class_docstr: A class representing binned representations with custom centers.
  
  Parameters
  ----------
  bin_centers
      The bins to be used to discretize the data.
      (default: 1024)
code: def initialize_from_dataset(
      self,
      input_dataset: Dataset,
      ctx: mx.Context = get_mxnet_context(),
  ):
      self.initialize_from_array(np.array([]), ctx)
  
file_path: gluonts/src/gluonts/mx/representation/custom_binning.py
imports: from typing import List, Optional, Tuple
  import mxnet
  import numpy
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.mx import Tensor
  from gluonts.mx.context import get_mxnet_context
  from .binning_helpers import bin_edges_from_bin_centers
  from .representation import Representation
label_desc: Use image node_id 2 for calling the CustomBinning obj's underlying member method code with example usage: obj.initialize_from_dataset(input_dataset, ctx) without return types