code: def _validate_sparse_input(X):
      """
      Validate the format and dtype of sparse inputs.
      This function throws an error for any cupyx.scipy.sparse object that is not
      of type cupyx.scipy.sparse.csr_matrix or cupyx.scipy.sparse.csc_matrix.
      It also validates the dtype of the input to be 'float32' or 'float64'
  
      Parameters
      ----------
  
      X : scipy.sparse or cupyx.scipy.sparse object
          A sparse input
  
      Returns
      -------
  
      X : The input converted to a cupyx.scipy.sparse.csr_matrix object
  
      """
  
      acceptable_dtypes = ("float32", "float64")
  
      # NOTE: We can include cupyx.scipy.sparse.csc.csc_matrix
      # once it supports indexing in cupy 8.0.0b5
      acceptable_cupy_sparse_formats = cupyx.scipy.sparse.csr_matrix
  
      if X.dtype not in acceptable_dtypes:
          raise TypeError(
              "Expected input to be of type float32 or float64."
              " Received %s" % X.dtype
          )
      if scipy.sparse.issparse(X):
          return cupyx.scipy.sparse.csr_matrix(X)
      elif cupyx.scipy.sparse.issparse(X):
          if not isinstance(X, acceptable_cupy_sparse_formats):
              raise TypeError(
                  "Expected input to be of type"
                  " cupyx.scipy.sparse.csr_matrix or"
                  " cupyx.scipy.sparse.csc_matrix. Received %s"
                  % type(X)
              )
          else:
              return X
  
imports: from cuml.decomposition import PCA
  from cuml.internals.array import CumlArray
  import cuml.internals
  from cuml.internals.input_utils import input_to_cupy_array
  from cuml.common import input_to_cuml_array
  from cuml import Base
  from cuml.internals.safe_imports import cpu_only_import
  import numbers
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: _validate_sparse_input(X) and returns: cupyx, X