Merge remote-tracking branch 'origin/fix_leftovers'

Author: paren8esis

README.md

@@ -10,9 +10,9 @@
 
 This repository was tested on:
 * Python 3.8
-* CUDA 11.2
-* PyTorch 1.8.1
-* PyTorch Lightning 1.2.1
+* CUDA 11.4
+* PyTorch 1.11
+* PyTorch Lightning 1.6
 
 Check `requirements.txt` for other essential modules.
 

compute_class_weights.py

@@ -5,7 +5,7 @@
 
 from pycocotools.coco import COCO
 
-from utils.patches_datamodule import PatchesDataModule
+from utils.PAD_datamodule import PADDataModule
 from utils.settings.config import CROP_ENCODING, LINEAR_ENCODER
 
 
@@ -43,7 +43,7 @@
         class_pixel_counts = pickle.load(open(pixel_cnts_name, 'rb'))
     else:
         # Create Data Module
-        dm = PatchesDataModule(
+        dm = PADDataModule(
             root_path_coco=root_path_coco,
             path_train=coco_train,
             path_val=coco_val,

pad_experiments.py

@@ -5,7 +5,7 @@
 In order to be used as model inputs, the training data are further split into
 sequences using a rolling window of a fixed size.
 '''
-import argparsse
+import argparse
 from pathlib import Path
 from datetime import datetime
 
@@ -18,12 +18,11 @@
 from pytorch_lightning import loggers as pl_loggers
 from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint, LearningRateMonitor
 from pytorch_lightning.plugins import DDPPlugin
-from pytorch_lightning.plugins.precision.native_amp import NativeMixedPrecisionPlugin
 import torch
 
 from utils.PAD_datamodule import PADDataModule
 from utils.tools import font_colors
-from utils.settings.config import RANDOM_SEED, CROP_ENCODING, LINEAR_ENCODER, CLASS_WEIGHTS
+from utils.settings.config import RANDOM_SEED, CROP_ENCODING, LINEAR_ENCODER, CLASS_WEIGHTS, BANDS
 
 # Set seed for everything
 pl.seed_everything(RANDOM_SEED)
@@ -385,7 +384,7 @@ def main():
 
     if args.train:
         # Create Data Modules
-        dm = PatchesDataModule(
+        dm = PADDataModule(
             root_path_coco=root_path_coco,
             path_train=path_train,
             path_val=path_val,
@@ -421,15 +420,13 @@ def main():
                 dirpath=run_path / 'checkpoints',
                 monitor=monitor,
                 mode='min',
-                period=1,
                 save_top_k=-1
             )
         )
 
         tb_logger = pl_loggers.TensorBoardLogger(run_path / 'tensorboard')
 
         my_ddp = DDPPlugin(find_unused_parameters=True)
-        mixed_precision = NativeMixedPrecisionPlugin()
 
         trainer = pl.Trainer(gpus=args.num_gpus,
                              num_nodes=args.num_nodes,
@@ -445,16 +442,15 @@ def main():
                              checkpoint_callback=True,
                              resume_from_checkpoint=resume_from_checkpoint,
                              fast_dev_run=args.devtest,
-                             distributed_backend='ddp' if args.num_gpus > 1 else None,
-                             plugins=[my_ddp, mixed_precision],
-                             deterministic=True
+                             strategy='ddp' if args.num_gpus > 1 else None,
+                             plugins=[my_ddp]
                              )
 
         # Train model
         trainer.fit(model, datamodule=dm)
     else:
         # Create Data Module
-        dm = PatchesDataModule(
+        dm = PADDataModule(
             root_path_coco=root_path_coco,
             path_test=path_test,
             group_freq=args.group_freq,
@@ -488,9 +484,8 @@ def main():
                              min_epochs=1,
                              max_epochs=2,
                              precision=32,
-                             distributed_backend='ddp' if args.num_gpus > 1 else None,
-                             plugins=[my_ddp],
-                             deterministic=True
+                             strategy='ddp' if args.num_gpus > 1 else None,
+                             plugins=[my_ddp]
                              )
 
         # Test model

requirements.txt

@@ -9,7 +9,7 @@ pandas==1.3.3
 Pillow==8.3.2
 pyarrow==5.0.0
 pycocotools==2.0.2
-pytorch-lightning==1.2.1
+pytorch-lightning==1.6.1
 scikit-learn==0.24.2
 scikit-multilearn=0.2.0
 seaborn==0.11.2
@@ -23,10 +23,10 @@ tensorboard-data-server==0.6.1
 tensorboard-plugin-wit==1.8.0
 tensorboardX==2.4
 timm==0.4.12
-torch==1.8.1+cu111
+torch==1.11.0+cu113
 torchlars==0.1.2
-torchmetrics==0.5.1
-torchvision==0.9.1+cu111
+torchmetrics==0.7.3
+torchvision==0.12.0+cu113
 tqdm==4.62.3
 transformers==4.6.1
 xarray==0.19.0

visualize_predictions.py

@@ -6,10 +6,10 @@
 from mpl_toolkits.axes_grid1 import ImageGrid
 from pycocotools.coco import COCO
 
-from model.convLSTM_lightning import ConvLSTM
-from model.tempCNN_lightning import TempCNN
-from model.convSTAR_lightning import ConvSTAR
-from model.unet_lightning import UNet
+from model.PAD_convLSTM import ConvLSTM
+from model.PAD_tempCNN import TempCNN
+from model.PAD_convSTAR import ConvSTAR
+from model.PAD_unet import UNet
 
 import pytorch_lightning as pl
 import torch