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DS-1000 / 723 / I have this example of matrix by matrix multiplication using numpy arrays:

Problem

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Problem:
I have this example of matrix by matrix multiplication using numpy arrays:
import numpy as np
m = np.array([[1,2,3],[4,5,6],[7,8,9]])
c = np.array([0,1,2])
m * c
array([[ 0,  2,  6],
       [ 0,  5, 12],
       [ 0,  8, 18]])
How can i do the same thing if m is scipy sparse CSR matrix? The result should be csr_matrix as well.
This gives dimension mismatch:
sp.sparse.csr_matrix(m)*sp.sparse.csr_matrix(c)

A:
<code>
from scipy import sparse
import numpy as np
example_sA = sparse.csr_matrix(np.array([[1,2,3],[4,5,6],[7,8,9]]))
example_sB = sparse.csr_matrix(np.array([0,1,2]))
def f(sA = example_sA, sB = example_sB):
    # return the solution in this function
    # result = f(sA, sB)
    ### BEGIN SOLUTION

library

Scipy

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Source and history

upstream_id / Original problem ID
723
task_id
ad95fc32-d181-5d69-9acd-89fcf665b71b
task_key
default--test--723
task_revision_id
1
config / split
default / test

Official source

initial import