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Divides a variable reference by sparse updates.
tf.compat.v1.scatter_div(
ref, indices, updates, use_locking=False, name=None
)
This operation computes
# Scalar indices
ref[indices, ...] /= updates[...]
# Vector indices (for each i)
ref[indices[i], ...] /= updates[i, ...]
# High rank indices (for each i, ..., j)
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 divide.
Requires updates.shape = indices.shape + ref.shape[1:]
or updates.shape =
[]
.
Args | |
---|---|
ref
|
A mutable Tensor . Must be one of the following types: float32 ,
float64 , int32 , uint8 , int16 , int8 , complex64 , int64 ,
qint8 , quint8 , qint32 , bfloat16 , uint16 , complex128 , half ,
uint32 , uint64 . 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 values
that ref is divided by.
|
use_locking
|
An optional bool . Defaults to False . If True, the operation
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 .
|