我是python和tensorflow的新手，所以我做了一些测试和测试，但是关于张量板的例子，我遇到了以下问题：
runfile('D:/Sintítulo 8.py', wdir='D:')
Traceback (most recent call last):
File "<ipython-input-129-8074dce3c7b8>", line 1, in <module>
runfile('D:/Sintítulo 8.py', wdir='D:')
File "D:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "D:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "D:/Sintítulo 8.py", line 47, in <module>
_, losses, summary=sess.run([train, loss, Merged], feed_dict={X: x_data, Y: y_data})
File "D:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 895, in run
run_metadata_ptr)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1321, in _do_run
options, run_metadata)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
InvalidArgumentError: You must feed a value for placeholder tensor 'labels' with dtype float and shape [?,10]
[[Node: labels = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'labels', defined at:
File "D:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 241, in <module>
main()
File "D:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 237, in main
kernel.start()
File "D:\Anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "D:\Anaconda3\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "D:\Anaconda3\lib\site-packages\tornado\ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "D:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "D:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "D:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "D:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "D:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "D:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "D:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "D:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "D:\Anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "D:\Anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "D:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2698, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "D:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2808, in run_ast_nodes
if self.run_code(code, result):
File "D:\Anaconda3\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-28-1563b8f59996>", line 1, in <module>
runfile('D:/Tensorflow/mnist_examp.py', wdir='D:/Tensorflow')
File "D:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "D:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "D:/Tensorflow/mnist_examp.py", line 148, in <module>
main()
File "D:/Tensorflow/mnist_examp.py", line 144, in main
mnist_model(learning_rate, use_two_fc, use_two_conv, hparam)
File "D:/Tensorflow/mnist_examp.py", line 61, in mnist_model
y = tf.placeholder(tf.float32, shape=[None, 10], name="labels")
File "D:\Anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1548, in placeholder
return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2094, in _placeholder
name=name)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
op_def=op_def)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "D:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1204, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'labels' with dtype float and shape [?,10]
[[Node: labels = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
正如我所说，我刚刚开始学习，所以代码可能不是最清晰的。我的代码如下：
import tensorflow as tf
import matplotlib.pyplot as plt
x_data = [1, 2, 3, 4]#np.linspace(0,10,10)
y_data = [0, -1, -2, -3]
#weight
W = tf.Variable(tf.random_normal([1]), name="weight")
#bias
b = tf.Variable(tf.random_normal([1]), name="bias")
#plaaceholders
with tf.name_scope ("Input"):
X=tf.placeholder(tf.float32, name="Input_X")
Y=tf.placeholder(tf.float32, name="Input_Y")
#Model-linear regression
with tf.name_scope ("Modelo"):
y_pred = tf.add(tf.multiply(X,W),b)
#cost
with tf.name_scope ("Error"):
loss = tf.reduce_mean(tf.square(y_pred - y_data))
tf.summary.scalar("loss",loss)
tf.summary.histogram("optimizer",loss)
#training algorithm
optimizer = tf.train.GradientDescentOptimizer(0.01)
train = optimizer.minimize(loss)
#initializing the variables
init = tf.global_variables_initializer()
#starting the session session
sess = tf.Session()
# training the line
sess.run(init)
pasos=1000
Merged= tf.summary.merge_all()
writer= tf.summary.FileWriter(r'D:\Tensorflow\tmp\example1', graph=tf.get_default_graph())
for step in range(pasos):
_, losses, summary=sess.run([train, loss, Merged], feed_dict={X: x_data, Y: y_data})
writer.add_summary(summary, step)
我在Windows 10 64bit中运行anaconda，我已经尝试过全部搜索，但似乎我看起来的任何地方都是在tensorflow网络中的MNIST示例（带有红色指甲开发视频的那个）而且那个时候太密集了。