我正在使用TensorFlow进行Udemy课程和CNN的初学者学习。在运行会话时，出现InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder_1' with dtype float and shape [?,10]错误。
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}))
我收到以下错误。
---------------------------------------------------------------------------
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"]()]]
`
最佳答案
y_true和mnist.test.labels的尺寸应该一致。希望可以为您提供帮助。
关于python - 处理MNIST数据时在TensorFlow中获取“InvalidArgumentError”，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/57036446/