TensorFlow:张量不是这个图的元素 [英] TensorFlow: The tensor is not the element of this graph

问题描述

#file for inputing the data for testing
from scipy import ndimage
image_file='test.png'
image_data = ndimage.imread(image_file).astype(float) 
image_data = image_data.reshape((-1, image_size * image_size)).astype(np.float32)
rst = tf.Graph()
with rst.as_default():
     result = tf.matmul(image_data, weights) + biases
     picko=tf.nn.softmax(result)
with tf.Session(graph=rst) as rsts:
     tf.global_variables_initializer().run()
     predictions = rsts.run([picko])

运行上述代码时出现以下错误.请给我建议一个我无法手动解决的解决方案.

When running the above code I am getting the below error .Please suggest me a solution I am not able to solve it manually .

ValueError: Fetch 参数不能解释为张量.(Tensor Tensor("Softmax_4:0", shape=(1, 10), dtype=float32) 不是这个图的元素.)

ValueError: Fetch argument cannot be interpreted as a Tensor. (Tensor Tensor("Softmax_4:0", shape=(1, 10), dtype=float32) is not an element of this graph.)

推荐答案

试试这个代码.

主要区别在于整个代码使用默认图形，没有使用创建的图形.

The main difference is that the whole code uses the default graph and none of it uses a created graph.

#file for inputing the data for testing
from scipy import ndimage
image_file = 'test.png'
image_data = ndimage.imread(image_file).astype(float) 
image_data = image_data.reshape((-1, image_size * image_size)).astype(np.float32)    
result = tf.matmul(image_data, weights) + biases
picko = tf.nn.softmax(result)
with tf.Session() as rsts:
     tf.global_variables_initializer().run()
     predictions = rsts.run([picko])

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