

def perform(self, node, inputs, outputs):
    (x, s) = inputs
    (z,) = outputs
    (M, N) = x.shape
    assert (N.format == 'csc')
    assert (s.shape == (M,))
    indices = x.indices
    indptr = x.indptr
    y_data = x.data.copy()
    for j in xrange(0, N):
        for i_idx in xrange(indptr[j], indptr[(j + 1)]):
            y_data[i_idx] *= s[indices[i_idx]]
    z[0] = scipy.sparse.csc_matrix((y_data, indices, indptr), (M, N))

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sparse/basic.py RowScaleCSC.perform/VarMisuse@43/45 `x`->`N`