update dependencies for installation

Author: marsggbo

Dockerfile

@@ -5,18 +5,18 @@
 # GPU-ready with Apex for mixed-precision support
 # https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
 # https://docs.nvidia.com/deeplearning/frameworks/support-matrix/
-FROM nvcr.io/nvidia/pytorch:21.03-py3
+FROM nvcr.io/nvidia/pytorch:22.07-py3
 
 
 # Copy all files
-ADD . /workspace/project
-WORKDIR /workspace/project
+ADD . /workspace/hyperbox
+WORKDIR /workspace/hyperbox
 
 
-# Create myenv
-RUN conda env create -f conda_env_gpu.yaml -n myenv
+# Create hyperbox
+RUN conda env create -f conda_env_gpu.yaml -n hyperbox
 RUN conda init bash
 
 
-# Set myenv to default virtual environment
-RUN echo "source activate myenv" >> ~/.bashrc
+# Set hyperbox to default virtual environment
+RUN echo "source activate hyperbox" >> ~/.bashrc

conda_env_gpu.yaml

@@ -1,4 +1,4 @@
-name: myenv
+name: hyperbox
 
 channels:
   - pytorch

hyperbox/run.py

@@ -1,14 +1,11 @@
 import os
 import sys
 
-import dotenv
 import hydra
-from ipdb import set_trace
 from omegaconf import DictConfig
 
 # load environment variables from `.env` file if it exists
 # recursively searches for `.env` in all folders starting from work dir
-dotenv.load_dotenv(override=True)
 
 
 @hydra.main(version_base="1.2", config_path="configs/", config_name="config.yaml")
@@ -33,6 +30,7 @@ def main(config: DictConfig):
 
     # Train model
     if config.ipdb_debug:
+        from ipdb import set_trace
         set_trace()
     return train(config)
 

requirements.txt

@@ -1,7 +1,7 @@
 # --------- pytorch --------- #
 torch>=1.8.1
 torchvision
-pytorch-lightning==1.5.8
+pytorch-lightning>=1.5.8
 torchmetrics>=0.3.2
 lightning-bolts>=0.3.3