TensorFlow学习——tf.placeholder

函数原型:tf.placeholder(dtype, shape=None, name=None)

参数解释：

dtype: The type of elements in the tensor to be fed.(参数类型)
shape: The shape of the tensor to be fed (optional). If the shape is not
  specified, you can feed a tensor of any shape.（参数的shape）
name: A name for the operation (optional).

placeholder，中文意思是占位符，在tensorflow中类似于函数参数，运行时必须传入值。

下面复制官方文档中的示例:

x = tf.placeholder(tf.float32, shape=(1024, 1024))
y = tf.matmul(x, x)
with tf.Session() as sess:
    print(sess.run(y))  # ERROR: will fail because x was not fed.
    rand_array = np.random.rand(1024, 1024)
    print(sess.run(y, feed_dict={x: rand_array}))  # Will succeed.

从官方示例来看，placeholder一定要在运行时候feed值。

下面看另一个示例：

x = tf.placeholder(tf.float32, [None, 784])

这个None,代表可以动态放入任意维数.