code: def inplace_column_scale(X, scale):
      """Inplace column scaling of a CSC/CSR matrix.
  
      Scale each feature of the data matrix by multiplying with specific scale
      provided by the caller assuming a (n_samples, n_features) shape.
  
      Parameters
      ----------
      X : CSC or CSR matrix with shape (n_samples, n_features)
          Matrix to normalize using the variance of the features.
  
      scale : float array with shape (n_features,)
          Array of precomputed feature-wise values to use for scaling.
      """
      if iscsc(X):
          inplace_csr_row_scale(X.T, scale)
      elif iscsr(X):
          inplace_csr_column_scale(X, scale)
      else:
          _raise_typeerror(X)
  
file_path: cuml/python/cuml/_thirdparty/sklearn/utils/sparsefuncs.py
imports: from ....thirdparty_adapters.sparsefuncs_fast import csr_mean_variance_axis0, csc_mean_variance_axis0
  from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import gpu_only_import
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals.safe_imports import cpu_only_import_from
label_desc: Use image node_id 8 for calling a global function with example usage: inplace_column_scale(X, scale) without return types