# jax.ops.index_max¶

jax.ops.index_max(x, idx, y, indices_are_sorted=False, unique_indices=False)[source]

Pure equivalent of x[idx] = maximum(x[idx], y).

Returns the value of x that would result from the NumPy-style indexed assignment:

x[idx] = maximum(x[idx], y)


Note the index_max operator is pure; x itself is not modified, instead the new value that x would have taken is returned.

Unlike the NumPy code x[idx] = maximum(x[idx], y), if multiple indices refer to the same location the final value will be the overall max. (NumPy would only look at the last update, rather than all of the updates.)

Parameters
• x – an array with the values to be updated.

• idx – a Numpy-style index, consisting of None, integers, slice objects, ellipses, ndarrays with integer dtypes, or a tuple of the above. A convenient syntactic sugar for forming indices is via the jax.ops.index object.

• y – the array of updates. y must be broadcastable to the shape of the array that would be returned by x[idx].

• indices_are_sorted – whether scatter_indices is known to be sorted

• unique_indices – whether scatter_indices is known to be free of duplicates

Returns

An array.

>>> x = jax.numpy.ones((5, 6))
>>> jax.ops.index_max(x, jax.ops.index[2:4, 3:], 6.)
array([[1., 1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1., 1.],
[1., 1., 1., 6., 6., 6.],
[1., 1., 1., 6., 6., 6.],
[1., 1., 1., 1., 1., 1.]], dtype=float32)