一开始没看懂stddev是什么参数，找了一下，在tensorflow/python/ops里有random_ops，其中是这么写的：
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def random_normal(shape, mean=0.0, stddev=1.0, dtype=types.float32, seed=None, name=None): """Outputs random values from a normal distribution. Args: shape: A 1-D integer Tensor or Python array. The shape of the output tensor. mean: A 0-D Tensor or Python value of type `dtype`. The mean of the normal distribution. stddev: A 0-D Tensor or Python value of type `dtype`. The standard deviation of the normal distribution. dtype: The type of the output. seed: A Python integer. Used to create a random seed for the distribution. See [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed) for behavior. name: A name for the operation (optional). Returns: A tensor of the specified shape filled with random normal values. """ |
也就是按照正态分布初始化权重，mean是正态分布的平均值，stddev是正态分布的标准差（standard deviation），seed是作为分布的random seed（随机种子，我百度了一下，跟什么伪随机数发生器还有关，就是产生随机数的），在mnist/concolutional中seed赋值为66478，挺有意思，不知道是什么原理。
后面还有truncated_normal的定义：
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def truncated_normal(shape, mean=0.0, stddev=1.0, dtype=types.float32, seed=None, name=None): """Outputs random values from a truncated normal distribution. The generated values follow a normal distribution with specified mean and standard deviation, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked. Args: shape: A 1-D integer Tensor or Python array. The shape of the output tensor. mean: A 0-D Tensor or Python value of type `dtype`. The mean of the truncated normal distribution. stddev: A 0-D Tensor or Python value of type `dtype`. The standard deviation of the truncated normal distribution. dtype: The type of the output. seed: A Python integer. Used to create a random seed for the distribution. See [`set_random_seed`](../../api_docs/python/constant_op.md#set_random_seed) for behavior. name: A name for the operation (optional). Returns: A tensor of the specified shape filled with random truncated normal values. """ |
截断正态分布，以前都没听说过。
TensorFlow还提供了平均分布等。
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原文链接：https://www.cnblogs.com/dcsds1/p/5203764.html
