docstr: Static covariate size.
  
  Returns:
      int: size of static covariates
docstr_tok: ["Static","covariate","size",".","Returns",":","int",":","size","of","static","covariates"]
code: def static_size(self) -> int:
      """Static covariate size.
  
      Returns:
          int: size of static covariates
      """
      return len(self.hparams.static_reals) + sum(
          self.embeddings.output_size[name]
          for name in self.hparams.static_categoricals
      )
  
imports: from copy import copy
  from typing import Dict, List, Optional, Tuple, Union
  from matplotlib import pyplot
  import numpy
  import torch
  from torch import nn
  from pytorch_forecasting.data import TimeSeriesDataSet
  from pytorch_forecasting.data.encoders import NaNLabelEncoder
  from pytorch_forecasting.metrics import MAE, MAPE, MASE, RMSE, SMAPE, MultiHorizonMetric, MultiLoss
  from pytorch_forecasting.models.base_model import BaseModelWithCovariates
  from pytorch_forecasting.models.nhits.sub_modules import NHiTS
  from pytorch_forecasting.models.nn.embeddings import MultiEmbedding
  from pytorch_forecasting.utils import create_mask, detach, to_list
label_desc: Use image node_id 4 for calling the NHiTS obj's underlying member method code with example usage: obj.static_size() and returns: unknown