tf.experimental.numpy.issubdtype

Returns True if first argument is a typecode lower/equal in type hierarchy.

tf.experimental.numpy.issubdtype(
    arg1, arg2
)

This is like the builtin :func:issubclass, but for dtype\ s.

Parameters

arg1, arg2 : dtype_like dtype or object coercible to one

Returns

out : bool

See Also

:ref:arrays.scalars : Overview of the numpy type hierarchy. issubsctype, issubclass_

Examples

issubdtype can be used to check the type of arrays:

ints = np.array([1, 2, 3], dtype=np.int32)
np.issubdtype(ints.dtype, np.integer)
True
np.issubdtype(ints.dtype, np.floating)
False
 
floats = np.array([1, 2, 3], dtype=np.float32)
np.issubdtype(floats.dtype, np.integer)
False
np.issubdtype(floats.dtype, np.floating)
True

Similar types of different sizes are not subdtypes of each other:

np.issubdtype(np.float64, np.float32)
False
np.issubdtype(np.float32, np.float64)
False

but both are subtypes of floating:

np.issubdtype(np.float64, np.floating)
True
np.issubdtype(np.float32, np.floating)
True

For convenience, dtype-like objects are allowed too:

np.issubdtype('S1', np.string_)
True
np.issubdtype('i4', np.signedinteger)
True