count_nonzero can return either a builtin int or numpy's intp

The return type of np.count_nonzero() is currently somewhat inconsistent:

A builtin integer is returned if axis is None and not keepdims.
An np.intp (or an array) is returned otherwise.

The former case is handled by the an identically named function in the np.core._multiarray_umath
module (which apparently always returns an int) while the latter is effectively a wrapper around
np.ndarray.sum() with its dtype explicitly set to np.intp:

numpy/numpy/core/numeric.py

Lines 484 to 495 in 4ccfbe6

    
           if axis is None and not keepdims: 
        
               return multiarray.count_nonzero(a) 
        
           a = asanyarray(a) 
        
           # TODO: this works around .astype(bool) not working properly (gh-9847) 
        
           if np.issubdtype(a.dtype, np.character): 
        
               a_bool = a != a.dtype.type() 
        
           else: 
        
               a_bool = a.astype(np.bool_, copy=False) 
        
           return a_bool.sum(axis=axis, dtype=np.intp, keepdims=keepdims)

Reproducing code example:

MacOS 10.15.6; Python 3.8.5; NumPy 1.20.0.dev0+eb2c751

In [1]: import numpy as np

In [2]: ar = np.arange(10)

In [3]: np.count_nonzero(ar).__class__
Out[3]: int

In [4]: np.count_nonzero(ar, axis=0).__class__
Out[4]: numpy.int64  # i.e. np.intp

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	if axis is None and not keepdims:
	return multiarray.count_nonzero(a)

	a = asanyarray(a)

	# TODO: this works around .astype(bool) not working properly (gh-9847)
	if np.issubdtype(a.dtype, np.character):
	a_bool = a != a.dtype.type()
	else:
	a_bool = a.astype(np.bool_, copy=False)

	return a_bool.sum(axis=axis, dtype=np.intp, keepdims=keepdims)

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