tf.placeholder()用法

最新推荐文章于 2023-10-22 23:40:14 发布

KAila_Lucky

最新推荐文章于 2023-10-22 23:40:14 发布

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文章标签： TensorFlow

本文详细介绍了TensorFlow中Placeholder的功能和使用方法，解释了如何在计算图中预留位置供外部输入数据，并通过实例演示了其在矩阵乘法运算中的应用。

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感谢：https://tensorflow.google.cn/api_docs/python/tf/placeholder

tf.placeholder(
    dtype,
    shape=None,
    name=None
)

Inserts a placeholder for a tensor that will be always fed.

placeholder是TensorFlow中的占位符，暂时存储变量。TensorFlow如果要从外部传入数据，需要用tf.placeholder()

Important: This tensor will produce an error if evaluated. Its value must be fed using the feed_dictoptional argument to Session.run(), Tensor.eval(), or Operation.run().

需要注意的是：placeholder（）和sess.run(***,feed_dict={input1 : ***,input2 : ***})绑定了，必须要用这种形式传输数据。

For example:

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.

Args:

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