docstr: Make sure arguments can be passed correctly.
docstr_tok: ["Make","sure","arguments","can","be","passed","correctly","."]
code: def testBasicMemory(self):
      """Make sure arguments can be passed correctly."""
      with test_util.device(use_gpu=False):
          a = constant_op.constant(10, name="a")
          b = constant_op.constant(20, name="b")
          c = math_ops.add_n([a, b], name="c")
          d = math_ops.add_n([b, c], name="d")
          train_op = ops.get_collection_ref(ops.GraphKeys.TRAIN_OP)
          train_op.append(d)
          mg = meta_graph.create_meta_graph_def(
              graph=ops.get_default_graph()
          )
  
      report = cost_analyzer.GenerateMemoryReport(mg)
  
      # Print the report to make it easier to debug
      print("{}".format(report))
  
      # Check the report
      self.assertTrue(
          "Peak usage for device /job:localhost/replica:0/task:0/device:CPU:0: "
          "16 bytes" in report
      )
      self.assertTrue("  a:0 uses 4 bytes" in report)
      self.assertTrue("  b:0 uses 4 bytes" in report)
      self.assertTrue("  c:0 uses 4 bytes" in report)
      self.assertTrue("  d:0 uses 4 bytes" in report)
  
imports: import re
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import meta_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.grappler import cost_analyzer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_grad
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import adam
label_desc: Use image node_id 4 for calling the CostAnalysisTest obj's underlying member method code with example usage: obj.testBasicMemory() without return types