class_docstr: This benchmark concatenates an array of size ``(5n)^3``
class_docstr_tok: ["This","benchmark","concatenates","an","array","of","size","``","(","5n",")","^3","``"]
code: def setup(self, n, mode):
      # Slow setup method: hence separated from the others above
      self.a000 = np.ones((2 * n, 2 * n, 2 * n), int) * 1
  
      self.a100 = np.ones((3 * n, 2 * n, 2 * n), int) * 2
      self.a010 = np.ones((2 * n, 3 * n, 2 * n), int) * 3
      self.a001 = np.ones((2 * n, 2 * n, 3 * n), int) * 4
  
      self.a011 = np.ones((2 * n, 3 * n, 3 * n), int) * 5
      self.a101 = np.ones((3 * n, 2 * n, 3 * n), int) * 6
      self.a110 = np.ones((3 * n, 3 * n, 2 * n), int) * 7
  
      self.a111 = np.ones((3 * n, 3 * n, 3 * n), int) * 8
  
      self.block = [
          [
              [self.a000, self.a001],
              [self.a010, self.a011],
          ],
          [
              [self.a100, self.a101],
              [self.a110, self.a111],
          ],
      ]
      self.arr_list = [
          a for two_d in self.block for one_d in two_d for a in one_d
      ]
  
imports: from .common import Benchmark
  import numpy
label_desc: Use image node_id 1 for calling the Block3D obj's underlying member method code with example usage: obj.setup(n, mode) without return types