Cython: Transpose A Memoryview

Some background for the question: I'm trying to optimise a custom neural network code. It relies heavily on loops and I decided to use cython to speed up the calculation. I followe

Solution 1:

I think the best answer is "you store the numpy as an untyped python object"

cdefclass C:
    cdefobject array

    defexample_function(self):
        # if you want to use the fast Cython array indexing in a function# you can do:
        cdefnp.ndarray[np.float64_t,ndim=4] self_array = self.array
        # or
        cdefnp.float64_t[:,:,:,:] self_array2 = self.array

        # note that neither of these are copies - they're references# to exactly the same array and so if you modify one it'll modify# self.array toodeffunction2(self):
        return self.array.transpose(1,0,2,3) # works fine!

The small cost to doing it this way is that there's a bit of type-checking at the start of example_function to check that it is actually a 4D numpy array with the correct dtype. Provided you do a decent amount of work in the function that shouldn't matter.

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As an alternative (if you decide you really want to store them as memoryviews) you could use np.asarray to convert it back to a numpy array without making a copy (i.e. they share data).

e.g.

cdefnp.ndarray[DTYPE_t, ndim=4] d_out_image = np.asarray(self.d_y).transpose(1, 0, 2,3)