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"]()]]

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)