tf.scatter_max( ref, indices, updates, use_locking=False, name=None )
Defined in tensorflow/python/ops/gen_state_ops.py
.
See the guide: Variables > Sparse Variable Updates
Reduces sparse updates into a variable reference using the max
operation.
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 = []
.
ref
: A mutable Tensor
. Must be one of the following types: half
, bfloat16
, float32
, float64
, int32
, int64
. Should be from a Variable
node.indices
: A Tensor
. Must be one of the following types: int32
, int64
. A tensor of indices into the first dimension of ref
.updates
: A Tensor
. Must have the same type as ref
. A tensor of updated values to reduce into ref
.use_locking
: An optional bool
. Defaults to False
. If True, the update will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.name
: A name for the operation (optional).A mutable Tensor
. Has the same type as ref
.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/scatter_max