code: def test_flop_counter_overrides():
      # Testing that one can override the counter's default implementation for
      # an operation with a custom counter function.
  
      class Addition(torch.nn.Module):
          def forward(self, x, y):
              return x + y
  
      add_override_value = 1234567.0
  
      count, _, _ = count_flops(
          Addition(),
          (torch.tensor(5.0), torch.tensor(6.0)),
          counter_overrides={
              "aten::add": lambda inputs, outputs: add_override_value
          },
      )
  
      assert torch.allclose(
          torch.tensor(count).float(),
          torch.tensor(add_override_value).float(),
      )
  
imports: import pytest
  import torch
  import torch.nn
  from neuralcompression.functional import count_flops
label_desc: Use image node_id 4 for calling a global function with example usage: test_flop_counter_overrides() and returns: unknown