code: def __init__(self, freq: str) -> None:
      # reocurring freq
      freqs = [
          "month",
          "day",
          "hour",
          "minute",
          "weekofyear",
          "weekday",
          "dayofweek",
          "dayofyear",
          "daysinmonth",
      ]
  
      assert freq in freqs
      self.freq = freq
  
imports: from functools import partial
  from typing import Callable, List, Optional
  import numpy
  import pandas
  from mxnet.gluon import HybridBlock
  from pandas.tseries.frequencies import to_offset
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.loader import DataLoader, TrainDataLoader, ValidationDataLoader
  from gluonts.model.predictor import Predictor
  from gluonts.mx.batchify import batchify
  from gluonts.mx.distribution import DistributionOutput, LowrankMultivariateGaussianOutput
  from gluonts.mx.model.estimator import GluonEstimator
  from gluonts.mx.model.predictor import RepresentableBlockPredictor
  from gluonts.mx.trainer import Trainer
  from gluonts.mx.util import copy_parameters, get_hybrid_forward_input_names
  from gluonts.time_feature import TimeFeature, norm_freq_str
  from gluonts.transform import AddObservedValuesIndicator, AddTimeFeatures, AsNumpyArray, CDFtoGaussianTransform, Chain, ExpandDimArray, ExpectedNumInstanceSampler, InstanceSampler, InstanceSplitter, RenameFields, SelectFields, SetFieldIfNotPresent, TargetDimIndicator, TestSplitSampler, Transformation, ValidationSplitSampler, VstackFeatures, cdf_to_gaussian_forward_transform
  from ._network import DeepVARPredictionNetwork, DeepVARTrainingNetwork
label_desc: Use image node_id 1 to create a new FourierDateFeatures object  with example: obj = FourierDateFeatures(freq)