code: def inplace_csr_row_scale(X, scale):
      """Inplace row scaling of a CSR matrix.
  
      Scale each sample of the data matrix by multiplying with specific scale
      provided by the caller assuming a (n_samples, n_features) shape.
  
      Parameters
      ----------
      X : sparse matrix of shape (n_samples, n_features)
          Matrix to be scaled. It should be of CSR format.
  
      scale : ndarray of float of shape (n_samples,)
          Array of precomputed sample-wise values to use for scaling.
      """
      assert scale.shape[0] == X.shape[0]
      X.data *= np.repeat(scale, np.diff(X.indptr))
  
imports: import numpy
  import scipy.sparse
  from ..utils.validation import _check_sample_weight
  from .sparsefuncs_fast import csc_mean_variance_axis0
  from .sparsefuncs_fast import csr_mean_variance_axis0
  from .sparsefuncs_fast import incr_mean_variance_axis0
label_desc: Use image node_id 4 for calling a global function with example usage: inplace_csr_row_scale(X, scale) without return types