code: def _generate_plausible_inputs_binary(
      num_batches=NUM_BATCHES, batch_size=BATCH_SIZE
  ):
      targets = torch.randint(high=2, size=(num_batches, batch_size))
      preds = (
          torch.rand(num_batches, batch_size)
          + torch.rand(num_batches, batch_size) * targets / 3
      )
      return _Input(preds=preds / (preds.max() + 0.01), target=targets)
  
file_path: torchmetrics/tests/unittests/classification/inputs.py
imports: from typing import Any
  import pytest
  import torch
  from torch import Tensor
  from unittests import BATCH_SIZE, EXTRA_DIM, NUM_BATCHES, NUM_CLASSES, _GroupInput, _Input
  from unittests.helpers import seed_all
label_desc: Use image node_id 5 for calling a global function with example usage: _generate_plausible_inputs_binary(num_batches, batch_size) and returns: _Input