I0415 15:03:37.603461 27311 solver.cpp:42] Solver scaffolding done.
I0415 15:03:37.603549 27311 solver.cpp:247] Solving AlexNet
I0415 15:03:37.603559 27311 solver.cpp:248] Learning Rate Policy: step
I0415 15:03:37.749981 27311 solver.cpp:214] Iteration 0, loss = 5.45141
I0415 15:03:37.750030 27311 solver.cpp:229] Train net output #0: loss = 5.45141 (* 1 = 5.45141 loss)
I0415 15:03:37.750048 27311 solver.cpp:489] Iteration 0, lr = 0.001
I0415 15:03:38.316994 27311 solver.cpp:214] Iteration 12, loss = 4.23865
I0415 15:03:38.317054 27311 solver.cpp:229] Train net output #0: loss = 4.23865 (* 1 = 4.23865 loss)
I0415 15:03:38.317068 27311 solver.cpp:489] Iteration 12, lr = 0.001
I0415 15:03:38.920938 27311 solver.cpp:214] Iteration 24, loss = 2.49914
I0415 15:03:38.921000 27311 solver.cpp:229] Train net output #0: loss = 2.49914 (* 1 = 2.49914 loss)
I0415 15:03:38.921016 27311 solver.cpp:489] Iteration 24, lr = 0.001
I0415 15:03:39.509793 27311 solver.cpp:214] Iteration 36, loss = 3.76504
I0415 15:03:39.509850 27311 solver.cpp:229] Train net output #0: loss = 3.76504 (* 1 = 3.76504 loss)
I0415 15:03:39.509861 27311 solver.cpp:489] Iteration 36, lr = 0.001
I0415 15:03:40.080806 27311 solver.cpp:214] Iteration 48, loss = 3.74901
I0415 15:03:40.080862 27311 solver.cpp:229] Train net output #0: loss = 3.74901 (* 1 = 3.74901 loss)
I0415 15:03:40.080878 27311 solver.cpp:489] Iteration 48, lr = 0.001
I0415 15:03:40.643797 27311 solver.cpp:214] Iteration 60, loss = 2.27091
I0415 15:03:40.643849 27311 solver.cpp:229] Train net output #0: loss = 2.27091 (* 1 = 2.27091 loss)
I0415 15:03:40.643860 27311 solver.cpp:489] Iteration 60, lr = 0.001
I0415 15:03:41.217475 27311 solver.cpp:214] Iteration 72, loss = 2.67078
I0415 15:03:41.217541 27311 solver.cpp:229] Train net output #0: loss = 2.67078 (* 1 = 2.67078 loss)
I0415 15:03:41.217561 27311 solver.cpp:489] Iteration 72, lr = 0.001
I0415 15:03:41.793390 27311 solver.cpp:214] Iteration 84, loss = 1.77313
I0415 15:03:41.793452 27311 solver.cpp:229] Train net output #0: loss = 1.77313 (* 1 = 1.77313 loss)
I0415 15:03:41.793468 27311 solver.cpp:489] Iteration 84, lr = 0.001
I0415 15:03:42.362951 27311 solver.cpp:214] Iteration 96, loss = 3.49406
I0415 15:03:42.363004 27311 solver.cpp:229] Train net output #0: loss = 3.49406 (* 1 = 3.49406 loss)
I0415 15:03:42.363025 27311 solver.cpp:489] Iteration 96, lr = 0.001
I0415 15:03:42.946568 27311 solver.cpp:214] Iteration 108, loss = 2.81601
I0415 15:03:42.946633 27311 solver.cpp:229] Train net output #0: loss = 2.81601 (* 1 = 2.81601 loss)
I0415 15:03:42.946651 27311 solver.cpp:489] Iteration 108, lr = 0.001
I0415 15:03:43.524155 27311 solver.cpp:214] Iteration 120, loss = 2.85056
I0415 15:03:43.524247 27311 solver.cpp:229] Train net output #0: loss = 2.85056 (* 1 = 2.85056 loss)
I0415 15:03:43.524265 27311 solver.cpp:489] Iteration 120, lr = 0.001
I0415 15:03:44.100580 27311 solver.cpp:214] Iteration 132, loss = 3.58945
I0415 15:03:44.100646 27311 solver.cpp:229] Train net output #0: loss = 3.58945 (* 1 = 3.58945 loss)
I0415 15:03:44.100661 27311 solver.cpp:489] Iteration 132, lr = 0.001
F0415 15:03:44.536542 27311 math_functions.cpp:91] Check failed: error == cudaSuccess (4 vs. 0) unspecified launch failure
*** Check failure stack trace: ***
@ 0x7f01dbd9ddaa (unknown)
@ 0x7f01dbd9dce4 (unknown)
@ 0x7f01dbd9d6e6 (unknown)
@ 0x7f01dbda0687 (unknown)
@ 0x7f01dc1bb3f5 caffe::caffe_copy<>()
@ 0x7f01dc230232 caffe::BasePrefetchingDataLayer<>::Forward_gpu()
@ 0x7f01dc1d9d6f caffe::Net<>::ForwardFromTo()
@ 0x7f01dc1da197 caffe::Net<>::ForwardPrefilled()
@ 0x7f01dc20cbe5 caffe::Solver<>::Step()
@ 0x7f01dc20d52f caffe::Solver<>::Solve()
@ 0x406428 train()
@ 0x404961 main
@ 0x7f01db2afec5 (unknown)
@ 0x404f0d (unknown)
@ (nil) (unknown)
Aborted
[email protected]:~/Downloads/lstm_caffe_master$
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怎么破 ？？？求解答。。。。
