optimizer = dict(type='SGD', lr=0.015, momentum=0.9, weight_decay=0.0004, paramwise_options=dict(bias_lr_mult=2., bias_decay_mult=0.)) optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2)) learning policy lr_config = dict( policy='step', warmup='linear', warmup_ite...
# 需要导入模块: from config import config [as 别名]# 或者: from config.config importlr[as 别名]defaddOptimizerOp(self):withtf.variable_scope("trainAddOptimizer"): self.globalStep = tf.Variable(0, dtype = tf.int32, trainable =False, name ="globalStep")# init to 0 every run?optimizer ...
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