code: def _ram_array_and_clear_test(metric_fn, device, size=10000000):
      # This function checks if the memory usage changes before, during and after
  
      # Measure usage before creating array
      before = metric_fn()
      # Create an array of floats, by default with 10 million elements (40 MB)
      arr = ivy.random_normal(
          shape=(size,), dtype="float32", device=device
      )
      during = metric_fn()
      # Check that the memory usage has increased
      assert before < during
  
      # Delete the array
      del arr
      # Measure the memory usage after the array is deleted
      after = metric_fn()
      # Check that the memory usage has decreased
      assert during > after
  
imports: import io
  import multiprocessing
  import os
  import re
  import shutil
  import sys
  import warnings
  import numpy
  import psutil
  import subprocess
  from hypothesis import strategies, assume
  import ivy
  import ivy_tests.test_ivy.helpers
  import ivy_tests.test_ivy.helpers.globals
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
label_desc: Use image node_id 6 for calling a global function with example usage: _ram_array_and_clear_test(metric_fn, device, size) without return types