tf.ones(shape, dtype=dtypes.float32, name=None) 初始化元素为1
tf.zeros(shape, dtype=dtypes.float32, name=None) 初始化元素为0
tf.ones_like(tensor, dtype=None, name=None, optimize=True) 初始化元素为1，形状与指定tensor相同的张量
tf.zeros_like(tensor, dtype=None, name=None, optimize=True) 初始化元素为0，形状与指定tensor相同的张量
tf.fill(dims, value, name=None) dims指定张量形状，填充值为value
tf.constant(value, dtype=None, shape=None, name="Const", verify_shape=False) 创建常量tensor
tf.random_normal(shape, mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None) 根据正态分布生成随机张量，mean是均值，stddev是标准差，seed是随机种子
tf.truncated_normal(shape, mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)
tf.random_uniform(shape, minval=0, maxval=None, dtype=tf.float32, seed=None, name=None)
tf.lin_space(start, stop, num, name=None)
tf.range(start, limit=None, delta=1, dtype=None, name="range")
