我正在尝试为TensorFlow提供的Deep MNIST示例运行以下示例代码，但是当我运行它时出现错误。代码的第一部分运行良好，并使用GradientDescentOptimizer打印出测试的准确性。第二部分在最后一行失败，它打印卷积网络的测试精度。该程序以以下行结束：＆＃34; 流程以退出代码139结束（由信号11：SIGSEGV中断）＆＃34;
我已经尝试过Python 3和3.5但我同时遇到了同样的错误。
更新：我注意到，如果我将 mnist.test.images 和 mnist.test.labels 交换为批次[0 ] 和批处理[1] 在最终的打印语句中发生段错误，并在打印之前生成一个新的批处理：＆＃34; batch = mnist.test.next_batch(50)＆＃34;它工作正常。
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
sess = tf.InteractiveSession()
x = tf.placeholder(tf.float32, shape=[None, 784])
y_ = tf.placeholder(tf.float32, shape=[None, 10])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
sess.run(tf.global_variables_initializer())
y = tf.matmul(x, W) + b
cross_entropy = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
for _ in range(1000):
batch = mnist.train.next_batch(100)
train_step.run(feed_dict={x: batch[0], y_: batch[1]})
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(accuracy.eval(feed_dict={x: mnist.test.images, y_: mnist.test.labels}))
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')
W_conv1 = weight_variable([5, 5, 1, 32])
b_conv1 = bias_variable([32])
x_image = tf.reshape(x, [-1, 28, 28, 1])
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.matmul(h_fc1_drop, W_fc2) + b_fc2
cross_entropy = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(100):
batch = mnist.train.next_batch(50)
if i % 100 == 0:
train_accuracy = accuracy.eval(feed_dict={
x: batch[0], y_: batch[1], keep_prob: 1.0})
print('step %d, training accuracy %g' % (i, train_accuracy))
train_step.run(feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5})
print('test accuracy %g' % accuracy.eval(
feed_dict={x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))
编辑：这是我使用python3.5和gdb运行程序并显示框架和回溯时得到的结果:(也是hastebin上相同输出的链接：{{3} }）
Thread 6 "python" received signal SIGSEGV, Segmentation fault.
[Switching to Thread 0x7ffff2a55700 (LWP 13640)]
0x00007fffe7b56d99 in Eigen::internal::gemm_pack_lhs<float, long, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, 8, 4, 0, false, false>::operator()(float*, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer> const&, long, long, long, long) ()
from /home/jimmy/.virtualenvs/TensorFlowTest/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
(gdb) info frame
Stack level 0, frame at 0x7ffff2a54d00:
rip = 0x7fffe7b56d99
in Eigen::internal::gemm_pack_lhs<float, long, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, 8, 4, 0, false, false>::operator()(float*, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer> const&, long, long, long, long); saved rip = 0x7fffe7b65fba
called by frame at 0x7ffff2a54e00
Arglist at 0x7ffff2a54cf0, args:
Locals at 0x7ffff2a54cf0, Previous frame's sp is 0x7ffff2a54d00
Saved registers:
rbx at 0x7ffff2a54cc8, rbp at 0x7ffff2a54cf0, r12 at 0x7ffff2a54cd0, r13 at 0x7ffff2a54cd8, r14 at 0x7ffff2a54ce0, r15 at 0x7ffff2a54ce8, rip at 0x7ffff2a54cf8
(gdb) backtrace
#0 0x00007fffe7b56d99 in Eigen::internal::gemm_pack_lhs<float, long, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, 8, 4, 0, false, false>::operator()(float*, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer> const&, long, long, long, long) ()
from /home/jimmy/.virtualenvs/TensorFlowTest/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#1 0x00007fffe7b65fba in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorImagePatchOp<-1l, -1l, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const> const, Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const> const, Eigen::ThreadPoolDevice>::Context<Eigen::internal::gemm_pack_lhs<float, long, Eigen::internal::TensorContractionSubMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, 8, 4, 0, false, false>, Eigen::internal::gemm_pack_rhs<float, long, Eigen::internal::TensorContractionSubMapper<float, long, 0, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorImagePatchOp<-1l, -1l, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, 4, 0, false, false>, Eigen::internal::gebp_kernel<float, float, long, Eigen::internal::blas_data_mapper<float, long, 0, 0>, 8, 4, false, false>, Eigen::internal::TensorContractionInputMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, Eigen::internal::TensorContractionInputMapper<float, long, 0, Eigen::TensorEvaluator<Eigen::TensorReshapingOp<Eigen::DSizes<long, 2> const, Eigen::TensorImagePatchOp<-1l, -1l, Eigen::TensorMap<Eigen::Tensor<float const, 4, 1, long>, 16, Eigen::MakePointer> const> const> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, Eigen::internal::blas_data_mapper<float, long, 0, 0> >::enqueue_packing_helper(long, long, long, bool) ()
from /home/jimmy/.virtualenvs/TensorFlowTest/lib/python3.5/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#2 0x00007fffe4b33e22 in Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) ()
from /home/jimmy/.virtualenvs/TensorFlowTest/lib/python3.5/site-packages/tensorflow/python/../libtensorflow_framework.so
#3 0x00007fffe4b32ed2 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) ()
from /home/jimmy/.virtualenvs/TensorFlowTest/lib/python3.5/site-packages/tensorflow/python/../libtensorflow_framework.so
#4 0x00007fffe4150e20 in std::execute_native_thread_routine_compat (__p=<optimized out>) at /build/gcc-multilib/src/gcc/libstdc++-v3/src/c++11/thread.cc:110
#5 0x00007ffff76f908a in start_thread () from /usr/lib/libpthread.so.0
#6 0x00007ffff743047f in clone () from /usr/lib/libc.so.6