Deep learning 深度学习中jupyter笔记本中的tensorflow导入错误 我正在写一个tensorflow程序来寻找狗对猫的预测。当我试图在juypter笔记本中执行这个单元格时，这部分代码中出现了一个错误
2.代码如下：Deep learning 深度学习中jupyter笔记本中的tensorflow导入错误 我正在写一个tensorflow程序来寻找狗对猫的预测。当我试图在juypter笔记本中执行这个单元格时，这部分代码中出现了一个错误,deep-learning,Deep Learning,2.代码如下： import tflearn from tflearn.layers.conv import conv_2d, max_pool_2d from tflearn.layers.core import input_data, dropoutfully_connected from tflearn.layers.estimator import regression import tensorflow
import tflearn
from tflearn.layers.conv import conv_2d, max_pool_2d
from tflearn.layers.core import input_data, dropoutfully_connected
from tflearn.layers.estimator import regression
import tensorflow as tf
tf.reset_default_graph()
convnet = input_data(shape=[None, IMG_SIZE, IMG_SIZE, 1],name='input')
convnet = conv_2d(convnet, 32, 5, activation='relu')
convnet = max_pool_2d(convnet, 5)
convnet = conv_2d(convnet, 64, 5, activation='relu')
convnet = max_pool_2d(convnet, 5)
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=LR, loss='categorical_crossentropy', name='targets')
model = tflearn.DNN(convnet, tensorboard_dir='log')
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-6-2ef14dea0c38> in <module>()
----> 1 import tflearn
2 from tflearn.layers.conv import conv_2d, max_pool_2d
3 from tflearn.layers.core import input_data, dropout, fully_connected
4 from tflearn.layers.estimator import regression
5
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/__init__.py in <module>()
19
20 # Predefined ops
---> 21 from .layers import normalization
22 from . import metrics
23 from . import activations
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/layers/__init__.py in <module>()
8 from .normalization import batch_normalization, local_response_normalization
9 from .estimator import regression
---> 10 from .recurrent import lstm, gru, simple_rnn, bidirectional_rnn, \
11 BasicRNNCell, BasicLSTMCell, GRUCell
12 from .embedding_ops import embedding
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/layers/recurrent.py in <module>()
6 import tensorflow as tf
7 from tensorflow.python.ops import array_ops
----> 8 from tensorflow.contrib.rnn.python.ops.core_rnn import static_rnn as _rnn, \
9 static_bidirectional_rnn as _brnn
10 from tensorflow.python.ops.rnn import rnn_cell_impl as _rnn_cell, \
ModuleNotFoundError: No module named 'tensorflow.contrib.rnn.python.ops.core_rnn'
ModuleNotFoundError回溯（最近一次调用）
在（）
---->1导入tflearn
2从tflearn.layers.conv导入conv_2d、max_pool_2d
3从tflearn.layers.core导入输入数据，退出，完全连接
4从tflearn.layers.estimator导入回归
5.
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/__-init__;u.py in（）
19
20#预定义操作
--->21.从图层导入规范化
22从。导入度量
23来自。导入激活
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/layers/__-init___;u.py in（）
8.从规范化导入批处理规范化、本地响应规范化
9.估计量输入回归
--->10.来自经常性输入lstm、gru、简单、双向、\
11基本细胞，基本细胞，GRUCell
12.从嵌入操作导入嵌入
/home/aravind/anaconda3/lib/python3.6/site-packages/tflearn/layers/recurrent.py in（）
6导入tensorflow作为tf
7从tensorflow.python.ops导入数组
---->8从tensorflow.contrib.rnn.python.ops.core\u rnn导入静态作为\
9静态双向作为
10从tensorflow.python.ops.rnn导入rnn\u单元格\
ModuleNotFoundError:没有名为“tensorflow.contrib.rnn.python.ops.core\n”的模块