# tf.raw_ops.ResourceSparseApplyAdagradV2

<br />

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.ResourceSparseApplyAdagradV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/ResourceSparseApplyAdagradV2)

<br />

    tf.raw_ops.ResourceSparseApplyAdagradV2(
        var,
        accum,
        lr,
        epsilon,
        grad,
        indices,
        use_locking=False,
        update_slots=True,
        name=None
    )

That is for rows we have grad for, we update var and accum as follows:
accum += grad \* grad
var -= lr \* grad \* (1 / sqrt(accum))

<br />

<br />

<br />

| ## 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`. Learning rate. 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. |
| `indices` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A vector of indices into the first dimension of var and accum. |
| `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). |

<br />

<br />

<br />

<br />

| ## Returns ||
|---|---|
| The created Operation. ||

<br />