Python 获取参数<；tf.张量'；批次：0'；形状=（128,56,56,3）数据类型=浮动32>；不能解释为张量。

我写了一个测试代码，当我运行它时，它说Fetch参数不能被解释为张量。我真的不知道发生了什么。有人能告诉我如何修复它吗？非常感谢。这是密码

# coding=utf-8
from  color_1 import read_and_decode, get_batch, get_test_batch
import color_inference
import cv2
import os
import time
import numpy as np
import tensorflow as tf
import color_train
import math

EVAL_INTERVAL_SECS=10
batch_size=128
num_examples = 10000
crop_size=56
def test(test_x, test_y):
    with tf.Graph().as_default() as g:
        image_holder = tf.placeholder(tf.float32, [batch_size, 56, 56, 3], name='x-input')
        label_holder = tf.placeholder(tf.int32, [batch_size], name='y-input')

        y=color_inference.inference(image_holder)

        num_iter = int(math.ceil(num_examples / batch_size))
        true_count = 0
        total_sample_count = num_iter * batch_size
        saver=tf.train.Saver()
        top_k_op = tf.nn.in_top_k(y, label_holder, 1)
        while True:
            with tf.Session() as sess:
                ckpt=tf.train.get_checkpoint_state(color_train.MODEL_SAVE_PATH)
                if ckpt and ckpt.model_checkpoint_path:
                    saver.restore(sess,ckpt.model_checkpoint_path)
                    global_step=ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]
                    image_batch, label_batch = sess.run([test_x, test_y])
                    predictions = sess.run([top_k_op], feed_dict={image_holder: image_batch,
                                                                  label_holder: label_batch})
                    true_count += np.sum(predictions)
                    precision = true_count * 1.0 / total_sample_count
                    print("After %s training step,the prediction is :%g",global_step,precision)
                else:
                    print('No checkpoint file found')
                    return
            time.sleep(EVAL_INTERVAL_SECS)

def main(argv=None):
    test_image, test_label = read_and_decode('val.tfrecords')
    test_images, test_labels = get_test_batch(test_image, test_label, batch_size, crop_size)
    test(test_images, test_labels)

if __name__=='__main__':
    tf.app.run()

错误在这里：

File "/home/vrview/tensorflow/example/char/tfrecords/color_test.py", line 57, in <module>
    tf.app.run()
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "/home/vrview/tensorflow/example/char/tfrecords/color_test.py", line 54, in main
    test(test_images, test_labels)
  File "/home/vrview/tensorflow/example/char/tfrecords/color_test.py", line 39, in test
    image_batch, label_batch = sess.run([test_x, test_y])
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run
    run_metadata_ptr)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 952, in _run
    fetch_handler = _FetchHandler(self._graph, fetches, feed_dict_string)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 408, in __init__
    self._fetch_mapper = _FetchMapper.for_fetch(fetches)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 230, in for_fetch
    return _ListFetchMapper(fetch)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 337, in __init__
    self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 238, in for_fetch
    return _ElementFetchMapper(fetches, contraction_fn)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 274, in __init__
    'Tensor. (%s)' % (fetch, str(e)))
ValueError: Fetch argument <tf.Tensor 'batch:0' shape=(128, 56, 56, 3) dtype=float32> cannot be interpreted as a Tensor. (Tensor Tensor("batch:0", shape=(128, 56, 56, 3), dtype=float32) is not an element of this graph.)

文件“/home/vrview/tensorflow/example/char/tfrecords/color_test.py”，第57行，在
tf.app.run（）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/platform/app.py”，第44行，正在运行
_系统出口（主（_sys.argv[：1]+标志_passthrough））
文件“/home/vrview/tensorflow/example/char/tfrecords/color_test.py”，第54行，在main中
测试（测试图像、测试标签）
文件“/home/vrview/tensorflow/example/char/tfrecords/color_test.py”，第39行，测试中
image\u batch，label\u batch=sess.run（[test\u x，test\u y]）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第767行，正在运行
运行_元数据_ptr）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第952行，正在运行
fetch\u handler=\u FetchHandler（self.\u图形、fetches、feed\u dict\u字符串）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第408行，在__
self.\u fetch\u mapper=\u FetchMapper.for\u fetch（fetches）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第230行，用于获取
return\u ListFetchMapper（fetch）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第337行，在__
self._mappers=[_FetchMapper.for_fetch（fetch）for fetch in fetches]
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第238行，for_fetch
return\u ElementFetchMapper（fetches，contraction\u fn）
文件“/home/vrview/tensorflow/local/lib/python2.7/site packages/tensorflow/python/client/session.py”，第274行，在__
张量。（%s）'（提取，str（e）））
ValueError:无法将Fetch参数解释为张量。（张量张量（“批次：0”，形状=（128,56,56,3），dtype=float32）不是此图的元素。）

您关注错误消息的错误部分。相关部分是

张量不是这个图的一个元素

问题在于，您在函数

test

中创建了一个图形

g

，该图形与创建占位符

test_x

和

test_y

作为参数提供的图形不同

最简单的解决方案是在

main

中创建图形

g

def main(argv=None):
    test_image, test_label = read_and_decode('val.tfrecords')
    with tf.Graph().as_default():
        test_images, test_labels = get_test_batch(test_image, test_label,
                                                  batch_size, crop_size)
        test(test_images, test_labels)

---

很抱歉我尝试了你说的话，但还是错了。我得到了同样的错误。你意识到它在“image\u batch，label\u batch=sess.run（[test\u x，test\u y]）”一行中说的错误了吗？你是否用tf.Graph（）删除了

。在
test
中作为g
默认值（）？是的，当然。我尝试了这两个，但仍然不起作用。我认为这行“image\u batch，label\u batch=sess.run（[test\u x，test\y]）”是错误的关键，但我不知道如何解决，您是否也在
读取和解码中创建了任何tensorflow对象？另一个原因可能是您实际如何定义
测试x
和
测试y
，但代码缺失。请加上。我也有同样的问题。我没能在不同的功能中将构建图和运行图分开。无论如何，如果需要更改图形中的任何内容，可以使用占位符。另一个解决方法是保存图形并执行初始操作