No implementation of function Function(<built-in function mul>) found for signature: >>> mul(array(float32, 1d, C), array(float32, 1d, C))

[vrunm]

I am trying to optimize the below code, so that it executes on GPU. There is a cosine_similarity function in scikit-learn, which was throwing error with numba, so then I created a separate function

@cuda.jit
def cosine_similarity_numba(u:np.ndarray, v:np.ndarray):
    assert(u.shape[0] == v.shape[0])
    print(u.shape[0])
    print(v.shape[0])
    l = 0
    m = 0
    n = 0
    for i in range(u.shape[0]):
        print(u[i])
        print(v[i])
        l += u[i]*v[i]
        m += u[i]*u[i]
        n += v[i]*v[i]
    cos_theta = 1
    if m!=0 and n!=0:
        cos_theta = l/np.sqrt(m*n)
    return cos_theta

but numba is still throwing error.

The error is:-
`

Failed in cuda mode pipeline (step: nopython frontend)
No implementation of function Function(<built-in function mul>) found for signature:
 
 >>> mul(array(float32, 1d, C), array(float32, 1d, C))
 
There are 12 candidate implementations:
      - Of which 10 did not match due to:
      Overload of function 'mul': File: <numerous>: Line N/A.
        With argument(s): '(array(float32, 1d, C), array(float32, 1d, C))':
       No match.
      - Of which 2 did not match due to:
      Operator Overload in function 'mul': File: unknown: Line unknown.
        With argument(s): '(array(float32, 1d, C), array(float32, 1d, C))':
       No match for registered cases:
        * (int64, int64) -> int64
        * (int64, uint64) -> int64
        * (uint64, int64) -> int64
        * (uint64, uint64) -> uint64
        * (float32, float32) -> float32
        * (float64, float64) -> float64
        * (complex64, complex64) -> complex64
        * (complex128, complex128) -> complex128

During: typing of intrinsic-call at /home/proeffico/Desktop/ProlificCUDA/face_rec.py (92)

File "face_rec.py", line 92:
def cosine_similarity_numba(u:np.ndarray, v:np.ndarray):
    <source elided>
        print(v[i])
        l += u[i]*v[i]
        ^

During: resolving callee type: type(CUDADispatcher(<function cosine_similarity_numba at 0x7f622ce37700>))
During: typing of call at /home/proeffico/Desktop/ProlificCUDA/face_rec.py (59)


File "face_rec.py", line 59:
def ml_search_algorithm(names,feature_column,test_vector,thresh=0.5):
    <source elided>
    # step-3: Cal. cosine similarity
    similar = cosine_similarity_numba(x,test_vector.reshape(1,-1))
    ^
`

Is there any way around this?

[adrinjalali]

That seems a numba issue.