Question

我正在尝试使用CNN然后使用LSTM训练MNIST图像。但是在训练中，我得到了上述错误。无法解决它错误：feed_dict [net_inputs [i]] = x IndexError：列表索引超出范围

from __future__ import division, print_function, absolute_import
import tensorflow as tf
tf.reset_default_graph()
import tflearn
import numpy as np
from tflearn.layers.core import input_data, dropout, fully_connected
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.normalization import local_response_normalization
from tflearn.layers.estimator import regression

# Data loading and preprocessing
import tflearn.datasets.mnist as mnist

X, Y, testX, testY = mnist.load_data(one_hot=True)
X = X.reshape([-1, 28, 28, 1])
testX = testX.reshape([-1, 28, 28, 1])

# Building convolutional network
network = input_data(shape=[None, 28, 28, 1], name='input')
network = conv_2d(network, 32, 3, activation='relu', regularizer="L2")
network = max_pool_2d(network, 2)
network = local_response_normalization(network)
network = conv_2d(network, 64, 3, activation='relu', regularizer="L2")
network = max_pool_2d(network, 2)
network = local_response_normalization(network)
network = fully_connected(network, 128, activation='tanh')
network = dropout(network, 0.8)
network = fully_connected(network, 256, activation='tanh')
network = dropout(network, 0.8)
network = fully_connected(network, 10, activation='softmax')
network = regression(network, optimizer='adam', learning_rate=0.01,
                 loss='categorical_crossentropy', name='target')

#lstm
net = tflearn.input_data(shape=[None, 28, 28])
network = tflearn.reshape(network,(-1, 28, 28))
net = tflearn.lstm(network, 128, return_seq=True)
net = tflearn.lstm(net, 128)
net = tflearn.fully_connected(net, 10, activation='softmax')
net = tflearn.regression(net, optimizer='adam',
                     loss='categorical_crossentropy', name='target')

#train
model = tflearn.DNN(net, tensorboard_verbose=2)
model.fit(X, Y, n_epoch=1, validation_set=0.1, show_metric=True,
snapshot_step=100)

重新启动内核也无济于事！

IndexError：列表索引超出CNN和LSTM实现MNIST的范围

0 个答案: