title: Getting "InvalidArgumentError" in TensorFlow when working on MNIST data
body: <p>I'm following a Udemy course and a beginner with CNN with TensorFlow. When I'm running a session I'm getting <code>InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]</code> error. </p>
  
  <pre><code>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.....] --&gt; 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}))
  </code></pre>
  
  <p>I'm getting the following error. </p>
  
  <pre><code>---------------------------------------------------------------------------
  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:
  -&gt; 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,
  -&gt; 1306                                    status, run_metadata)
     1307 
  
  ~/anaconda3/envs/tfdeeplearning/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
       65             try:
  ---&gt; 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)),
  --&gt; 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)
  &lt;ipython-input-30-1df33799cd1a&gt; in &lt;module&gt;()
        7         batch_x, batch_y = mnist.train.next_batch(100)
        8 
  ----&gt; 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,
  --&gt; 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,
  -&gt; 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,
  -&gt; 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
  -&gt; 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 &lt;module&gt;
      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 "&lt;ipython-input-23-12e74ec33d57&gt;", line 2, in &lt;module&gt;
      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"]()]]
  `
  </code></pre>