code: def rankreduce_batch(arrays, rankbound):
      """Apply rankreduce to axis 0 stack of arrays."""
      resultarrays = np.zeros(
          [arrays.shape[0], arrays.shape[1], rankbound]
      )
      for i in range(arrays.shape[0]):
          resultarrays[i, :, :] = rankreduce(arrays[i, :, :], rankbound)
      return resultarrays
  
imports: import collections
  from functools import partial
  import numpy
  from scipy.sparse.linalg import svds
  from sklearn.base import BaseEstimator, TransformerMixin
  from sktime.dists_kernels.base import BasePairwiseTransformerPanel
label_desc: Use image node_id 9 for calling a global function with example usage: rankreduce_batch(arrays, rankbound) and returns: resultarrays