code: def setup(self, dtype):
      self.one_dim_small = np.arange(600, dtype=dtype)
      self.one_dim = np.arange(3000, dtype=dtype)
      self.one_dim_big = np.arange(480000, dtype=dtype)
      self.two_dim_small = np.arange(1200, dtype=dtype).reshape(30, 40)
      self.two_dim = np.arange(240000, dtype=dtype).reshape(400, 600)
      self.three_dim_small = np.arange(10000, dtype=dtype).reshape(
          10, 100, 10
      )
      self.three_dim = np.arange(24000, dtype=dtype).reshape(20, 30, 40)
      # non_contiguous arrays
      self.non_contiguous_dim1_small = np.arange(1, 80, 2, dtype=dtype)
      self.non_contiguous_dim1 = np.arange(1, 4000, 2, dtype=dtype)
      self.non_contiguous_dim2 = np.arange(
          1, 2400, 2, dtype=dtype
      ).reshape(30, 40)
      self.non_contiguous_dim3 = np.arange(
          1, 48000, 2, dtype=dtype
      ).reshape(20, 30, 40)
  
imports: from .common import Benchmark, get_squares_, get_indexes_rand, TYPES1
  import numpy
label_desc: Use image node_id 1 for calling the Einsum obj's underlying member method code with example usage: obj.setup(dtype) without return types