在处理MNIST d时在TensorFlow中获取“InvalidArgumentError”

Question

我正在学习我的课程，也是CNN TensorFlow的初学者。当我运行会话时，我得到了InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]错误。你知道吗

with tf.Session() as sess:

    sess.run(init)

    for step in range(1000):

        batch_x, batch_y = mnist.train.next_batch(100)

        sess.run(train, feed_dict={x:batch_x, y:batch_y})

    # Evaluate the model
    correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_true,1))

    # Output will be like [True, False, True.....] --> Cast to [1.0, 0.0, 1.0.....]
    acc = tf.reduce_mean(tf.cast(correct_prediction,tf.float32))

    print(sess.run(acc,feed_dict={x:mnist.test.images,y_true:mnist.test.labels}))

我得到以下错误。你知道吗

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1326     try:
-> 1327       return fn(*args)
   1328     except errors.OpError as e:

~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
   1305                                    feed_dict, fetch_list, target_list,
-> 1306                                    status, run_metadata)
   1307 

~/anaconda3/envs/tfdeeplearning/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
     65             try:
---> 66                 next(self.gen)
     67             except StopIteration:

~/anaconda3/envs/tfdeeplearning/lib/python3.5/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 'Placeholder_1' with dtype float and shape [?,10]
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,10], _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-30-1df33799cd1a> in <module>()
      7         batch_x, batch_y = mnist.train.next_batch(100)
      8 
----> 9         sess.run(train, feed_dict={x:batch_x, y:batch_y})
     10 
     11     # Evaluate the model

~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    893     try:
    894       result = self._run(None, fetches, feed_dict, options_ptr,
--> 895                          run_metadata_ptr)
    896       if run_metadata:
    897         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1122     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1123       results = self._do_run(handle, final_targets, final_fetches,
-> 1124                              feed_dict_tensor, options, run_metadata)
   1125     else:
   1126       results = []

~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1319     if handle is None:
   1320       return self._do_call(_run_fn, self._session, feeds, fetches, targets,
-> 1321                            options, run_metadata)
   1322     else:
   1323       return self._do_call(_prun_fn, self._session, handle, feeds, fetches)

~/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1338         except KeyError:
   1339           pass
-> 1340       raise type(e)(node_def, op, message)
   1341 
   1342   def _extend_graph(self):

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/cpu:0"]()]]

Caused by op 'Placeholder_1', defined at:
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 477, in start
    ioloop.IOLoop.instance().start()
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tornado/ioloop.py", line 888, in start
    handler_func(fd_obj, events)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tornado/stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tornado/stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 283, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
    handler(stream, idents, msg)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 533, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2698, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2802, in run_ast_nodes
    if self.run_code(code, result):
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2862, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-23-12e74ec33d57>", line 2, in <module>
    y_true = tf.placeholder(tf.float32, shape=[None, 10])
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1548, in placeholder
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2094, in _placeholder
    name=name)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/Users/majain/anaconda3/envs/tfdeeplearning/lib/python3.5/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 'Placeholder_1' with dtype float and shape [?,10]
     [[Node: Placeholder_1 = Placeholder[dtype=DT_FLOAT, shape=[?,10], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
`

Answer 1

看起来，您尚未初始化占位符变量。 Tensorflow使用您编写的语句构造计算图。 所以当你写的时候： 赛斯·润（acc，feed_dict={x:mnist.test.images文件年_正确：mnist.test.labels}) TensorFlow搜索计算acc所需的所有内容，并递归地查找其他变量。你知道吗

该错误表明占位符变量之一未初始化或初始化方式错误。你知道吗

您在feed\ dict中输入了错误的变量名。Tensorflow在计算交叉熵步时寻找y\ true，但您输入的是“y”。做如下变化计算图赛斯·润（列，feed\u dict={x:batch\u x，y）_正确：批量})你知道吗

Answer 2

你的尺寸是真的mnist.test.labels标签应该是始终如一。希望如此可以帮助您。