code: def convolution():
      # MNIST-scale convolution operation
      import autograd.scipy.signal
  
      convolve = autograd.scipy.signal.convolve
      dat = npr.randn(256, 3, 28, 28)
      kernel = npr.randn(3, 5, 5)
      with tictoc():
          convolve(
              dat, kernel, axes=([2, 3], [1, 2]), dot_axes=([1], [0])
          )
  
file_path: autograd/tests/profiling.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  from autograd import grad
  import autograd.numpy
  import autograd.numpy.random
  from time import time
  from contextlib import contextmanager
label_desc: Use image node_id 3 for calling a global function with example usage: convolution() without return types