tensorflow/core/api_def/base_api/api_def_ResourceSparseApplyAdagradV2.pbtxt

op {
  graph_op_name: "ResourceSparseApplyAdagradV2"
  visibility: HIDDEN
  in_arg {
    name: "var"
    description: <<END
Should be from a Variable().
END
  }
  in_arg {
    name: "accum"
    description: <<END
Should be from a Variable().
END
  }
  in_arg {
    name: "lr"
    description: <<END
Learning rate. Must be a scalar.
END
  }
  in_arg {
    name: "epsilon"
    description: <<END
Constant factor. Must be a scalar.
END
  }
  in_arg {
    name: "grad"
    description: <<END
The gradient.
END
  }
  in_arg {
    name: "indices"
    description: <<END
A vector of indices into the first dimension of var and accum.
END
  }
  attr {
    name: "use_locking"
    description: <<END
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.
END
  }
  summary: "Update relevant entries in \'*var\' and \'*accum\' according to the adagrad scheme."
  description: <<END
That is for rows we have grad for, we update var and accum as follows:
accum += grad * grad
var -= lr * grad * (1 / sqrt(accum))
END
}