[devops] Upgrade to lightning 2.0

neuralprophet/configure.py

@@ -5,15 +5,15 @@
 import types
 from collections import OrderedDict
 from dataclasses import dataclass, field
-from typing import Callable, Iterable, List, Optional
+from typing import Callable, List, Optional
 from typing import OrderedDict as OrderedDictType
 from typing import Type, Union
 
 import numpy as np
 import pandas as pd
 import torch
 
-from neuralprophet import df_utils, np_types, utils, utils_torch
+from neuralprophet import df_utils, np_types, utils_torch
 from neuralprophet.custom_loss_metrics import PinballLoss
 from neuralprophet.hdays_utils import get_holidays_from_country
 
@@ -306,17 +306,17 @@
             self.trend_global_local = "global"
 
         # If trend_local_reg < 0
         if self.trend_local_reg < 0:
             log.error("Invalid  negative trend_local_reg '{}'. Set to False".format(self.trend_local_reg))
             self.trend_local_reg = False
 
         # If trend_local_reg = True
-        if self.trend_local_reg:
+        if self.trend_local_reg is True:
             log.error("trend_local_reg = True. Default trend_local_reg value set to 1")
             self.trend_local_reg = 1
 
         # If Trend modelling is global.
-        if self.trend_global_local == "global" and self.trend_local_reg:
+        if self.trend_global_local == "global" and self.trend_local_reg is True:
             log.error("Trend modeling is '{}'. Setting the trend_local_reg to False".format(self.trend_global_local))
             self.trend_local_reg = False
 
@@ -356,13 +356,13 @@
             log.error("Invalid global_local mode '{}'. Set to 'global'".format(self.global_local))
             self.global_local = "global"
 
         self.periods = OrderedDict(
             {
                 "yearly": Season(
                     resolution=6,
                     period=365.25,
                     arg=self.yearly_arg,
                     global_local=(
                         self.yearly_global_local
                         if self.yearly_global_local in ["global", "local"]
                         else self.global_local
@@ -373,7 +373,7 @@
                     resolution=3,
                     period=7,
                     arg=self.weekly_arg,
                     global_local=(
                         self.weekly_global_local
                         if self.weekly_global_local in ["global", "local"]
                         else self.global_local
@@ -384,7 +384,7 @@
                     resolution=6,
                     period=1,
                     arg=self.daily_arg,
                     global_local=(
                         self.daily_global_local if self.daily_global_local in ["global", "local"] else self.global_local
                     ),
                     condition_name=None,
@@ -393,17 +393,17 @@
         )
 
         # If seasonality_local_reg < 0
         if self.seasonality_local_reg < 0:
             log.error("Invalid  negative seasonality_local_reg '{}'. Set to False".format(self.seasonality_local_reg))
             self.seasonality_local_reg = False
 
         # If seasonality_local_reg = True
-        if self.seasonality_local_reg:
+        if self.seasonality_local_reg is True:
             log.error("seasonality_local_reg = True. Default seasonality_local_reg value set to 1")
             self.seasonality_local_reg = 1
 
         # If Season modelling is global.
-        if self.global_local == "global" and self.seasonality_local_reg:
+        if self.global_local == "global" and self.seasonality_local_reg is True:
             log.error(
                 "Seasonality modeling is '{}'. Setting the seasonality_local_reg to False".format(self.global_local)
             )
@@ -414,7 +414,7 @@
             resolution=resolution,
             period=period,
             arg=arg,
             global_local=global_local if global_local in ["global", "local"] else self.global_local,
             condition_name=condition_name,
         )
 
@@ -490,7 +490,7 @@
     regressors: OrderedDict = field(init=False)  # contains RegressorConfig objects
 
     def __post_init__(self):
         self.regressors = None
 
 
 @dataclass

neuralprophet/utils.py

@@ -5,15 +5,14 @@
 import os
 import sys
 from collections import OrderedDict
-from typing import IO, TYPE_CHECKING, BinaryIO, Iterable, Optional, Union
+from typing import IO, TYPE_CHECKING, BinaryIO, Optional, Union
 
 import numpy as np
 import pandas as pd
 import pytorch_lightning as pl
 import torch
 
 from neuralprophet import utils_torch
-from neuralprophet.hdays_utils import get_country_holidays
 from neuralprophet.logger import ProgressBar
 
 if TYPE_CHECKING: