indicator of intrinsic algorithmic efficiency, so the default
        is set to one. This is in contrast to the default PyTorch
        threadpool size which tries to utilize all cores.
blocked_autorange(callback=None, min_run_time=0.2)
  Measure many replicates while keeping timer overhead to a
  minimum.

  At a high level, blocked_autorange executes the following
  pseudo-code:

     `setup`

     total_time = 0
     while total_time < min_run_time
         start = timer()
         for _ in range(block_size):
             `stmt`
         total_time += (timer() - start)

  Note the variable *block_size* in the inner loop. The choice of
  block size is important to measurement quality, and must balance
  two competing objectives:

     1. A small block size results in more replicates and
        generally better statistics.

     2. A large block size better amortizes the cost of *timer*
