< using nvtabular==1.3.0, higher version returns [ModuleNotFoundError: No module named 'merlin.dag.executors'] >
Version mismatch: this is the 'cffi' package version 1.15.1, located in '/usr/local/lib/python3.7/dist-packages/cffi/api.py'. When we import the top-level '_cffi_backend' extension module, we get version 1.15.0, located in '/usr/local/lib/python3.7/site-packages/_cffi_backend.cpython-37m-x86_64-linux-gnu.so'. The two versions should be equal; check your installation.
desc: colab nvtabular, cffi error fix
< using nvtabular==1.3.0, higher version returns [ModuleNotFoundError: No module named 'merlin.dag.executors'] >
Version mismatch: this is the 'cffi' package version 1.15.1, located in '/usr/local/lib/python3.7/dist-packages/cffi/api.py'. When we import the top-level '_cffi_backend' extension module, we get version 1.15.0, located in '/usr/local/lib/python3.7/site-packages/_cffi_backend.cpython-37m-x86_64-linux-gnu.so'. The two versions should be equal; check your installation.
detail Install process
cell-1
!git clone https://github.com/rapidsai/rapidsai-csp-utils.git !python rapidsai-csp-utils/colab/env-check.py
!bash rapidsai-csp-utils/colab/update_gcc.sh -qq import os os._exit(00)
cell-2
!pip install -q condacolab import condacolab condacolab.install()
cell-3
!python rapidsai-csp-utils/colab/install_rapids.py stable
import os os.environ['NUMBAPRO_NVVM'] = '/usr/local/cuda/nvvm/lib64/libnvvm.so' os.environ['NUMBAPRO_LIBDEVICE'] = '/usr/local/cuda/nvvm/libdevice/' os.environ['CONDA_PREFIX'] = '/usr/local'
cell-4
!pip install -qqq transformers4rec[pytorch,nvtabular] !conda install -c nvidia -c rapidsai -c numba -c conda-forge nvtabular -y
After fixing cffi version, the nvtabular workflow works