code: def num_samples(self) -> int:
      return self.samples.shape[1]
  
imports: from copy import deepcopy
  from typing import ChainMap, Iterator, Optional, Union
  from dataclasses import dataclass
  import numpy
  from gluonts.dataset.repository import get_dataset
  from gluonts.dataset.split import TestData, split
  from gluonts.ext.naive_2 import naive_2
  from gluonts.time_feature.seasonality import get_seasonality
  from gluonts.model.forecast import Quantile, SampleForecast
  from gluonts.model.seasonal_naive import SeasonalNaivePredictor
  from gluonts.evaluation import Evaluator
  from gluonts.evaluation.backtest import make_evaluation_predictions
  from gluonts.ev import evaluate
  from gluonts.ev.ts_stats import seasonal_error
  from gluonts.ev.metrics import MAPE, MASE, MSE, MSIS, SMAPE, Coverage, SumAbsoluteError, SumQuantileLoss, mean_absolute_label, sum_absolute_label, ND, NRMSE, RMSE, MAECoverage, MeanSumQuantileLoss, MeanWeightedSumQuantileLoss, WeightedSumQuantileLoss, OWA
label_desc: Use image node_id 4 for calling the SampleForecastBatch obj's underlying member method code with example usage: obj.num_samples() and returns: self