我正在尝试根据自己的数据微调/重新训练InceptionV1模型。我本来可以
INFO:tensorflow:global step 1000: loss = 0.1833 (20.37 sec/step) INFO:tensorflow:Stopping Training.
INFO:tensorflow:Finished training! Saving model to disk. INFO:tensorflow:Scale of 0 disables regularizer.
WARNING:tensorflow:From eval_image_classifier.py:157: streaming_recall_at_k (from tensorflow.contrib.metrics.python.ops.metric_ops) is deprecated and will be removed after 2016-11-08. Instructions for updating: Please use streaming_sparse_recall_at_k, and reshape labels from [batch_size] to [batch_size, 1].
INFO:tensorflow:Evaluating /tmp/flowers-models/inception_v1/all/model.ckpt-1000
INFO:tensorflow:Starting evaluation at 2017-04-26-14:59:28 INFO:tensorflow:Restoring parameters from /tmp/flowers-models/inception_v1/all/model.ckpt-1000
INFO:tensorflow:Evaluation [1/4]
INFO:tensorflow:Evaluation [2/4]
INFO:tensorflow:Evaluation [3/4]
INFO:tensorflow:Evaluation [4/4]
2017-04-26 20:30:23.505265: I tensorflow/core/kernels/logging_ops.cc:79] eval/Recall_5[1]
2017-04-26 20:30:23.505420: I tensorflow/core/kernels/logging_ops.cc:79] eval/Accuracy[1]
INFO:tensorflow:Finished evaluation at 2017-04-26-15:00:23
4.培训过程中产生了许多检查点,两个graph.pbtxt文件。根据讨论here,我使用了卡住工具中的最新检查点和graph.pbtxt文件并生成了一个.pb文件,我使用了以下参数
以下是我对ClassifierActivity.java所做的更改
请帮助我了解如何解决此问题。
最佳答案
Here是创建的网络的输入,因此如果可以添加
images = tf.identity(images,name ='Inputs')来命名网络的张量。
关于machine-learning - 微调/重新训练inceptionV1 slim 模型时,在“图形中没有名为[输入]的操作”错误,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/43647446/