CODEWITHSUNDEEP
python-3.xnumpyjitnumba
Kritika
Kritika

Reputation: 98

Numba Invalid use of BoundFunction on np.astype

I'm trying to compile a function that does some computation on an image patch using numba. Here is part of the code:

@jit(nopython=True, parallel=True)
def value_at_patch(img, coords, imgsize, patch_radius):
    x_center = coords[0]; y_center = coords[1];
    r = patch_radius
    s = 2*r+1
    xvec = np.arange(x_center-r, x_center+r+1)
    xvec[xvec <= 0] = 0 #prevent negative index
    xvec = xvec.astype(int)
    yvec = np.arange(y_center-r, y_center+r+1)
    yvec[yvec <= 0] = 0
    yvec = yvec.astype(int)
    A = np.zeros((s,s))

    #do some parallel computation on A

    p = np.any(A)
    return p

I'm able to compile the function, but when I run it, I get the following error message:

Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of BoundFunction(array.astype for array(float64, 1d, C)) with parameters (Function(<class 'int'>))
 * parameterized
[1] During: resolving callee type: BoundFunction(array.astype for array(float64, 1d, C))
[2] During: typing of call at <ipython-input-17-90e27ac302a8> (42)


File "<ipython-input-17-90e27ac302a8>", line 42:
def value_at_patch(img, coords, imgsize, patch_radius):
    <source elided>
    xvec[xvec <= 0] = 0 #prevent negative index
    xvec = xvec.astype(int)
    ^

I checked the numba documentation and np.astype should be supported with just one argument. Do you know what could be causing the problem?

Upvotes: 7

Views: 3469

Answers (1)

Bal Krishna Jha
Bal Krishna Jha

Reputation: 7226

Use np.int64 in place of int in following places:

xvec = xvec.astype(np.int64)

yvec = yvec.astype(np.int64)

Upvotes: 8

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