TensorFlow中权重的随机初始化的方法

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. """

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. """