code: def inplace_csr_column_scale(X, scale):
      """Inplace column scaling of a 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 : 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.
      """
      assert scale.shape[0] == X.shape[1]
      indices_copy = X.indices.copy()
      indices_copy[indices_copy >= X.shape[1]] = X.shape[1] - 1
      X.data *= scale.take(indices_copy)
  
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 6 for calling a global function with example usage: inplace_csr_column_scale(X, scale) without return types