07e464d81392c4e918e8c0f394793449866b0166,tensorpack/models/layer_norm.py,,InstanceNorm,#,67

Before Change

    mean, var = tf.nn.moments(x, axis, keep_dims=True)

    if not use_affine:
        return tf.divide(x - mean, tf.sqrt(var + epsilon), name="output")

    beta = tf.get_variable("beta", [ch], initializer=tf.constant_initializer())
    beta = tf.reshape(beta, new_shape)
    if gamma_init is None:

After Change

        gamma = tf.get_variable("gamma", [ch], initializer=gamma_initializer)
        gamma = tf.reshape(gamma, new_shape)
    else:
        gamma = tf.ones([1, 1, 1, 1], name="gamma", dtype=x.dtype)
    ret = tf.nn.batch_normalization(x, mean, var, beta, gamma, epsilon, name="output")

    vh = ret.variables = VariableHolder()
    if scale:

Instances