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proximal_ada_grad optimizer

This commit is contained in:
lilei 2020-06-15 11:29:08 +08:00
parent 36d9e353a5
commit 7e4bdf6add
1 changed files with 3 additions and 5 deletions
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8
mindspore/nn/optim/proximal_ada_grad.py
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@ -31,15 +31,13 @@ def _tensor_run_opt(opt, learning_rate, l1, l2, gradient, weight, accum):
return success
def _check_param_value(accum, learning_rate, l1, l2, use_locking, prim_name=None):
def _check_param_value(accum, l1, l2, use_locking, prim_name=None):
"""Check inputs param."""
validator.check_value_type("accum", accum, [float], prim_name)
validator.check_value_type("learning_rate", learning_rate, [float], prim_name)
validator.check_value_type("l1", l1, [float], prim_name)
validator.check_value_type("l2", l2, [float], prim_name)
validator.check_value_type("use_locking", use_locking, [bool], prim_name)
validator.check_number_range("accum", accum, 0.0, float("inf"), Rel.INC_LEFT, prim_name)
validator.check_number_range("learning_rate", learning_rate, 0.0, float("inf"), Rel.INC_LEFT, prim_name)
validator.check_number_range("l1", l1, 0.0, float("inf"), Rel.INC_LEFT, prim_name)
validator.check_number_range("l2", l2, 0.0, float("inf"), Rel.INC_LEFT, prim_name)
@ -79,10 +77,10 @@ class ProximalAdagrad(Optimizer):
def __init__(self, params, accum=0.1, learning_rate=0.001, l1=0.0, l2=0.0,
use_locking=False, loss_scale=1.0, weight_decay=0.0):
super(ProximalAdagrad, self).__init__(0.0, params, weight_decay, loss_scale)
super(ProximalAdagrad, self).__init__(learning_rate, params, weight_decay, loss_scale)
if self.is_group:
raise RuntimeError(f"The {self.cls_name} optimizer cannot support group setting.")
_check_param_value(accum, learning_rate, l1, l2, use_locking, self.cls_name)
_check_param_value(accum, l1, l2, use_locking, self.cls_name)
self.accum = self.parameters.clone(prefix="accum", init=accum)
self.l1 = Tensor(l1, mstype.float32)
self.l2 = Tensor(l2, mstype.float32)