Update Readme

.gitignore

@@ -130,3 +130,6 @@ dmypy.json
 
 # don't save logs
 logs/
+
+# don't save vscode settings
+.vscode/

README.md

@@ -10,19 +10,19 @@ This repo provides different pytorch implementation for training a deep learning
   pytorch-templates/
   │
   ├── train_simple.py : A single-GPU implementation
-  |
+  │
   ├── train_multi.py : A multi-GPU implementation
   │
   ├── train_pl.py : Pytorch-lightning implementation along with Tensorboard logging
   │
-  ├── train_pl.ipynb : Jupyter notebook for Pytorch-lightning implementation along with Tensorboard logging
-  │
   ├── pl_hydra/ - contains all the files pertaining to pytorch-lightning hydra implementation
-  │   └──data_loaders.py
-  |
-  └── utils/ - small utility functions
-      ├── util.py
-      └── ...
+  │   └──...
+  │
+  ├──  utils/ - small utility functions
+  │    ├── util.py
+  │    └── ...
+  │
+  └── requirements.txt : file to install python dependencies
   ```
 
 ## Single-GPU implementation
@@ -50,9 +50,61 @@ optional arguments:
   --momentum MOMENTUM   Momentum value in SGD.
   --gamma GAMMA         gamma value for MultiStepLR.
 ```
+
+```
+# Start training with default parameters: 
+python train_simple.py --run_name=test_single
+
+# You can either parameters through commandline, for e.g.:
+python train_simple.py -bs=64 -ep=2 --run_name=test_single
+
+# You can also set parameters run_simple.sh file and start the training as following:
+source train_simple.py
+```
+
 ## Multi-GPU implementation
+```
+# Training with default parameters and 2 GPU: 
+python -m torch.distributed.launch --nproc_per_node=2 --master_port=9995 train_multi.py --run_name=test_multi
+
+# You can also pass parameters through commandline (single GPU training), for e.g.:
+python -m torch.distributed.launch --nproc_per_node=1 --master_port=9995 train_multi.py -ep=5 --run_name=test_single
+
+# You can also set parameters in run_simple.sh file and start the training as following:
+source train_multi.py
+```
 
 ## Pytorch-lightning implementation
+```
+# Training with 1 GPU:
+python train_pl.py --epochs=5 --run_name=test_pl --gpus=1
+
+# Training with 2 GPUs:
+python train_pl.py --epochs=5 --run_name=test_pl --gpus=2
+```
+
+```
+# Running the Tensorboard:
+tensorboard --logdir ./logs/
+```
 
 ## Pytorch-lightning Hydra implementation
+[Tensorboard containing the runs comparing different architectures on CIFAR10](https://tensorboard.dev/experiment/JUrYiGdOQqC0iGNoWtdPlg/#scalars&run=densenet%2F2022-05-06_00-27-19%2Ftensorboard%2Fdensenet&runSelectionState=eyJkZW5zZW5ldC8yMDIyLTA1LTA2XzAwLTI3LTE5L3RlbnNvcmJvYXJkL2RlbnNlbmV0Ijp0cnVlLCJnb29nbGVuZXQvMjAyMi0wNS0wNl8wOC00OS01My90ZW5zb3Jib2FyZC9nb29nbGVuZXQiOnRydWUsInJlc25ldC8yMDIyLTA1LTA2XzEwLTM1LTM5L3RlbnNvcmJvYXJkL3Jlc25ldCI6dHJ1ZSwidmdnLzIwMjItMDUtMDVfMTUtNTYtMDAvdGVuc29yYm9hcmQvdmdnIjp0cnVlLCJ2aXQvMjAyMi0wNS0wNV8xNS0wMS01NS90ZW5zb3Jib2FyZC92aXQiOnRydWV9)
+
+
+## Quickstart
+```
+# clone project
+git clone https://https://github.com/garg-aayush/pytorch-pl-hydra-templates
+cd pytorch-pl-hydra-templates
+
+# create conda environment
+conda create -n pl_hydra python=3.8
+conda activate pl_hydra
+
+# install requirements
+pip install -r requirements.txt
+```
 
+## Feedback
+To give feedback or ask a question or for environment setup issues, you can use the [Github Discussions](https://https://github.com/garg-aayush/pytorch-pl-hydra-templates/discussions).

run_simple.sh

@@ -5,7 +5,6 @@ run_name='train_simple.py'
 logfile=./logs/train_simple.log
 train_script='train_simple.py'
 ngpus=1
-port=9994
 epochs=150
 epochs_per_test=1
 batch_size=128