8e23a3ec47a2ccbf6cdd222a80886c6b9f17264f,keras/initializers.py,VarianceScaling,__call__,#VarianceScaling#Any#Any#,201

Before Change

        if self.distribution == "normal":
            // 0.879... = scipy.stats.truncnorm.std(a=-2, b=2, loc=0., scale=1.)
            stddev = np.sqrt(scale) / .87962566103423978
            return K.truncated_normal(shape, 0., stddev,
                                      dtype=dtype, seed=self.seed)
        else:
            limit = np.sqrt(3. * scale)
            return K.random_uniform(shape, -limit, limit,
                                    dtype=dtype, seed=self.seed)

After Change

        if self.distribution == "normal":
            // 0.879... = scipy.stats.truncnorm.std(a=-2, b=2, loc=0., scale=1.)
            stddev = np.sqrt(scale) / .87962566103423978
            x = K.truncated_normal(shape, 0., stddev,
                                   dtype=dtype, seed=self.seed)
        else:
            limit = np.sqrt(3. * scale)
            x = K.random_uniform(shape, -limit, limit,
                                 dtype=dtype, seed=self.seed)

Instances