tf.raw_ops.ScatterMax

Reduces sparse updates into a variable reference using the max operation.

tf.raw_ops.ScatterMax(
    ref, indices, updates, use_locking=False, name=None
)

This operation computes

# Scalar indices
ref[indices, ...] = max(ref[indices, ...], updates[...])

# Vector indices (for each i)
ref[indices[i], ...] = max(ref[indices[i], ...], updates[i, ...])

# High rank indices (for each i, ..., j)
ref[indices[i, ..., j], ...] = max(ref[indices[i, ..., j], ...], updates[i, ..., j, ...])

This operation outputs ref after the update is done. This makes it easier to chain operations that need to use the reset value.

Duplicate entries are handled correctly: if multiple indices reference the same location, their contributions combine.

Requires updates.shape = indices.shape + ref.shape[1:] or updates.shape = [].