tensorflow::ops::ScatterMin

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

Summary

This operation computes

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

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

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

Arguments:

• scope: A Scope object
• ref: Should be from a Variable node.
• indices: A tensor of indices into the first dimension of ref.
• updates: A tensor of updated values to reduce into ref.

Optional attributes (see Attrs):

• use_locking: If True, the update will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.

Returns:

• Output: = Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.

Public attributes

Operation operation

::tensorflow::Output output_ref

 ScatterMin(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input ref,
  ::tensorflow::Input indices,
  ::tensorflow::Input updates
)

 ScatterMin(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input ref,
  ::tensorflow::Input indices,
  ::tensorflow::Input updates,
  const ScatterMin::Attrs & attrs
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const 

Attrs UseLocking(
  bool x
)