mix data type inputs for numba njit

Question

I have a large array for operation, for example, matrix transpose. numba is much faster:

#test_transpose.py
import numpy as np
import numba as nb
import time


@nb.njit('float64[:,:](float64[:,:])', parallel=True)
def transpose(x):
    r, c = x.shape
    x2 = np.zeros((c, r))
    for i in nb.prange(c):
        for j in range(r):
            x2[i, j] = x[j][i]
   return x2


if __name__ == "__main__":
    x = np.random.randn(int(3e6), 50)
    t = time.time()
    x = x.transpose().copy()
    print(f"numpy transpose: {round(time.time() - t, 4)} secs")

    x = np.random.randn(int(3e6), 50)
    t = time.time()
    x = transpose(x)
    print(f"numba paralleled transpose: {round(time.time() - t, 4)} secs")

Run in Windows command prompt

D:\data\test>python test_transpose.py
numpy transpose: 2.0961 secs
numba paralleled transpose: 0.8584 secs

However, I want to input another large matrix, which are integers, using x as

x = np.random.randint(int(3e6), size=(int(3e6), 50), dtype=np.int64)

Exception is raised as

Traceback (most recent call last):
  File "test_transpose.py", line 39, in <module>
    x = transpose(x)
  File "C:\Program Files\Python38\lib\site-packages\numba\core\dispatcher.py", line 703, in _explain_matching_error
    raise TypeError(msg)
TypeError: No matching definition for argument type(s) array(int64, 2d, C)

It does not recognize the input data matrix as integer. If I release the data type check for the integer matrix as

@nb.njit(parallel=True) # 'float64[:,:](float64[:,:])'
def transpose(x):
    r, c = x.shape
    x2 = np.zeros((c, r))
    for i in nb.prange(c):
        for j in range(r):
            x2[i, j] = x[j][i]
    return x2

It is slower:

D:\Data\test>python test_transpose.py
numba paralleled transpose: 1.6653 secs

Using @nb.njit('int64[:,:](int64[:,:])', parallel=True) for the integer data matrix is faster, as expected.

So, how can I still allow mixed data type intputs but keep the speed, instead of creating functions each for different types?