我是Tensorflow的新手，并试图与CNN一起运行mnist数据集。我的网络构建如
def weight_variable(shape): initial = tf.truncated_normal(shape, stddev=0.1) return tf.Variable(initial) def bias_variable(shape): initial = tf.constant(0.1, shape=shape) return tf.Variable(initial) def conv2d(x, W): return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME') def max_pool_2x2(x): return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME') mnist = input_data.read_data_sets('MNIST_data/', one_hot=True) sess = tf.InteractiveSession() x = tf.placeholder(tf.float32, [None, 784]) y_ = tf.placeholder(tf.float32, [None, 10]) x_image = tf.reshape(x, [-1 , 28, 28, 1]) W_conv1 = weight_variable([5, 5, 1, 32]) b_conv1 = bias_variable([32]) h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1) h_pool1 = max_pool_2x2(h_conv1) W_conv2 = weight_variable([5, 5, 32, 64]) b_conv2 = bias_variable([64]) h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2) h_pool2 = max_pool_2x2(h_conv2) W_fc1 = weight_variable([7*7*64, 1024]) b_fc1 = bias_variable([1024]) h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64]) h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1) keep_prob = tf.placeholder(tf.float32) h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob) W_fc2 = weight_variable([1024, 10]) b_fc2 = bias_variable([10]) y_conv = tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2) cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y_conv), reduction_indices=[1])) train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy) correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.arg_max(y_, 1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) tf.global_variables_initializer().run() for i in range(20000): batch_xs, batch_ys = mnist.train.next_batch(50) if i % 100 == 0: train_accuracy = accuracy.eval(feed_dict={x: batch_xs, y_: batch_ys, keep_prob: 1.0}) print('step {:d}, training accuracy {:g}'.format(i, train_accuracy)) train_step.run(feed_dict={x: batch_xs, y_: batch_ys, keep_prob: 0.5})
以下是堆栈信息：
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1138 try:
-> 1139 return fn(*args)
1140 except errors.OpError as e:
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict,
fetch_list, target_list, options, run_metadata)
1120 feed_dict, fetch_list, target_list,
-> 1121 status, run_metadata)
1122
/home/lv/anaconda3/lib/python3.6/contextlib.py in __exit__(self, type, value, traceback)
88 try:
---> 89 next(self.gen)
90 except StopIteration:
/home/lv/anaconda3/lib/python3.6/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: Shape [-1,784] has negative dimensions
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[?,784],
_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-32-d670cfa25269> in <module>()
4 # train_accuracy = accuracy.eval(feed_dict={x: batch_xs, y_: batch_ys, keep_prob: 1.0})
5 # print('step {:d}, training accuracy {:g}'.format(i, train_accuracy))
----> 6 train_step.run(feed_dict={x: batch_xs, y_: batch_ys, keep_prob: 0.5})
7
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in run(self, feed_dict, session)
1704 none, the default session will be used.
1705 """
-> 1706 _run_using_default_session(self, feed_dict, self.graph, session)
1707
1708
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _run_using_default_session
(operation, feed_dict, graph, session)
3961 "the operation's graph is different from the session's "
3962 "graph.")
-> 3963 session.run(operation, feed_dict)
3964
3965
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict,
options, run_metadata)
787 try:
788 result = self._run(None, fetches, feed_dict, options_ptr,
--> 789 run_metadata_ptr)
790 if run_metadata:
791 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches,
feed_dict, options, run_metadata)
995 if final_fetches or final_targets:
996 results = self._do_run(handle, final_targets, final_fetches,
--> 997 feed_dict_string, options, run_metadata)
998 else:
999 results = []
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list,
fetch_list, feed_dict, options, run_metadata)
1130 if handle is None:
1131 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1132 target_list, options, run_metadata)
1133 else:
1134 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1150 except KeyError:
1151 pass
-> 1152 raise type(e)(node_def, op, message)
1153
1154 def _extend_graph(self):
InvalidArgumentError: Shape [-1,784] has negative dimensions
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[?,784],
_device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'Placeholder', defined at:
File "/home/lv/anaconda3/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/home/lv/anaconda3/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/home/lv/anaconda3/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "/home/lv/anaconda3/lib/python3.6/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/lv/anaconda3/lib/python3.6/site-packages/tornado/ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "/home/lv/anaconda3/lib/python3.6/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/lv/anaconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/lv/anaconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/lv/anaconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/lv/anaconda3/lib/python3.6/site-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/lv/anaconda3/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/lv/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/lv/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "/home/lv/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-5-c7318338c904>", line 1, in <module>
x = tf.placeholder(tf.float32, [None, 784])
File "/home/lv/anaconda3/lib/python3.6/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/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1954, in
_placeholder
name=name)
File "/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in
apply_op
op_def=op_def)
File "/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/lv/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1269, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): Shape [-1,784] has negative dimensions
[[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[?,784],
_device="/job:localhost/replica:0/task:0/cpu:0"]()]]
那么，问题是什么？有人能帮助我吗？很多。
答案 0 :(得分：1)
tf.global_variables_initializer().run()两次，这似乎是造成错误的原因，我猜。
答案 1 :(得分：0)
当您使用代码tensor.eval()时，某些宣传者不支持方法tf.placeholder()。
如果您不使用这些张量.eval()，则不会出现错误。