说我有张量流形状：
y_ = tf.placeholder(tf.float32,[None,19],name='Labels')
我的想法是每次给19个元素的向量，并将它（插入）添加到y _
并列出inputlabel 57作为篇幅：
我想将此列表中的行提供给y_
sess.run(train_step,feed_dict={x:xdata,y_:np.reshape(inputlabel,(3,19))})
这种喂养不起作用，我真的不知道如何解决它。这是我收到的错误消息：
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1021 try:
-> 1022 return fn(*args)
1023 except errors.OpError as e:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1003 feed_dict, fetch_list, target_list,
-> 1004 status, run_metadata)
1005
c:\users\engine\appdata\local\programs\python\python35\lib\contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
InvalidArgumentError: You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-7-1da2dc43ca63> in <module>()
1 for j in range(len(batch_xs)-1):
----> 2 print(sess.run(train_step,feed_dict={x:batch_xs[j],y_:np.reshape(batch_ys[j],(3,numberOFClasses))}))
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
765 try:
766 result = self._run(None, fetches, feed_dict, options_ptr,
--> 767 run_metadata_ptr)
768 if run_metadata:
769 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
963 if final_fetches or final_targets:
964 results = self._do_run(handle, final_targets, final_fetches,
--> 965 feed_dict_string, options, run_metadata)
966 else:
967 results = []
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1013 if handle is None:
1014 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1015 target_list, options, run_metadata)
1016 else:
1017 return self._do_call(_prun_fn, self._session, handle, feed_dict,
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1033 except KeyError:
1034 pass
-> 1035 raise type(e)(node_def, op, message)
1036
1037 def _extend_graph(self):
InvalidArgumentError: You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'Labels', defined at:
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\__main__.py", line 3, in <module>
app.launch_new_instance()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance
app.start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "c:\users\engine\appdata\local\programs\python\python35\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\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-3-49d5bdb3e7ad>", line 6, in <module>
y_ = tf.placeholder(tf.float32,[None],name='Labels')
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1502, in placeholder
name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2149, in _placeholder
name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 763, in apply_op
op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2327, in create_op
original_op=self._default_original_op, op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1226, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
**更新**
输入标签声明如下：
..............
inputlabel =[]
..................
for i in batch(Training_Data,batchSize):
inputlabel.append(i)
def batch(iterable, n=1):
l = len(iterable)
for ndx in range(0, l, n):
yield iterable[ndx:min(ndx + n, l)]
不，类型问题解决了我得到了其他奇怪的东西：
InvalidArgumentError (see above for traceback): Incompatible shapes: [3,19] vs. [57,19]
[[Node: gradients/mul_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](gradients/mul_grad/Shape, gradients/mul_grad/Shape_1)]]
答案 0 :(得分：1)
这有效：
import numpy as np
import tensorflow as tf
y_ = tf.placeholder(tf.float32,[None,19],name='Labels')
sess = tf.InteractiveSession()
labels = np.zeros(57, dtype=np.float32)
sess.run(y_, feed_dict = {y_: np.reshape(labels, (3,19))})
可能是您的inputlabel类型错误吗？
答案 1 :(得分：0)
您只需将编码1-hot标签的（nSamples）整数列表转换为导入数据时仅包含0和1的形状数组（nSamples，19），
例如(1, 8, 2) -> [[1, 0, 0, ...], [0, 0, 1, 0, 0, ...], [0, 1, 0, 0, ...]]
你可以这样做：
label_1_hot_coding = row[-1]
array_of_bits = np.zeros(numberOFClasses)
n = 1
for i,_in enumerate(array_of_bits):
if n== label_1_hot_coding:
array_of_bits[i] = 1
Training_Labels.append(array_of_bits)
您的标签现在自然具有(nSamples, numberOfClasses)形状，以及形状(batchSize, numberOfClasses)的批次，这是您的其他程序所需要的。