我创建了一个卷积神经网络。它预测mnist数据集的位数。它可以正常工作而不会丢失。当我添加辍学时，它给出了错误。由于错误，我无法计算准确性。 这是代码：
import numpy as np
from matplotlib.pyplot import imshow
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist=input_data.read_data_sets("data/mnist",one_hot=True,reshape=False)
def get_val(in_):
for i in range(len(in_)):
if round(_list[i])==1.:
return i
else:
continue
X=tf.placeholder(tf.float32,[None,28,28,1])
Y=tf.placeholder(tf.float32,[None,10])
pkeep=Y=tf.placeholder(tf.float32)
wc1=tf.Variable(tf.random.truncated_normal([6,6,1,16],stddev=0.2))
bc1=tf.Variable(tf.random.truncated_normal([16],stddev=0.2))
wc2=tf.Variable(tf.random.truncated_normal([5,5,16,32],stddev=0.2))
bc2=tf.Variable(tf.random.truncated_normal([32],stddev=0.2))
wd1=tf.Variable(tf.random.truncated_normal([1568,256],stddev=0.2))
bd1=tf.Variable(tf.random.truncated_normal([256],stddev=0.2))
wd2=tf.Variable(tf.random.truncated_normal([256,64],stddev=0.2))
bd2=tf.Variable(tf.random.truncated_normal([64],stddev=0.2))
wdo=tf.Variable(tf.random.truncated_normal([64,10],stddev=0.2))
bdo=tf.Variable(tf.random.truncated_normal([10],stddev=0.2))
y=tf.nn.relu(tf.nn.conv2d(X,wc1,strides=[1,1,1,1],padding="SAME")+bc1)
y=tf.nn.max_pool(y,ksize=[1,2,2,1],strides=[1,2,2,1],padding="SAME")
y=tf.nn.relu(tf.nn.conv2d(y,wc2,strides=[1,1,1,1],padding="SAME")+bc2)
y=tf.nn.max_pool(y,ksize=[1,2,2,1],strides=[1,2,2,1],padding="SAME")
y=tf.reshape(y,(-1,1568))
y=tf.nn.tanh(tf.linalg.matmul(y,wd1)+bd1)
y=tf.nn.dropout(y,pkeep)
y=tf.nn.tanh(tf.linalg.matmul(y,wd2)+bd2)
y=tf.nn.dropout(y,pkeep)
y_pred=tf.nn.softmax(tf.linalg.matmul(y,wdo)+bdo)
xent=-tf.reduce_sum(Y*tf.math.log(y_pred))
l2=tf.reduce_sum(tf.math.square(Y-y_pred))
correct_pred=tf.equal(tf.argmax(Y,-1),tf.argmax(y_pred,-1))
accuracy=tf.reduce_mean(tf.cast(correct_pred,tf.float32))
optimizer=tf.train.AdamOptimizer(1e-3).minimize(xent)
images=[]
saver=tf.train.Saver()
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(3001):
bx,by=mnist.train.next_batch(50)
sess.run(optimizer,feed_dict={X:bx,Y:by,pkeep:0.75})
acc,x_l,l2_l=sess.run([accuracy,xent,l2],feed_dict={X:bx,Y:by,pkeep:1})
print("Iteration",i,"Accuracy="+str(acc),"Cross Entropy Loss="+str(x_l),"Mean Squared Error="+str(l2_l))
test_acc,test_x,test_l=sess.run([accuracy,xent,l2],feed_dict={X:mnist.test.images,Y:mnist.test.labels,pkeep:1})
print("Train Accuracy="+str(test_acc),"Cross Entropy Loss="+str(test_x),"Mean Squared Error="+str(test_l),"\n\n")
print("Model is trained with",test_acc,"accuracy")
save_path = saver.save(sess, "tmp/model.ckpt")
print("Model saved in path: %s" % save_path)
这是您的错误。我在tf.argmax()函数中收到错误。
-------------------------------------------------- -------------------------
InvalidArgumentError错误回溯（最近一次通话）
_do_call中的/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py(self，fn，* args）
1355试试：
-> 1356返回fn（* args）
1357除了errors.OpError为e：
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1340 return self._call_tf_sessionrun(
-> 1341 options, feed_dict, fetch_list, target_list, run_metadata)
1342
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1428 self._session, options, feed_dict, fetch_list, target_list,
-> 1429 run_metadata)
1430
InvalidArgumentError: Expected dimension in the range [0, 0), but got -1
[[{{node ArgMax_8}}]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-8-4c94f5a440b2> in <module>()
56 bx,by=mnist.train.next_batch(50)
57 sess.run(optimizer,feed_dict={X:bx,Y:by,pkeep:0.75})
---> 58 acc,x_l,l2_l=sess.run([accuracy,xent,l2],feed_dict={X:bx,Y:by,pkeep:1})
59 print("Iteration",i,"Accuracy="+str(acc),"Cross Entropy Loss="+str(x_l),"Mean Squared Error="+str(l2_l))
60 test_acc,test_x,test_l=sess.run([accuracy,xent,l2],feed_dict={X:mnist.test.images,Y:mnist.test.labels,pkeep:1})
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
948 try:
949 result = self._run(None, fetches, feed_dict, options_ptr,
--> 950 run_metadata_ptr)
951 if run_metadata:
952 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1171 if final_fetches or final_targets or (handle and feed_dict_tensor):
1172 results = self._do_run(handle, final_targets, final_fetches,
-> 1173 feed_dict_tensor, options, run_metadata)
1174 else:
1175 results = []
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1348 if handle is None:
1349 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1350 run_metadata)
1351 else:
1352 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1368 pass
1369 message = error_interpolation.interpolate(message, self._graph)
-> 1370 raise type(e)(node_def, op, message)
1371
1372 def _extend_graph(self):
InvalidArgumentError: Expected dimension in the range [0, 0), but got -1
[[node ArgMax_8 (defined at <ipython-input-8-4c94f5a440b2>:46) ]]
Errors may have originated from an input operation.
Input Source operations connected to node ArgMax_8:
Placeholder_17 (defined at <ipython-input-8-4c94f5a440b2>:15)
Original stack trace for 'ArgMax_8':
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.6/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python3.6/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-8-4c94f5a440b2>", line 46, in <module>
correct_pred=tf.equal(tf.argmax(Y,-1),tf.argmax(y_pred,-1))
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py", line 138, in argmax
return argmax_v2(input, axis, output_type, name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py", line 175, in argmax_v2
return gen_math_ops.arg_max(input, axis, name=name, output_type=output_type)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 948, in arg_max
name=name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 2005, in __init__
self._traceback = tf_stack.extract_stack()