_0\n      - libmambapy=1.5.8=py310h39ff949_0\n      - libnghttp2=1.58.0=h47da74e_1\n      - libnsl=2.0.1=hd590300_0\n      - libogg=1.3.4=h7f98852_1\n      - libopenblas=0.3.27=pthreads_h413a1c8_0\n      - libopus=1.3.1=h7f98852_1\n      - libpng=1.6.43=h2797004_0\n      - libpq=16.2=h33b98f1_1\n      - libprotobuf=4.25.1=hf27288f_2\n      - libsndfile=1.2.2=hc60ed4a_1\n      - libsodium=1.0.18=h36c2ea0_1\n      - libsolv=0.7.28=hfc55251_2\n      - libsqlite=3.45.2=h2797004_0\n      - libssh2=1.11.0=h0841786_0\n      - libstdcxx-ng=13.2.0=h7e041cc_5\n      - libsystemd0=255=h3516f8a_1\n      - libtiff=4.6.0=h1dd3fc0_3\n      - libtorch=2.1.2=cpu_generic_ha017de0_3\n      - libuuid=2.38.1=h0b41bf4_0\n      - libuv=1.48.0=hd590300_0\n      - libvorbis=1.3.7=h9c3ff4c_0\n      - libwebp-base=1.4.0=hd590300_0\n      - libxcb=1.15=h0b41bf4_0\n      - libxcrypt=4.4.36=hd590300_1\n      - libxkbcommon=1.7.0=h662e7e4_0\n      - libxml2=2.12.6=h232c23b_2\n      - libzlib=1.2.13=hd590300_5\n      - lightning=2.2.2=pyhd8ed1ab_0\n      - lightning-utilities=0.11.2=pyhd8ed1ab_0\n      - lz4-c=1.9.4=hcb278e6_0\n      - lzo=2.10=h516909a_1000\n      - mamba=1.5.8=py310h51d5547_0\n      - markupsafe=2.1.5=py310h2372a71_0\n      - matplotlib=3.8.4=py310hff52083_0\n      - matplotlib-base=3.8.4=py310h62c0568_0\n      - matplotlib-inline=0.1.7=pyhd8ed1ab_0\n      - menuinst=2.0.2=py310hff52083_0\n      - mpc=1.3.1=hfe3b2da_0\n      - mpfr=4.2.1=h9458935_1\n      - mpg123=1.32.6=h59595ed_0\n      - mpmath=1.3.0=pyhd8ed1ab_0\n      - munkres=1.1.4=pyh9f0ad1d_0\n      - mysql-common=8.3.0=hf1915f5_4\n      - mysql-libs=8.3.0=hca2cd23_4\n      - ncurses=6.4.20240210=h59595ed_0\n      - nest-asyncio=1.6.0=pyhd8ed1ab_0\n      - networkx=3.3=pyhd8ed1ab_1\n      - nomkl=1.0=h5ca1d4c_0\n      - nspr=4.35=h27087fc_0\n      - nss=3.98=h1d7d5a4_0\n      - numpy=1.26.4=py310hb13e2d6_0\n      - openjpeg=2.5.2=h488ebb8_0\n      - openssl=3.2.1=hd590300_1\n      - packaging=24.0=pyhd8ed1ab_0\n      - pandas=2.2.2=py310hcc13569_0\n      - parso=0.8.4=pyhd8ed1ab_0\n      - patsy=0.5.6=pyhd8ed1ab_0\n      - pcre2=10.43=hcad00b1_0\n      - pexpect=4.9.0=pyhd8ed1ab_0\n      - pickleshare=0.7.5=py_1003\n      - pillow=10.3.0=py310hf73ecf8_0\n      - pip=24.0=pyhd8ed1ab_0\n      - pixman=0.43.2=h59595ed_0\n      - platformdirs=4.2.0=pyhd8ed1ab_0\n      - pluggy=1.4.0=pyhd8ed1ab_0\n      - ply=3.11=pyhd8ed1ab_2\n      - prompt-toolkit=3.0.42=pyha770c72_0\n      - psutil=5.9.8=py310h2372a71_0\n      - pthread-stubs=0.4=h36c2ea0_1001\n      - ptyprocess=0.7.0=pyhd3deb0d_0\n      - pulseaudio-client=17.0=hb77b528_0\n      - pure_eval=0.2.2=pyhd8ed1ab_0\n      - pybind11-abi=4=hd8ed1ab_3\n      - pycosat=0.6.6=py310h2372a71_0\n      - pycparser=2.22=pyhd8ed1ab_0\n      - pygments=2.17.2=pyhd8ed1ab_0\n      - pyparsing=3.1.2=pyhd8ed1ab_0\n      - pyqt=5.15.9=py310h04931ad_5\n      - pyqt5-sip=12.12.2=py310hc6cd4ac_5\n      - pysocks=1.7.1=pyha2e5f31_6\n      - python=3.10.14=hd12c33a_0_cpython\n      - python-dateutil=2.9.0=pyhd8ed1ab_0\n      - python-tzdata=2024.1=pyhd8ed1ab_0\n      - python_abi=3.10=4_cp310\n      - pytorch=2.1.2=cpu_generic_py310h5d8fa8e_3\n      - pytorch-lightning=2.2.2=pyhd8ed1ab_0\n      - pytz=2024.1=pyhd8ed1ab_0\n      - pyyaml=6.0.1=py310h2372a71_1\n      - pyzmq=26.0.0=py310h795f18f_0\n      - qt-main=5.15.8=hc9dc06e_21\n      - readline=8.2=h8228510_1\n      - reproc=14.2.4.post0=hd590300_1\n      - reproc-cpp=14.2.4.post0=h59595ed_1\n      - requests=2.31.0=pyhd8ed1ab_0\n      - ruamel.yaml=0.18.6=py310h2372a71_0\n      - ruamel.yaml.clib=0.2.8=py310h2372a71_0\n      - scipy=1.13.0=py310hb13e2d6_0\n      - seaborn=0.13.2=hd8ed1ab_0\n      - seaborn-base=0.13.2=pyhd8ed1ab_0\n      - setuptools=69.5.1=pyhd8ed1ab_0\n      - sip=6.7.12=py310hc6cd4ac_0\n      - six=1.16.0=pyh6c4a22f_0\n      - sleef=3.5.1=h9b69904_2\n      - stack_data=0.6.2=pyhd8ed1ab_0\n      - statsmodels=0.14.1=py310h1f7b6fc_0\n      - sympy=1.12=pypyh9d50eac_103\n      - tk=8.6.13=noxft_h4845f30_101\n      - toml=0.10.2=pyhd8ed1ab_0\n      - tomli=2.0.1=pyhd8ed1ab_0\n      - torchmetrics=1.3.2=pyhd8ed1ab_0\n      - tornado=6.4=py310h2372a71_0\n      - tqdm=4.66.2=pyhd8ed1ab_0\n      - traitlets=5.14.2=pyhd8ed1ab_0\n      - truststore=0.8.0=pyhd8ed1ab_0\n      - typing-extensions=4.11.0=hd8ed1ab_0\n      - typing_extensions=4.11.0=pyha770c72_0\n      - tzdata=2024a=h0c530f3_0\n      - unicodedata2=15.1.0=py310h2372a71_0\n      - urllib3=2.2.1=pyhd8ed1ab_0\n      - wcwidth=0.2.13=pyhd8ed1ab_0\n      - wheel=0.43.0=pyhd8ed1ab_1\n      - xcb-util=0.4.0=hd590300_1\n      - xcb-util-image=0.4.0=h8ee46fc_1\n      - xcb-util-keysyms=0.4.0=h8ee46fc_1\n      - xcb-util-renderutil=0.3.9=hd590300_1\n      - xcb-util-wm=0.4.1=h8ee46fc_1\n      - xkeyboard-config=2.41=hd590300_0\n      - xorg-kbproto=1.0.7=h7f98852_1002\n      - xorg-libice=1.1.1=hd590300_0\n      - xorg-libsm=1.2.4=h7391055_0\n      - xorg-libx11=1.8.9=h8ee46fc_0\n      - xorg-libxau=1.0.11=hd590300_0\n      - xorg-libxdmcp=1.1.3=h7f98852_0\n      - xorg-libxext=1.3.4=h0b41bf4_2\n      - xorg-libxrender=0.9.11=hd590300_0\n      - xorg-renderproto=0.11.1=h7f98852_1002\n      - xorg-xextproto=7.3.0=h0b41bf4_1003\n      - xorg-xf86vidmodeproto=2.3.1=h7f98852_1002\n      - xorg-xproto=7.0.31=h7f98852_1007\n      - xz=5.2.6=h166bdaf_0\n      - yaml=0.2.5=h7f98852_2\n      - yaml-cpp=0.8.0=h59595ed_0\n      - zeromq=4.3.5=h59595ed_1\n      - zipp=3.17.0=pyhd8ed1ab_0\n      - zlib=1.2.13=hd590300_5\n      - zstandard=0.22.0=py310h1275a96_0\n      - zstd=1.5.5=hfc55251_0\n      - pip:\n          - aiobotocore==2.12.3\n          - aiohttp==3.9.5\n          - aioitertools==0.11.0\n          - aiosignal==1.3.1\n          - annotated-types==0.6.0\n          - antlr4-python3-runtime==4.9.3\n          - anyio==4.3.0\n          - arrow==1.3.0\n          - async-timeout==4.0.3\n          - attrs==23.2.0\n          - backoff==2.2.1\n          - beautifulsoup4==4.12.3\n          - bitsandbytes==0.41.0\n          - blessed==1.20.0\n          - boto3==1.34.69\n          - botocore==1.34.69\n          - click==8.1.7\n          - croniter==1.4.1\n          - dateutils==0.6.12\n          - deepdiff==6.7.1\n          - docker==6.1.3\n          - docstring-parser==0.16\n          - editor==1.6.6\n          - fastapi==0.110.1\n          - frozenlist==1.4.1\n          - fsspec==2023.12.2\n          - h11==0.14.0\n          - hydra-core==1.3.2\n          - importlib-resources==6.4.0\n          - inquirer==3.2.4\n          - jmespath==1.0.1\n          - jsonargparse==4.28.0\n          - lightning-api-access==0.0.5\n          - lightning-cloud==0.5.65\n          - lightning-fabric==2.2.2\n          - markdown-it-py==3.0.0\n          - mdurl==0.1.2\n          - multidict==6.0.5\n          - nvidia-cublas-cu12==12.1.3.1\n          - nvidia-cuda-cupti-cu12==12.1.105\n          - nvidia-cuda-nvrtc-cu12==12.1.105\n          - nvidia-cuda-runtime-cu12==12.1.105\n          - nvidia-cudnn-cu12==8.9.2.26\n          - nvidia-cufft-cu12==11.0.2.54\n          - nvidia-curand-cu12==10.3.2.106\n          - nvidia-cusolver-cu12==11.4.5.107\n          - nvidia-cusparse-cu12==12.1.0.106\n          - nvidia-nccl-cu12==2.19.3\n          - nvidia-nvjitlink-cu12==12.4.127\n          - nvidia-nvtx-cu12==12.1.105\n          - omegaconf==2.3.0\n          - ordered-set==4.1.0\n          - protobuf==5.26.1\n          - pydantic==2.7.0\n          - pydantic-core==2.18.1\n          - pyjwt==2.8.0\n          - python-multipart==0.0.9\n          - readchar==4.0.6\n          - redis==5.0.3\n          - rich==13.7.1\n          - runs==1.2.2\n          - s3fs==2023.12.2\n          - s3transfer==0.10.1\n          - sniffio==1.3.1\n          - soupsieve==2.5\n          - starlette==0.37.2\n          - tensorboardx==2.6.2.2\n          - torch==2.2.2\n          - triton==2.2.0\n          - types-python-dateutil==2.9.0.20240316\n          - typeshed-client==2.5.1\n          - uvicorn==0.29.0\n          - websocket-client==1.7.0\n          - websockets==11.0.3\n          - wrapt==1.16.0\n          - xmod==1.8.1\n          - yarl==1.9.4\n    prefix: /home/sagemaker-user/.conda/envs/mamba_gpu\n    \n\nA selfmade cuda program which I compiled with nvcc works perfectly and using pytorch without lightning also works.\n\nHow can I get lightning to run?",
  "label": "r/pytorch",
  "dataType": "post",
  "communityName": "r/pytorch",
  "datetime": "2024-04-17",
  "username_encoded": "Z0FBQUFBQm5LakwxaTZpdGxVdXdjcXpoOU9oSW9UOEkxdTJydzNKclU5SktXbVhMY19SS0o4dHk4blR4VmlpX1c5Zk5pNVM4elJRcFBzdlZUWkdnbHlZR1UxUldwM2k3WlE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9GTm95dVNJZWR5bThyRHZmTE41ZzEwNnpfdjFhYVdtTVNNYkFzYzZ5bm9QQUFLSGplQ1E0MnRrc1Jvc2I2anNWeGhvM0R0R2VEYTdoOVNqR3kydDdWRTg5Yl9kOUlNTDNOWjdZSkt0R05GcUx5ZTV0NDRrR2szVmZNMGlKQTUxR1F5ZGRSa0xHVHdNUUZUS2VUNF9pSnVJYzVmYl91LWdUTXU1YW1GVnBFUGx5dEJlaTROUl9QbnZiTFlkcER3T0ct"
}

Entry Information

• Entry ID: 4574
• Repository: Axioma AXP
• Dataset: arrmlet/reddit_dataset_36
• Total Entries: 100,000