Adding certain pip and/or conda packages removes pre-installed packages #1051
Description
Version
0.16, master
Steps to reproduce
1. deploy a gpu cluster (SSHing into a GPU machine and running locally should work too)
2. modify examples/pytorch/iris-classifier as follows:
update requirements.txt to be:
torch scikit-learn asciitree==0.3.3 gin-config==0.3.0 requests==2.23.0 tensorboard==2.2.1 tqdm==4.30.0 OpenNMT-py==1.1.1 create conda-packages.txt:
conda-forge::boto3=1.12.39=pyh9f0ad1d_0 chembl::chembl_structure_pipeline=1.0.0=py38_0 cudatoolkit=10.1.243=h6bb024c_0 cudnn=7.6.5=cuda10.1_0 conda-forge::matplotlib=3.1.3=py37_0 conda-forge::networkx=2.4=py_1 conda-forge::numpy=1.18.1=py37h8960a57_1 conda-forge::pandas=1.0.3=py37h0da4684_1 conda-forge::pathos=0.2.5=py_0 defaults::python=3.7.7=hcf32534_0_cpython pytorch::pytorch=1.5.0=py3.7_cuda10.1.243_cudnn7.6.3_0 conda-forge::rdkit=2020.03.1=py37hdd87690_3 conda-forge::scipy=1.4.1=py37ha3d9a3c_3 update cortex.yaml to be:
- name: iris-classifier predictor: type: python path: predictor.py image: cortexlabs/python-predictor-gpu-slim:master config: model: s3://cortex-examples/pytorch/iris-classifier/weights.pth monitoring: model_type: classification compute: cpu: 3 gpu: 1 mem: 15Gif you are running off the 0.16 branch, replace image: cortexlabs/python-predictor-gpu-slim:master with image: cortexlabs/python-predictor-gpu-slim:0.16.0
-
cortex deploy -
cortex logs iris-classifierwill show this error:
ModuleNotFoundError: No module named 'uvicorn' Additional context
It seems that all of the pre-installed cortex packages are removed or not able to be found. When appending the cortex-required packages to the requirements.txt above, the API works:
torch scikit-learn asciitree==0.3.3 gin-config==0.3.0 requests==2.23.0 tensorboard==2.2.1 tqdm==4.30.0 OpenNMT-py==1.1.1 boto3==1.12.31 datadog==0.35.0 dill==0.3.1.1 fastapi==0.53.0 msgpack==1.0.0 numpy==1.18.2 pyyaml==5.3.1 requests==2.23.0 uvicorn==0.11.3