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:
A 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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