Transformers4Rec: [BUG] Conda install takes...forever?

Bug description

Ran conda install -c nvidia -c conda-forge transformers4rec on an Ubuntu 20.04 machine. The install runs for an unreasonable amount of time, I haven’t seen it end yet. I will try to let a run go on as long as possible to see if it ever ends. I’ve also tried targeting specific versions e.g. transformers4rec=0.1.4 and the same issue occurs.

Steps/Code to reproduce bug

Create conda environment on Ubuntu 20.04 machine
Run conda install -c nvidia -c conda-forge transformers4rec
Notice the install runs for a very long time.

Expected behavior

Install to take less than a few minutes, and for transformers4rec to be available to start using in the conda environment.

Environment details

Transformers4Rec version: 0.1.4 (attempted)
Platform: Ubuntu 20.04
Python version: 3.8
Huggingface Transformers version: X
PyTorch version (GPU?): X
Tensorflow version (GPU?): X

Additional context

At the start of the install I also see:

Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.

Then Solving environment: - for a long time.

About this issue

Original URL
State: closed
Created 2 years ago
Comments: 39 (39 by maintainers)

Most upvoted comments

conda create -y -n rapids -c rapidsai -c nvidia -c conda-forge rapids=22.06 python=3.8 cudatoolkit=11.2

@masoncusack I think you would not need this step since you are installing cudf and dask_cudf via pip. so you can create a conda env but not install rapids via conda. and install cudf via pip.

rnyak on Jan 30, 2023

Oof, surprised that requirement isn’t included. In the rest of Merlin, we require tensorflow-metadata>=1.2.0.

karlhigley on Jan 24, 2023

@masoncusack If that error about writing the output to disk is repeatable and persists, that sounds like a potential directory permissions issue.

karlhigley on Jan 24, 2023

Having the same issue running the Merlin models getting started notebook also.

@masoncusack You are not installing torch for Merlin Models right? There you only need TF for Merlin models not torch. You can installl TF 2.9.1 version. what problem you are getting there? cupy issue again? do you mind to create a ticket for that in Merlin Model GH repo as well? thanks!

rnyak on Jan 23, 2023

I’d recommend you to look at this page for systems requirements: https://rapids.ai/start.html

rnyak on Jan 17, 2023

Hm, actually I can’t right now due to quota issues, but that would be the thing to do.

masoncusack on Dec 23, 2022

Hello @masoncusack,

thanks for sharing. We will work on it to provide better installation instructions.

Currently, I can provide you some “workarounds” (for GPU support):

Installing Conda in two steps: I think the main issue in freezing the installation is to resolve dependencies of RAPIDs and Transformer4Rec. We use RAPIDs cuDF and dask_cudf. I was able to install Transformer4Rec by installing RAPIDs, first and then Transformer4Rec.

conda create -y -n rapids -c rapidsai -c nvidia -c conda-forge rapids=22.06 python=3.8 cudatoolkit=11.2
### Activate the environment
conda install -c nvidia -c conda-forge transformers4rec[pytorch,nvtabular]

Transformer4Rec (and NVTabular) are based on cuDF/RAPIDS 22.06 release. You need to have the CUDA and supporting CUDA libraries installed. You can install the libraries via gitclone and pip inside the conda environment. This is often faster than resolving and installing dependencies

conda create -y -n rapids -c rapidsai -c nvidia -c conda-forge rapids=22.06 python=3.8 cudatoolkit=11.2
### Activate the environment
git clone https://github.com/NVIDIA-Merlin/Transformers4Rec.git && cd Transformers4Rec && pip install . && cd ..
git clone https://github.com/NVIDIA-Merlin/NVTabular.git && cd NVTabular && pip install . && cd ..
git clone https://github.com/NVIDIA-Merlin/dataloader.git && cd dataloader && pip install . && cd ..
git clone https://github.com/NVIDIA-Merlin/core.git && cd core && pip install . && cd ..

Do you use a specific docker container that I can reproduce the installation end-to-end?

bschifferer on Dec 14, 2022