class_docstr: Samples N time points from each series.
  
  Parameters
  ----------
  N
      number of time points to sample from each time series.
class_docstr_tok: ["Samples","N","time","points","from","each","series",".","Parameters","--","--","--","--","--","N","number","of","time","points","to","sample","from","each","time","series","."]
code: def __call__(self, ts: np.ndarray) -> np.ndarray:
      a, b = self._get_bounds(ts)
      if a > b:
          return np.array([], dtype=int)
  
      return np.random.randint(a, b + 1, size=self.N)
  
imports: from typing import Tuple
  import numpy
  from gluonts.dataset.stat import ScaleHistogram
  from gluonts.pydantic import BaseModel
label_desc: Use image node_id 1 for calling the NumInstanceSampler obj's underlying member method code with example usage: obj.__call__(ts) and returns: np, np