Python Tensorflow占位符具有负维度

我正在研究一种预测二进制选择的神经网络。当我试图提取预测时，它不起作用，并给我以下跟踪：

2017-09-03 13:52:59.302796: W tensorflow/core/framework/op_kernel.cc:1148] Invalid argument: Shape [-1,2] has negative dimensions
2017-09-03 13:52:59.302843: E tensorflow/core/common_runtime/executor.cc:644] Executor failed to create kernel. Invalid argument: Shape [-1,2] has negative dimensions
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,2], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
2017-09-03 13:52:59.302922: W tensorflow/core/framework/op_kernel.cc:1148] Invalid argument: Shape [-1,2] has negative dimensions
2017-09-03 13:52:59.302939: E tensorflow/core/common_runtime/executor.cc:644] Executor failed to create kernel. Invalid argument: Shape [-1,2] has negative dimensions
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,2], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Traceback (most recent call last):
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1139, in _do_call
    return fn(*args)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1121, in _run_fn
    status, run_metadata)
  File "/home/tucker/anaconda3/lib/python3.5/contextlib.py", line 66, in __exit__
    next(self.gen)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape [-1,2] has negative dimensions
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,2], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 104, in <module>
    print(sess.run(y, feed_dict={x: future_x}))
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 789, in run
    run_metadata_ptr)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 997, in _run
    feed_dict_string, options, run_metadata)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1132, in _do_run
    target_list, options, run_metadata)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1152, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape [-1,2] has negative dimensions
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,2], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'Placeholder_1', defined at:
  File "train.py", line 37, in <module>
    y = tf.placeholder("float32", [None, num_classes])
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1530, in placeholder
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1954, in _placeholder
    name=name)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/tucker/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1269, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Shape [-1,2] has negative dimensions
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,2], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

---

提前感谢

由于这行

打印（sess.run（y，feed_dict={x:future_x}））而出现错误

，您试图通过输入另一个占位符

x

来获取

y

。这里的

x

和

y

是独立的

应按以下方式进行更正：；您需要为

y

print(sess.run(y, feed_dict={y: y_test}))

---

出现错误的原因是这一行

print（sess.run（y，feed_dict={x:future_x}））

，您试图通过输入另一个占位符

x

来获取

y

。这里的

x

和

y

是独立的

应按以下方式进行更正：；您需要为

y

print(sess.run(y, feed_dict={y: y_test}))

---

预测由张量

预测

（或

输出

，因为它是相同的）给出，而不是由占位符

y

（这是您在培训期间放置标签的位置）。预测代码应该是这样的：

print(sess.run(prediction, feed_dict={x: future_x}))

---

预测由张量

预测

（或

输出

，因为它是相同的）给出，而不是由占位符

y

（这是您在培训期间放置标签的位置）。预测代码应该是这样的：

print(sess.run(prediction, feed_dict={x: future_x}))

---

什么？我试着用X来预测Y。当我试着用X来预测Y时，如何用Y来预测Y？你如何用另一个不相关的占位符来预测占位符的值？什么？我试图用X来预测Y。当我试图用X来预测Y时，如何用Y来预测Y？如何用另一个不相关的占位符来预测占位符的值？