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我是张量流的新手。我正在使用 Tflearn 训练我的图像以对眼睛状态进行分类。在最初阶段，现在，我有 400 个训练图像和 200 个验证图像。我正在使用 image_preloader 在我的脚本中获取自定义图像输入。我认为它加载图像成功显示：

tflearn.data_utils.ImagePreloader 对象位于 0x7fa28f3a5310

但是在训练时划分和获取批次时会引起问题，

给出 Traceback 错误为

Traceback (most recent call last):
  File "tflearn_custom.py", line 181, in <module>
    model.fit(x,y,validation_set=({'input':test_x},{'targets':test_y}),n_epoch=10,batch_size=10)
  File "/usr/local/lib/python2.7/dist-packages/tflearn/models/dnn.py", line 215, in fit
    callbacks=callbacks)
  File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 285, in fit
    self.summ_writer, self.coord)
  File "/usr/local/lib/python2.7/dist-packages/tflearn/helpers/trainer.py", line 709, in initialize_fit
    self.n_train_samples = len(get_dict_first_element(feed_dict))
TypeError: object of type 'Tensor' has no len()

这是我的代码：

import tflearn 
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.core import input_data, dropout,fully_connected
from tflearn.layers.estimator import regression 
import tensorflow as tf
from tflearn.data_utils import image_preloader

test_filename='/path_to_validating_set/'
train_filename='/path_to_training_set/'


x, y = image_preloader(train_filename, image_shape=(128, 128),  mode='folder',  grayscale=True, categorical_labels=True,   normalize=True)
test_x, test_y = image_preloader(test_filename, image_shape=(128, 128),   mode='folder', grayscale=True, categorical_labels=True,   normalize=True)

convnet =input_data(shape=[None, 128,128,1], name='input')  
convnet = conv_2d(convnet, 32, 2, activation='relu') 

convnet = max_pool_2d(convnet,2)

convnet = conv_2d(convnet, 64, 2, activation='relu')

convnet = max_pool_2d(convnet,2)

convnet = fully_connected(convnet, 1024, activation='relu')  

convnet = dropout(convnet, 0.8)

convnet = fully_connected(convnet, 2, activation='softmax')



convnet = regression(convnet, optimizer='adam', learning_rate=0.01, loss='categorical_crossentropy', name='targets')

model= tflearn.DNN(convnet)


model.fit(x,y,validation_set=({'input':test_x},{'targets':test_y}),n_epoch=5,batch_size=5)

我正在使用张量流 1.0。我已经尝试搜索类似的问题，但没有任何解决办法。

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1 回答 1

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我认为问题是feed_dict张量，类型的对象Tensor没有长度。您可以使用feed_dict.shape[0]它来获取它的长度。

于 2018-05-31T13:39:40.750 回答