linting

notebooks/camera_ready/corrupt_data/pretrain.py

@@ -6,9 +6,9 @@
 
 import lightning.pytorch as pl
 import torch
+import wandb
 from lightning.fabric.strategies import XLAFSDPStrategy
 
-import wandb
 from sdofm import utils
 from sdofm.datasets import (BrightSpotsSDOMLDataModule,
                             HelioProjectedSDOMLDataModule, SDOMLDataModule)

notebooks/camera_ready/instrument_degrad/pretrain.py

@@ -6,9 +6,9 @@
 
 import lightning.pytorch as pl
 import torch
+import wandb
 from lightning.fabric.strategies import XLAFSDPStrategy
 
-import wandb
 from sdofm import utils
 from sdofm.datasets import (BrightSpotsSDOMLDataModule,
                             HelioProjectedSDOMLDataModule, SDOMLDataModule)

notebooks/camera_ready/virtual_eve/pretrain.py

@@ -6,9 +6,9 @@
 
 import lightning.pytorch as pl
 import torch
+import wandb
 from lightning.fabric.strategies import XLAFSDPStrategy
 
-import wandb
 from sdofm import utils
 from sdofm.datasets import (BrightSpotsSDOMLDataModule,
                             HelioProjectedSDOMLDataModule, SDOMLDataModule)

scripts/ablation.py

@@ -5,8 +5,8 @@
 
 import lightning.pytorch as pl
 import torch
-
 import wandb
+
 from sdofm import utils
 from sdofm.ablation import AblationAutocalibration
 from sdofm.datasets import DegradedSDOMLDataModule, SDOMLDataModule

scripts/finetune.py

@@ -5,8 +5,8 @@
 
 import lightning.pytorch as pl
 import torch
-
 import wandb
+
 from sdofm import utils
 from sdofm.datasets import DegradedSDOMLDataModule, SDOMLDataModule
 from sdofm.finetuning import Autocalibration, VirtualEVE

scripts/main.py

@@ -12,11 +12,11 @@
 import hydra
 import numpy as np
 import torch
+import wandb
 from lightning.pytorch import seed_everything
 from lightning.pytorch.loggers.wandb import WandbLogger
 from omegaconf import DictConfig, OmegaConf
 
-import wandb
 from sdofm import utils  # import days_hours_mins_secs_str
 from sdofm.utils import flatten_dict
 

scripts/main_tf.py

@@ -11,11 +11,11 @@
 import hydra
 import numpy as np
 import tensorflow as tf
+import wandb
 # from lightning.pytorch import seed_everything
 # from lightning.pytorch.loggers.wandb import WandbLogger
 from omegaconf import DictConfig, OmegaConf
 
-import wandb
 from sdofm import utils  # import days_hours_mins_secs_str
 from sdofm.utils import flatten_dict
 

scripts/pretrain.py

@@ -6,9 +6,9 @@
 
 import lightning.pytorch as pl
 import torch
+import wandb
 from lightning.fabric.strategies import XLAFSDPStrategy
 
-import wandb
 from sdofm import utils
 from sdofm.datasets import (BrightSpotsSDOMLDataModule,
                             HelioProjectedSDOMLDataModule,

sdofm/models/wrap_encoder.py

@@ -7,13 +7,12 @@
 import segmentation_models_pytorch as smp
 import torch
 import torch.nn as nn
+import wandb
 from einops import rearrange
 from omegaconf import DictConfig, OmegaConf
 from segmentation_models_pytorch import Unet
 from segmentation_models_pytorch.decoders.unet.decoder import UnetDecoder
 
-import wandb
-
 from .. import utils
 from . import ConvTransformerTokensToEmbeddingNeck, MaskedAutoencoderViT3D
 

sdofm/pretraining/MAE.py

@@ -107,9 +107,8 @@ def on_validation_epoch_end(self):
         batch_metrics = bench_recon.mean_metrics(merged_metrics)
 
         if isinstance(self.logger, pl.loggers.wandb.WandbLogger):
-            from pandas import DataFrame
-
             import wandb
+            from pandas import DataFrame
 
             # this only occurs on rank zero only
             df = DataFrame(batch_metrics)

sdofm/utils.py

@@ -7,7 +7,6 @@
 
 import numpy as np
 import torch
-
 import wandb