tf.raw_ops.ResourceApplyAdagradV2

Update '*var' according to the adagrad scheme.

Compat aliases for migration

tf.compat.v1.raw_ops.ResourceApplyAdagradV2

tf.raw_ops.ResourceApplyAdagradV2(
    var,
    accum,
    lr,
    epsilon,
    grad,
    use_locking=False,
    update_slots=True,
    name=None
)

accum += grad * grad var -= lr * grad * (1 / (sqrt(accum) + epsilon))

Args
`var`	A `Tensor` of type `resource`. Should be from a Variable().
`accum`	A `Tensor` of type `resource`. Should be from a Variable().
`lr`	A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `qint16`, `quint16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. Scaling factor. Must be a scalar.
`epsilon`	A `Tensor`. Must have the same type as `lr`. Constant factor. Must be a scalar.
`grad`	A `Tensor`. Must have the same type as `lr`. The gradient.
`use_locking`	An optional `bool`. Defaults to `False`. If `True`, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
`update_slots`	An optional `bool`. Defaults to `True`.
`name`	A name for the operation (optional).

Returns
The created Operation.

Args