jax.numpy.subtract¶

jax.numpy.subtract(x1, x2)¶

Subtract arguments, element-wise.

LAX-backend implementation of subtract(). Original docstring below.

subtract(x1, x2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj])

Parameters: x2 (x1,) – The arrays to be subtracted from each other. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
Returns: y – The difference of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars.
Return type: ndarray

Notes

Equivalent to x1 - x2 in terms of array broadcasting.

Examples

>>> np.subtract(1.0, 4.0)
-3.0

>>> x1 = np.arange(9.0).reshape((3, 3))
>>> x2 = np.arange(3.0)
>>> np.subtract(x1, x2)
array([[ 0.,  0.,  0.],
       [ 3.,  3.,  3.],
       [ 6.,  6.,  6.]])