tf.raw_ops.ResourceSparseApplyAdagradDA

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

var A Tensor of type resource. Should be from a Variable().
gradient_accumulator A Tensor of type resource. Should be from a Variable().
gradient_squared_accumulator A Tensor of type resource. Should be from a Variable().
grad A 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. 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.
lr A Tensor. Must have the same type as grad. Learning rate. Must be a scalar.
l1 A Tensor. Must have the same type as grad. L1 regularization. Must be a scalar.
l2 A Tensor. Must have the same type as grad. L2 regularization. Must be a scalar.
global_step A Tensor of type int64. Training step number. Must be a scalar.
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).

The created Operation.