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.
 """