setup_nvt_t4r_pytorch

# Start a SageMaker notebook instance (ml.p3.2xlarge) and open a terminal

# Upload the conda yml from here: https://gist.github.com/eugeneyan/3435e05dd675b9ee2af164214536752d

# Install NVTabular
conda env create -f=SageMaker/nvt_t4r.yml

# Activate conda env
source anaconda3/etc/profile.d/conda.sh
conda activate nvt_t4r

# Install pytorch with cuda enabled
conda install -y -c conda-forge pytorch-gpu

# Install the rest of the libraries
conda install -y -c nvidia -c rapidsai -c numba -c conda-forge transformers4rec
conda install -y tensorflow torchmetrics ipykernel

# Create jupyter kernel
python -m ipykernel install --user --name=nvt_t4r

# Start a notebook with the nvt_t4r kernel. You should be able to run the following fine.
import cudf
import cupy
import nvtabular as nvt
from merlin_standard_lib import Schema
from transformers4rec import torch as tr
from transformers4rec.torch.utils.examples_utils import fit_and_evaluate
from transformers4rec.torch.utils.data_utils import NVTabularDataLoader

import torch
torch.cuda.is_available()

# Try running the tutorial from here: https://github.com/NVIDIA-Merlin/Transformers4Rec/tree/main/examples/tutorial