tf.compat.v1.scatter_max | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.scatter_max
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Reduces sparse updates into a variable reference using the max
operation.
tf.compat.v1.scatter_max(
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 = []
.
Args | |
---|---|
ref | A mutable Tensor. Must be one of the following types: half,bfloat16, float32, float64, int32, int64. Should be from aVariable 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). |
Returns |
---|
A mutable Tensor. Has the same type as ref. |