code: def _error_inputs_sparse(
      maybe_failing_sample_inputs,
      validate_sample_input,
      op_info,
      *args,
      **kwargs,
  ):
      check_validate = (
          os.environ.get(
              "PYTORCH_TEST_CHECK_VALIDATE_SPARSE_SAMPLES", "0"
          )
          == "1"
      )
      for sample in maybe_failing_sample_inputs(
          op_info, *args, **kwargs
      ):
          sample = validate_sample_input(
              op_info, sample, check_validate=check_validate
          )
          if isinstance(sample, ErrorInput):
              yield sample
  
imports: import os
  import torch
  from torch.testing import make_tensor
  from torch.testing._internal.opinfo.core import BinaryUfuncInfo, ErrorInput, generate_elementwise_binary_tensors, ReductionOpInfo, sample_inputs_reduction, SampleInput
label_desc: Use image node_id 3 for calling a global function with example usage: _error_inputs_sparse(maybe_failing_sample_inputs, validate_sample_input, op_info) without return types