tf.raw_ops.SparseApplyAdadelta

var: Should be from a Variable().

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.SparseApplyAdadelta

tf.raw_ops.SparseApplyAdadelta(
    var, accum, accum_update, lr, rho, epsilon, grad, indices, use_locking=False,
    name=None
)

Args
var	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.
accum	A mutable Tensor. Must have the same type as var. Should be from a Variable().
accum_update	A mutable Tensor. Must have the same type as var. Should be from a Variable().
lr	A Tensor. Must have the same type as var. Learning rate. Must be a scalar.
rho	A Tensor. Must have the same type as var. Decay factor. Must be a scalar.
epsilon	A Tensor. Must have the same type as var. Constant factor. Must be a scalar.
grad	A Tensor. Must have the same type as var. 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.
name	A name for the operation (optional).

Returns
A mutable Tensor. Has the same type as var.