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batchnormalization.py
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batchnormalization.py
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import numpy as np
def batchnorm_forward(x, gamma, beta, bn_param):
mode = bn_param["mode"]
eps = 1e-5
momentum = 0.9
N, D = x.shape
running_mean = bn_param.get("running_mean", np.zeros(D, dtype=x.dtype))
running_var = bn_param.get("running_var", np.zeros(D, dtype=x.dtype))
out, cache = None, None
if mode == 'train':
# TODO: 实现训练过程中batch normalization层的前向传播
# ******请在此段内填写代码(开始)******#
pass
# ******请在此段内填写代码(结束)******#
elif mode == 'test':
# TODO: 实现测试过程中batch normalization层的前向传播
# ******请在此段内填写代码(开始)******#
pass
# ******请在此段内填写代码(结束)******#
else:
raise ValueError('ValueError: Batch Normalization mode "%s", only accept for "train" or "test". ' % mode)
bn_param["running_mean"] = running_mean
bn_param["running_var"] = running_var
return out, cache
def batchnorm_backward(dout, cache):
dx, dgamma, dbeta = None, None, None
# TODO: 实现batch normalization层的反向传播,将结果保存在dx, dgamma, dbeta三个变量中
# ******请在此段内填写代码(开始)******#
pass
# ******请在此段内填写代码(结束)******#
return dx, dgamma, dbeta