Python 进刀和numpy整形

假设我有一个tensorflow形状：

   y_ = tf.placeholder(tf.float32,[None,19],name='Labels')

我在这里的想法是每次得到19个元素的向量，然后把它加到y上_

并列出长度为57的inputlabel：

我想把这张单子上的行输入你

这种喂食不起作用，我真的不明白我该如何解决它。以下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"]()]]

不，类型问题是解决，我还有一个奇怪的东西：

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)]]

这项工作：

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))})

---

是否inputlabel的类型错误？

导入数据时，只需将编码1-hot标签的nSamples整数列表转换为形状nSamples数组，19只包含0和1

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)

---

现在，您的标签自然是shape nSamples、NumberOfClass和shape batchSize、NumberOfClass的批次，这是程序其余部分所需要的。

show inputLabel。这对我有用。printnp.reformeInputLabel[3,19]。shape。我认为你的输入标签是不同的形状。输出应为3,19

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))})

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)