[Python] polars: multiply 2 LazyFrames together by column

I have 2 polars LazyFrames:

df1 = pl.DataFrame(data={
'foo': np.random.uniform(0,127, size= n).astype(np.float64),
'bar': np.random.uniform(1e3,32767, size= n).astype(np.float64),
'baz': np.random.uniform(1e6,2147483, size= n).astype(np.float64)
}).lazy()

df2 = pl.DataFrame(data={
'foo': np.random.uniform(0,127, size= n).astype(np.float64),
'bar': np.random.uniform(1e3,32767, size= n).astype(np.float64),
'baz': np.random.uniform(1e6,2147483, size= n).astype(np.float64)
}).lazy()


I would like to multiply each column in df1 with its respective column in df2.

If I convert these to non-lazy DataFrames I can achieve this:

df1.collect() * df2.collect()


foo bar baz
f64 f64 f64
3831.295563 6.4637e6 3.3669e12
164.194271 2.9691e8 2.2696e12
3655.918761 1.9444e7 2.3625e12
7191.48868 3.7044e7 3.1687e12
9559.505277 2.6864e8 2.5426e12


However, if I try to perform the same expression on the LazyFrames, I get an exception

df1 * df2

TypeError: unsupported operand type(s) for *: 'LazyFrame' and 'LazyFrame'
​

How can I perform column-wise multiplication across 2 LazyFrames?

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