在莫烦Python教程的“Dropout 解决 overfitting”一节中,出现错误如下:

InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]

runfile('E:/python/kerasTest/tfDropoutTest9.py', wdir='E:/python/kerasTest')
C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\sklearn\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
"This module will be removed in 0.20.", DeprecationWarning) runfile('E:/python/kerasTest/tfDropoutTest9.py', wdir='E:/python/kerasTest')
Traceback (most recent call last): File "<ipython-input-2-64f3a3bcd083>", line 1, in <module>
runfile('E:/python/kerasTest/tfDropoutTest9.py', wdir='E:/python/kerasTest') File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
execfile(filename, namespace) File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace) File "E:/python/kerasTest/tfDropoutTest9.py", line 67, in <module>
train_result = sess.run(merged,feed_dict={xs:X_train,ys:y_train,keep_prob:1}) File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 895, in run
run_metadata_ptr) File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1128, in _run
feed_dict_tensor, options, run_metadata) File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1344, in _do_run
options, run_metadata) File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1363, in _do_call
raise type(e)(node_def, op, message) InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]
[[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]] Caused by op 'Placeholder_1', defined at:
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 241, in <module>
main()
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 237, in main
kernel.start()
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tornado\ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2698, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2808, in run_ast_nodes
if self.run_code(code, result):
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\IPython\core\interactiveshell.py", line 2862, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-1-64f3a3bcd083>", line 1, in <module>
runfile('E:/python/kerasTest/tfDropoutTest9.py', wdir='E:/python/kerasTest')
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "E:/python/kerasTest/tfDropoutTest9.py", line 39, in <module>
ys = tf.placeholder(tf.float32,[None,10])
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1680, in placeholder
return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 4105, in _placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 3160, in create_op
op_def=op_def)
File "C:\Users\Admin\AppData\Local\conda\conda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1625, in __init__
self._traceback = self._graph._extract_stack() InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]
[[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

代码如下:

import tensorflow as tf
from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import LabelBinarizer #load data
digits = load_digits()
X = digits.data#从0到9的图片
y = digits.target
y =LabelBinarizer().fit_transform(y)
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=.3) def add_layer(inputs,in_size,out_size,layer_name,activation_function=None):
#add one more layer and return the output of this layer
Weights = tf.Variable(tf.random_normal([in_size,out_size]))
biases = tf.Variable(tf.zeros([1, out_size]) + 0.1)
Wx_plus_b = tf.matmul(inputs, Weights) + biases
Wx_plus_b = tf.nn.dropout(Wx_plus_b,keep_prob)
if activation_function is None:
outputs = Wx_plus_b
else:
outputs = activation_function(Wx_plus_b)
tf.summary.histogram(layer_name+'/outputs',outputs)
return outputs xs = tf.placeholder(tf.float32,[None,64])#8*8
ys = tf.placeholder(tf.float32,[None,10])
keep_prob = tf.placeholder(tf.float32) #add output layer
l1 = add_layer(xs,64,50,'l1',activation_function=tf.nn.tanh)
prediction = add_layer(l1,50,10,'l2',activation_function=tf.nn.softmax) #the loss between prediction and real data
cross_entropy = tf.reduce_mean(-tf.reduce_sum(ys * tf.log(prediction),
reduction_indices=[1]))#loss
tf.summary.scalar('loss',cross_entropy)
train_step = tf.train.GradientDescentOptimizer(0.6).minimize(cross_entropy) sess = tf.Session()
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter("logs/train",sess.graph)
test_writer = tf.summary.FileWriter("logs/test",sess.graph) sess.run(tf.global_variables_initializer()) for i in range(500):
sess.run(train_step,feed_dict={xs:X_train,ys:y_train,keep_prob:0.5})
if i % 50 == 0:
train_result = sess.run(merged,feed_dict={xs:X_train,ys:y_train,keep_prob:1})
test_result = sess.run(merged,feed_dict={xs:X_test,ys:y_test,keep_prob:1})
train_writer.add_summary(train_result,i)
test_writer.add_summary(test_result,i)

原因:

在feed_dict中没有加入keep_prob的key和value

sess.run(train_step,feed_dict={xs:X_train,ys:y_train,keep_prob:0.5})中,没有写入keep_prob:0.5

造成feed_dict和placeholder的对应问题,但改正后,仍报该错误。反复检查了几遍,并没有发现问题。

最后实在无解,关闭了Spyder和anaconda,再打开anaconda和Spyder,居然可以正常运行了。。

但是也只是第一次可以正常运行,当删了生成的log文件,再次运行时,仍报该错误..至于为什么第二次运行就又报错仍未解决。

虽然问题不大,但是改了feed_dict后,问题还是没能解决,被困扰了一天,因此记录一下。

InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]的更多相关文章

  1. tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'x_1' with dtype float and shape [?,227,227,3]

    记一次超级蠢超级折磨我的bug. 报错内容: tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a ...

  2. Tensorflow报错:InvalidArgumentError: You must feed a value for placeholder tensor 'input_y' with dtype

    此错误神奇之处是每次第一次运行不会报错,第二次.第三次第四次....就都报错了.关掉重启,又不报错了,运行完再运行一次立马报错!搞笑! 折磨了我半天,终于被我给解决了! 问题解决来源于这边博客:htt ...

  3. 关于placeholder中 文字添加换行 用转义字符&#13;&#10;代替<br>

    今天遇到一个问题 UI给的效果图中 文本域的提示文字 是两行显示, 于是就想到placeholder中能否解析html标签, 尝试后发现并无卵用, 经过调查后发现 可以用转义字符代替<br> ...

  4. typeError:The value of a feed cannot be a tf.Tensor object.Acceptable feed values include Python scalars,strings,lists.numpy ndarrays,or TensorHandles.For reference.the tensor object was Tensor...

    如上贴出了:错误信息和错误代码. 这个问题困扰了自己两天,报错大概是说输入的数据和接受的格式不一样,不能作为tensor. 后来问了大神,原因出在tf.reshape(),因为网络训练时用placeh ...

  5. InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [2048,38] rhs shape= [2048,2]

    做tensorflow object detection 中,清空下checkpoint就可以啦

  6. tensorflow ValueError: Cannot feed value of shape (5000,) for Tensor 'output:0', which has shape '(?, 10)'

    提供的训练数据和定义的模型之间的维度不对应. 在MNIST手写数字识别时,在 mnist = input_data.read_data_sets("MNIST_data/") 中, ...

  7. 实战Google深度学习框架-C3-TensorFlow入门

    第三章:TensorFlow入门 TensorFlow存在计算模型,数据模型和运算模型(本文用TF代表TensorFlow) 3.1 计算模型-计算图 3.1.1 计算图的概念 TensorFlow这 ...

  8. 使用TensorFlow的卷积神经网络识别自己的单个手写数字,填坑总结

    折腾了几天,爬了大大小小若干的坑,特记录如下.代码在最后面. 环境: Python3.6.4 + TensorFlow 1.5.1 + Win7 64位 + I5 3570 CPU 方法: 先用MNI ...

  9. [2] TensorFlow 向前传播算法(forward-propagation)与反向传播算法(back-propagation)

    TensorFlow Playground http://playground.tensorflow.org 帮助更好的理解,游乐场Playground可以实现可视化训练过程的工具 TensorFlo ...

随机推荐

  1. Cocos2DX开发:记录遇到的一些问题和解决方法

    今天看了一下以前学习cocos2dx时记录的一些笔记,主要是在实际中遇到的一些问题,整理了一下,就成为了这篇文章,便于自己以后查找,也为一些新手提供点经验. 这篇文章会一直更新,将自己之后开发中遇到的 ...

  2. LintCode——颜色分类

    颜色分类:给定一个包含红,白,蓝且长度为 n 的数组,将数组元素进行分类使相同颜色的元素相邻,并按照红.白.蓝的顺序进行排序. 我们可以使用整数 0,1 和 2 分别代表红,白,蓝. 注意事项: 不能 ...

  3. python虚拟环境管理之virtualenv,virtualenvwrapper,pipenv,conda

    虚拟环境的作用 使python环境拥有独立的包,避免污染原本的python环境.为不同的项目创建不同的环境可以避免安装的库过于庞大和相互干扰. 例如你想在同一台机器上开发用python2和python ...

  4. 会了这十种Python优雅的写法,让你工作效率翻十倍,一人顶十人用!

      我们都知道,Python 的设计哲学是「优雅」.「明确」.「简单」.这也许很多人选择 Python 的原因.但是我收到有些伙伴反馈,他写的 Python 并不优雅,甚至很臃肿,那可能是你的姿势不对 ...

  5. notion笔记

    不错的笔记应用, 模式新颖, 正在使用, 如有相同使用者可以入群交流 notion QQ群 725638123

  6. linux 其他知识目录

    博客目录总纲首页 为博客园添加目录的方法总结 linux 命令自动补全包 手动配置网卡 nginx日志统计 Linux 深入理解inode/block/superblock /proc/sys目录下各 ...

  7. maven实战读书笔记(三)

    maven将一系列的步骤都封装为一系列的插件,运行命令后一系列的插件运行

  8. [buaa-SE-2017]个人作业-week3

    个人作业-week3:案例分析 分析产品:Bing词典 Part1:调研&评测 1.软件评测和Bug汇报 这次我选择Bing词典的原因是在于,首先我使用过的词典软件较多,平台涵盖PC端.网站. ...

  9. Task 4.3 求环形数组的最大子数组和

    任务要求:输入一个整形数组,数组里有正数也有负数. 数组中连续的一个或多个整数组成一个子数组,每个子数组都有一个和.    如果数组A[0]……A[j-1]首尾相邻,允许A[i-1], …… A[n- ...

  10. flownet2.0 caffe anaconda2 编译安装

    1. 下载flownet2.0源码到指定目录 cd /home/zzq/saliency_models/deep_optical_flow git clone https://github.com/l ...