code: def validate_sample_input_sparse(
      op_info, sample, check_validate=False
  ):
      """Return the specified sample when it is valid and supported by the
      operation. Otherwise, return the sample as ErrorInput instance.
  
      When check_validate is True, the result is validated against
      calling the op on the sample.
      """
      if isinstance(op_info, ReductionOpInfo):
          return _validate_sample_input_sparse_reduction(
              op_info, sample, check_validate=check_validate
          )
      elif isinstance(op_info, BinaryUfuncInfo):
          return _validate_sample_input_sparse_elementwise_binary_operation(
              op_info, sample, check_validate=check_validate
          )
      else:
          return _validate_sample_input_sparse_default(
              op_info, sample, check_validate=check_validate
          )
  
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 23 for calling a global function with example usage: validate_sample_input_sparse(op_info, sample, check_validate) and returns: _validate_sample_input_sparse_reduction, _validate_sample_input_sparse_elementwise_binary_operation, _validate_sample_input_sparse_default