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  • tf.placeholder

    tf.placeholder

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

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

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

    在构建graph的过程中,tensor是没有实际数据的,只是表达计算过程,那么通过placeholder函数对tensor变量进行占位表示。然后在Session执行过程中,通过feed_dict对占位的tensor进行feed值

    Args:

    • dtype: The type of elements in the tensor to be fed.指定数据类型
    • shape: The shape of the tensor to be fed (optional). If the shape is not specified, you can feed a tensor of any shape.指定tensor的维度,如果没有指定,可以feed任意维度的tensor
    • name: A name for the operation (optional).

    Returns:

    Tensor that may be used as a handle for feeding a value, but not evaluated directly.

    Raises:

    • RuntimeError: if eager execution is enabled
     
     1 import tensorflow as tf
     2 import numpy as np
     3 
     4                                                                 
     5 x = tf.placeholder(tf.float32, shape=(1024, 1024))
     6 y = tf.matmul(x, x)
     7 
     8 with tf.Session() as sess:
     9   #print(sess.run(y))  # ERROR: will fail because x was not fed.
    10   rand_array = np.random.rand(1024, 1024)
    11   print(sess.run(y, feed_dict={x: rand_array}))  # Will succeed.


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  • 原文地址:https://www.cnblogs.com/black-mamba/p/9108137.html
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