class_docstr: Internal class that manages partitioning. The ``FakePalettize`` class base classes the ``_Partitioner`` class
  and all the partitioning logic is controlled by this class.
docstr: Method to flatten a particular weight partition.
code: def flatten(self, weight_partition: _torch.Tensor):
      """
      Method to flatten a particular weight partition.
      """
      permute = self.cluster_permute
      dim = self.cluster_dim
  
      if permute and len(permute) == len(weight_partition.size()):
          weight_partition = weight_partition.permute(permute)
  
      num_misalignment = _torch.numel(weight_partition) % dim
  
      pad = None
      if num_misalignment:
          weight_partition = weight_partition.flatten()
          pad = weight_partition[-num_misalignment:]
          weight_partition = weight_partition[:-num_misalignment]
  
      return weight_partition.reshape(-1, dim), pad
  
file_path: coremltools/coremltools/optimize/torch/palettization/_partitioner.py
imports: from typing import Tuple
  import torch
  from ._efficient_kmeans import _EfficientKMeans
label_desc: Use image node_id 5 for calling the _Partitioner obj's underlying member method code with example usage: obj.flatten(weight_partition) and returns: weight_partition,  pad