[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

pipelines/precipitation_model/impa/src/eval/metrics/calc-metrics.py

@@ -9,6 +9,7 @@
 import numpy as np
 import pandas as pd
 import tqdm
+
 from pipelines.precipitation_model.impa.src.eval.metrics.metrics import metrics_dict
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_warning
 from pipelines.precipitation_model.impa.src.utils.hdf_utils import get_dataset_keys

pipelines/precipitation_model/impa/src/eval/update-real_time.py

@@ -6,8 +6,13 @@
 import boto3
 from botocore import UNSIGNED
 from botocore.config import Config
-from pipelines.precipitation_model.impa.src.data.process.build_dataframe import build_dataframe
-from pipelines.precipitation_model.impa.src.data.process.process_satellite import process_satellite
+
+from pipelines.precipitation_model.impa.src.data.process.build_dataframe import (
+ build_dataframe,
+)
+from pipelines.precipitation_model.impa.src.data.process.process_satellite import (
+ process_satellite,
+)
 from pipelines.precipitation_model.impa.src.eval.predict_real_time import predict
 
 BUCKET_NAME = "noaa-goes16"

pipelines/precipitation_model/impa/src/eval/update-real_time_.py

@@ -10,8 +10,13 @@
 from botocore import UNSIGNED
 from botocore.config import Config
 from joblib import Parallel, delayed
-from pipelines.precipitation_model.impa.src.data.process.build_dataframe import build_dataframe
-from pipelines.precipitation_model.impa.src.data.process.process_satellite import process_satellite
+
+from pipelines.precipitation_model.impa.src.data.process.build_dataframe import (
+ build_dataframe,
+)
+from pipelines.precipitation_model.impa.src.data.process.process_satellite import (
+ process_satellite,
+)
 from pipelines.precipitation_model.impa.src.eval.predict_real_time import predict
 
 # from itertools import product

pipelines/precipitation_model/impa/src/eval/viz/plot-real_time.py

@@ -10,6 +10,7 @@
 import numpy as np
 import pandas as pd
 import tqdm
+
 from pipelines.precipitation_model.impa.src.eval.metrics.metrics import metrics_dict
 from pipelines.precipitation_model.impa.src.utils.eval_utils import get_img
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_warning

pipelines/precipitation_model/impa/src/models/Evolution_Network/evolution_network.py

@@ -1,7 +1,13 @@
 # -*- coding: utf-8 -*-
 import torch
 import torch.nn as nn
-from pipelines.precipitation_model.impa.src.models.Evolution_Network.model_parts import DoubleConv, Down, OutConv, Up
+
+from pipelines.precipitation_model.impa.src.models.Evolution_Network.model_parts import (
+ DoubleConv,
+ Down,
+ OutConv,
+ Up,
+)
 
 
 class Evolution_Encoder_Decoder(nn.Module):

pipelines/precipitation_model/impa/src/models/Evolution_Network/lightning.py

@@ -1,7 +1,13 @@
 # -*- coding: utf-8 -*-
 import torch
-from pipelines.precipitation_model.impa.src.models.Evolution_Network.evolution_network import Evolution_Encoder_Decoder
-from pipelines.precipitation_model.impa.src.models.Evolution_Network.utils import make_grid, warp
+
+from pipelines.precipitation_model.impa.src.models.Evolution_Network.evolution_network import (
+ Evolution_Encoder_Decoder,
+)
+from pipelines.precipitation_model.impa.src.models.Evolution_Network.utils import (
+ make_grid,
+ warp,
+)
 from pipelines.precipitation_model.impa.src.models.lightning_module import LModule
 
 

pipelines/precipitation_model/impa/src/models/Metnet3/lightning.py

@@ -3,6 +3,8 @@
 
 import torch
 import torch.nn as nn
+from torch.nn import Sequential
+
 from pipelines.precipitation_model.impa.src.models.lightning_module import LModule
 from pipelines.precipitation_model.impa.src.models.Metnet3.Max_Vit.Max_Vit import MaxViT
 from pipelines.precipitation_model.impa.src.models.Metnet3.metnet3_pytorch import (
@@ -12,7 +14,6 @@
  ResnetBlocks,
  Upsample2x,
 )
-from torch.nn import Sequential
 
 
 class model(LModule):

pipelines/precipitation_model/impa/src/models/NowcastNet/lightning.py

@@ -1,6 +1,10 @@
 # -*- coding: utf-8 -*-
 import torch
-from pipelines.precipitation_model.impa.src.models.gan.gan_unet.model import NowcasnetGenerator, TemporalDiscriminator
+
+from pipelines.precipitation_model.impa.src.models.gan.gan_unet.model import (
+ NowcasnetGenerator,
+ TemporalDiscriminator,
+)
 from pipelines.precipitation_model.impa.src.models.lightning_module import LModule
 
 

pipelines/precipitation_model/impa/src/models/UNET/lightning.py

@@ -1,7 +1,13 @@
 # -*- coding: utf-8 -*-
 import torch
+
 from pipelines.precipitation_model.impa.src.models.lightning_module import LModule
-from pipelines.precipitation_model.impa.src.models.UNET.unet_parts import DoubleConv, Down, OutConv, Up
+from pipelines.precipitation_model.impa.src.models.UNET.unet_parts import (
+ DoubleConv,
+ Down,
+ OutConv,
+ Up,
+)
 
 
 class model(LModule):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/attention.py

@@ -5,9 +5,12 @@
 import torch
 import torch.nn.functional as F
 from einops import rearrange, repeat
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.utils import checkpoint
 from torch import einsum, nn
 
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.utils import (
+ checkpoint,
+)
+
 
 def exists(val):
  return val is not None

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/autoenc_v2.py

@@ -2,11 +2,17 @@
 import numpy as np
 import pytorch_lightning as pl
 import torch
+
 from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.distributions import (
  DiagonalGaussianDistribution,
 )
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.loss import LPIPSWithDiscriminator
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.modules import Decoder, Encoder
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.loss import (
+ LPIPSWithDiscriminator,
+)
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.modules import (
+ Decoder,
+ Encoder,
+)
 
 
 class AutoencoderKL(pl.LightningModule):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/autoencoder/loss.py

@@ -3,11 +3,12 @@
 
 import torch
 import torch.nn.functional as F
+from torch import nn
+
 from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoencoder.discriminator import (
  NLayerDiscriminator,
  weights_init,
 )
-from torch import nn
 
 
 def hinge_d_loss(logits_real, logits_fake):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/autoencoder/modules.py

@@ -8,7 +8,9 @@
 import torch.nn as nn
 
 # from ldm.util import instantiate_from_config
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.attention import LinearAttention
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.attention import (
+ LinearAttention,
+)
 
 
 class Encoder(nn.Module):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/ddim.py

@@ -5,12 +5,13 @@
 
 import numpy as np
 import torch
+from tqdm import tqdm
+
 from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.utils import (
  make_ddim_sampling_parameters,
  make_ddim_timesteps,
  noise_like,
 )
-from tqdm import tqdm
 
 
 class DDIMSampler(object):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/lightning_v2.py

@@ -6,17 +6,26 @@
 import torch.nn.functional as F
 from einops import rearrange
 from pytorch_lightning import LightningModule
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoenc_v2 import AutoencoderKL
+from tqdm import tqdm
+
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.autoenc_v2 import (
+ AutoencoderKL,
+)
 
 # from pipelines.precipitation_model.impa.src.models.context_LDM_concat.autoencoder.autoenc_old import AutoencoderKL
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.ddim import DDIMSampler
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.ddim import (
+ DDIMSampler,
+)
 from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.model import (
  get_named_beta_schedule,
  linear_beta_schedule,
 )
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.openaimodel import UNetModel
-from pipelines.precipitation_model.impa.src.utils.data_utils import data_modification_options
-from tqdm import tqdm
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.openaimodel import (
+ UNetModel,
+)
+from pipelines.precipitation_model.impa.src.utils.data_utils import (
+ data_modification_options,
+)
 
 
 def extract(a, t, x_shape):

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/openaimodel.py

@@ -8,7 +8,10 @@
 import torch as th
 import torch.nn as nn
 import torch.nn.functional as F
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.attention import SpatialTransformer
+
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.attention import (
+ SpatialTransformer,
+)
 from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.utils import (
  avg_pool_nd,
  checkpoint,

pipelines/precipitation_model/impa/src/models/context_LDM_concat_new/predict.py

@@ -4,11 +4,16 @@
 
 import pytorch_lightning as pl
 import torch
-from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import HDFDatasetLocations
-from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.lightning_v2 import Diffusion_Model
+from torch.utils.data import DataLoader
+
+from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import (
+ HDFDatasetLocations,
+)
+from pipelines.precipitation_model.impa.src.models.context_LDM_concat_new.lightning_v2 import (
+ Diffusion_Model,
+)
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_ok
 from pipelines.precipitation_model.impa.src.utils.hdf_utils import array_to_pred_hdf
-from torch.utils.data import DataLoader
 
 MEAN = 0.08
 STD = 0.39

pipelines/precipitation_model/impa/src/models/gan/gan_unet/model.py

@@ -3,13 +3,26 @@
 
 import torch
 import torch.nn as nn
-from pipelines.precipitation_model.impa.src.models.gan.gan_unet.unet_parts import DoubleConv, Down, OutConv, S, Up, Up2
-from pipelines.precipitation_model.impa.src.models.gan.parts_gan import AvgPool, L2_Block, L3_Block, Noise_Projector
+from torch.nn.utils import spectral_norm
+
+from pipelines.precipitation_model.impa.src.models.gan.gan_unet.unet_parts import (
+ DoubleConv,
+ Down,
+ OutConv,
+ S,
+ Up,
+ Up2,
+)
+from pipelines.precipitation_model.impa.src.models.gan.parts_gan import (
+ AvgPool,
+ L2_Block,
+ L3_Block,
+ Noise_Projector,
+)
 from pipelines.precipitation_model.impa.src.models.nowcasting.layers.generation.generative_network import (
  Generative_Decoder,
  Generative_Encoder,
 )
-from torch.nn.utils import spectral_norm
 
 ni = 192 # size of image
 ndf = 32 # size of discriminator feature map

pipelines/precipitation_model/impa/src/models/lightning_module.py

@@ -3,7 +3,10 @@
 import torch
 from einops import rearrange
 from pytorch_lightning import LightningModule
-from pipelines.precipitation_model.impa.src.utils.data_utils import data_modification_options
+
+from pipelines.precipitation_model.impa.src.utils.data_utils import (
+ data_modification_options,
+)
 
 
 # define the LightningModule

pipelines/precipitation_model/impa/src/models/mamba/lightning.py

@@ -3,8 +3,11 @@
 import torch
 from einops import rearrange
 from pytorch_lightning import LightningModule
+
 from pipelines.precipitation_model.impa.src.models.mamba.vmamba import VSSM
-from pipelines.precipitation_model.impa.src.utils.data_utils import data_modification_options
+from pipelines.precipitation_model.impa.src.utils.data_utils import (
+ data_modification_options,
+)
 
 
 class Vmamba_lightning(LightningModule):

pipelines/precipitation_model/impa/src/models/mamba/predict.py

@@ -4,11 +4,16 @@
 
 import pytorch_lightning as pl
 import torch
-from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import HDFDatasetLocations
-from pipelines.precipitation_model.impa.src.models.mamba.lightning import Vmamba_lightning
+from torch.utils.data import DataLoader
+
+from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import (
+ HDFDatasetLocations,
+)
+from pipelines.precipitation_model.impa.src.models.mamba.lightning import (
+ Vmamba_lightning,
+)
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_ok
 from pipelines.precipitation_model.impa.src.utils.hdf_utils import array_to_pred_hdf
-from torch.utils.data import DataLoader
 
 MEAN = 0.08
 STD = 0.39

pipelines/precipitation_model/impa/src/models/nowcasting/layers/generation/generative_network.py

@@ -3,8 +3,11 @@
 
 import torch.nn as nn
 import torch.nn.functional as F
+
 from pipelines.precipitation_model.impa.src.models.nowcasting.layers.evolution.module import *
-from pipelines.precipitation_model.impa.src.models.nowcasting.layers.generation.module import GenBlock
+from pipelines.precipitation_model.impa.src.models.nowcasting.layers.generation.module import (
+ GenBlock,
+)
 
 
 class Generative_Encoder(nn.Module):

pipelines/precipitation_model/impa/src/models/predict.py

@@ -7,13 +7,21 @@
 import pytorch_lightning as pl
 import torch
 from einops import rearrange
-from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import HDFDatasetLocations
-from pipelines.precipitation_model.impa.src.data.PredHDFDatasetLocations import PredHDFDatasetLocations
+from torch.utils.data import DataLoader
+
+from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import (
+ HDFDatasetLocations,
+)
+from pipelines.precipitation_model.impa.src.data.PredHDFDatasetLocations import (
+ PredHDFDatasetLocations,
+)
 from pipelines.precipitation_model.impa.src.utils.data_utils import sat_dataframe
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_ok
 from pipelines.precipitation_model.impa.src.utils.hdf_utils import array_to_pred_hdf
-from pipelines.precipitation_model.impa.src.utils.models_utils import get_ds, options_pretrained
-from torch.utils.data import DataLoader
+from pipelines.precipitation_model.impa.src.utils.models_utils import (
+ get_ds,
+ options_pretrained,
+)
 
 MEAN_LOG_SAT = 0.08
 STD_LOG_SAT = 0.39

pipelines/precipitation_model/impa/src/models/pysteps_LK/predict.py

@@ -7,7 +7,10 @@
 from joblib import Parallel, delayed
 from pysteps import motion, nowcasts
 from pysteps.utils import conversion, transformation
-from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import HDFDatasetLocations
+
+from pipelines.precipitation_model.impa.src.data.HDFDatasetLocations import (
+ HDFDatasetLocations,
+)
 from pipelines.precipitation_model.impa.src.utils.general_utils import print_ok
 from pipelines.precipitation_model.impa.src.utils.hdf_utils import array_to_pred_hdf