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!14634 fix mindspore.common.initializer.Normal 

From: @wudenggang
Reviewed-by: @kingxian,@zhoufeng54
Signed-off-by: @kingxian
This commit is contained in:
mindspore-ci-bot 2021-04-13 11:03:02 +08:00 committed by Gitee
parent 18e97fd078 696d80607d
commit a83c3dbce6
1 changed files with 6 additions and 4 deletions
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10
mindspore/common/initializer.py
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@ -366,25 +366,27 @@ class Uniform(Initializer):
@_register() @_register()
class Normal(Initializer): class Normal(Initializer):
""" """
Initialize a normal array, and obtain values N(0, sigma) from the uniform distribution Initialize a normal array, and obtain values N(sigma, mean) from the normal distribution
to fill the input tensor. to fill the input tensor.
Args: Args:
sigma (float): The sigma of the array. Default: 0.01. sigma (float): The sigma of the array. Default: 0.01.
mean (float): The mean of the array. Default: 0.0.
Returns: Returns:
Array, normal array. Array, normal array.
""" """
def __init__(self, sigma=0.01): def __init__(self, sigma=0.01, mean=0.0):
super(Normal, self).__init__(sigma=sigma) super(Normal, self).__init__(sigma=sigma, mean=mean)
self.sigma = sigma self.sigma = sigma
self.mean = mean
def _initialize(self, arr): def _initialize(self, arr):
seed, seed2 = self.seed seed, seed2 = self.seed
output_tensor = Tensor(np.zeros(arr.shape, dtype=np.float32)) output_tensor = Tensor(np.zeros(arr.shape, dtype=np.float32))
random_normal(0, self.sigma, arr.shape, seed, seed2, output_tensor) random_normal(0, self.sigma, arr.shape, seed, seed2, output_tensor)
output_data = output_tensor.asnumpy() output_data = output_tensor.asnumpy()
output_data *= self.sigma output_data = output_data * self.sigma + self.mean
_assignment(arr, output_data) _assignment(arr, output_data)
@_register() @_register()