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@@ -166,7 +166,8 @@ class Adam(Optimizer): |
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""" |
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""" |
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def __init__(self, params, learning_rate=1e-3, beta1=0.9, beta2=0.999, eps=1e-8, use_locking=False, |
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def __init__(self, params, learning_rate=1e-3, beta1=0.9, beta2=0.999, eps=1e-8, use_locking=False, |
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use_nesterov=False, weight_decay=0.0, loss_scale=1.0): |
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use_nesterov=False, weight_decay=0.0, loss_scale=1.0, |
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decay_filter=lambda x: 'beta' not in x.name and 'gamma' not in x.name): |
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super(Adam, self).__init__(learning_rate, params) |
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super(Adam, self).__init__(learning_rate, params) |
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_check_param_value(beta1, beta2, eps, weight_decay) |
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_check_param_value(beta1, beta2, eps, weight_decay) |
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validator.check_type("use_locking", use_locking, [bool]) |
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validator.check_type("use_locking", use_locking, [bool]) |
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@@ -192,6 +193,7 @@ class Adam(Optimizer): |
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self.moment1 = self.parameters.clone(prefix="moment1", init='zeros') |
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self.moment1 = self.parameters.clone(prefix="moment1", init='zeros') |
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self.moment2 = self.parameters.clone(prefix="moment2", init='zeros') |
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self.moment2 = self.parameters.clone(prefix="moment2", init='zeros') |
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self.decay_tf = tuple(decay_filter(x) for x in self.parameters) |
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self.hyper_map = C.HyperMap() |
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self.hyper_map = C.HyperMap() |
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self.opt = P.Adam(use_locking, use_nesterov) |
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self.opt = P.Adam(use_locking, use_nesterov) |
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self.weight_decay = weight_decay * loss_scale |
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self.weight_decay = weight_decay * loss_scale |
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