code: def inplace_row_scale(X, scale):
      """Inplace row scaling of a CSR or CSC matrix.
  
      Scale each row of the data matrix by multiplying with specific scale
      provided by the caller assuming a (n_samples, n_features) shape.
  
      Parameters
      ----------
      X : CSR or CSC sparse matrix, shape (n_samples, n_features)
          Matrix to be scaled.
  
      scale : float array with shape (n_features,)
          Array of precomputed sample-wise values to use for scaling.
      """
      if isinstance(X, sp.csc_matrix):
          inplace_csr_column_scale(X.T, scale)
      elif isinstance(X, sp.csr_matrix):
          inplace_csr_row_scale(X, scale)
      else:
          _raise_typeerror(X)
  
imports: import scipy.sparse
  import numpy
  from .fixes import sparse_min_max, bincount
  from .sparsefuncs_fast import csr_mean_variance_axis0, csc_mean_variance_axis0, incr_mean_variance_axis0
label_desc: Use image node_id 8 for calling a global function with example usage: inplace_row_scale(X, scale) without return types