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感谢您为我的问题挤出时间来帮我解决，我表示由衷的感谢！ 在tensorflow框架下，我将您的代码放入到resnet vgg-16 NIN模型中来对cifar-10数据集进行分类，发现训练的时候损失为nan以及验证集准确率一直为0.1。请问您知道是什么原因吗？下面这是我的tensorflow代码 channels = inputs.get_shape().as_list()[-1] scales1 = Conv2D(channels,kernel_size=3, strides=1, padding="same")(inputs) scales1 = BatchNormalization()(scales1) return tf.maximum(inputs,scales1)
channels = inputs.get_shape().as_list()[-1] scales1 = Conv2D(channels,kernel_size=3, strides=1, padding="same")(inputs) scales1 = BatchNormalization()(scales1) return tf.maximum(inputs,scales1)
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感谢您为我的问题挤出时间来帮我解决，我表示由衷的感谢！
在tensorflow框架下，我将您的代码放入到resnet vgg-16 NIN模型中来对cifar-10数据集进行分类，发现训练的时候损失为nan以及验证集准确率一直为0.1。请问您知道是什么原因吗？下面这是我的tensorflow代码
channels = inputs.get_shape().as_list()[-1] scales1 = Conv2D(channels,kernel_size=3, strides=1, padding="same")(inputs) scales1 = BatchNormalization()(scales1) return tf.maximum(inputs,scales1)The text was updated successfully, but these errors were encountered: