code: def _validate_sample_input_sparse_default(
      op_info, sample, check_validate=False
  ):
      if op_info.name == "to_sparse":
          if (
              sample.input.layout
              in {
                  torch.sparse_csr,
                  torch.sparse_csc,
                  torch.sparse_bsr,
                  torch.sparse_bsc,
              }
              and len(sample.args) == 1
              and isinstance(sample.args[0], int)
              and sample.args[0] != 2
          ):
              sample = ErrorInput(
                  sample,
                  error_regex="sparse dim argument must be 2 for sparse_compressed_to_sparse",
              )
  
      if check_validate:
          _check_validate(op_info, sample)
      return 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 22 for calling a global function with example usage: _validate_sample_input_sparse_default(op_info, sample, check_validate) and returns: sample