Open cmxnono opened 9 years ago
Can anyone help me?
I found(http://docs.scipy.org/doc/numpy-1.7.0/reference/generated/numpy.ndarray.T.html), when the dim of matrix is < 2,the isTrans() tag won't be set to true; The method is to disable the assert,now it work normally!!
python convnet.py --data-path ~/data/8_imagenet/ilsvrc2012/batchesx --train-range 0-417 --test-range 1000-1016 --save-path ~/data/8_imagenet/ilsvrc2012/models/ --epochs 90 --layer-def layers/layers-imagenet-1gpu.cfg --layer-params layers/layer-params-imagenet-1gpu.cfg --da ta-provider image --inner-size 227 --gpu 0 --mini 128 --test-freq 201 --color-noise 0.1 Initialized data layer 'data', producing 154587 outputs Initialized data layer 'labvec', producing 1 outputs Initialized convolutional layer 'conv1' on GPUs 0, producing 55x55 64-channel output Initialized cross-map response-normalization layer 'rnorm1' on GPUs 0, producing 55x55 64-channel output Initialized max-pooling layer 'pool1' on GPUs 0, producing 27x27 64-channel output Initialized convolutional layer 'conv2' on GPUs 0, producing 27x27 192-channel output Initialized cross-map response-normalization layer 'rnorm2' on GPUs 0, producing 27x27 192-channel output Initialized max-pooling layer 'pool2' on GPUs 0, producing 13x13 192-channel output Initialized convolutional layer 'conv3' on GPUs 0, producing 13x13 384-channel output Initialized convolutional layer 'conv4' on GPUs 0, producing 13x13 256-channel output Initialized convolutional layer 'conv5' on GPUs 0, producing 13x13 256-channel output Initialized max-pooling layer 'pool3' on GPUs 0, producing 6x6 256-channel output Initialized fully-connected layer 'fc4096a' on GPUs 0, producing 4096 outputs Initialized dropout2 layer 'dropout1' on GPUs 0, producing 4096 outputs Initialized fully-connected layer 'fc4096b' on GPUs 0, producing 4096 outputs Initialized dropout2 layer 'dropout2' on GPUs 0, producing 4096 outputs Initialized fully-connected layer 'fc1000' on GPUs 0, producing 1000 outputs Initialized softmax layer 'probs' on GPUs 0, producing 1000 outputs Initialized logistic regression cost 'logprob' on GPUs 0 Initialized neuron layer 'fc4096b_neuron' on GPUs 0, producing 4096 outputs Initialized neuron layer 'conv3_neuron' on GPUs 0, producing 64896 outputs Initialized neuron layer 'conv2_neuron' on GPUs 0, producing 139968 outputs Initialized neuron layer 'conv4_neuron' on GPUs 0, producing 43264 outputs Initialized neuron layer 'pool3_neuron' on GPUs 0, producing 9216 outputs Initialized neuron layer 'pool1_neuron' on GPUs 0, producing 46656 outputs Initialized neuron layer 'fc4096a_neuron' on GPUs 0, producing 4096 outputs Layer conv3_neuron using acts from layer conv3 Layer fc4096a_neuron using acts from layer fc4096a Layer fc4096b_neuron using acts from layer fc4096b Layer conv2_neuron using acts from layer conv2
Layer conv4_neuron using acts from layer conv4
Importing cudaconvnet._ConvNet C++ module Fwd terminal: logprob
found bwd terminal conv1[0] in passIdx=0
Training ConvNet Add PCA noise to color channels with given scale : 0.1 Check gradients and quit? : 0 [DEFAULT] Conserve GPU memory (slower)? : 0 [DEFAULT] Convert given conv layers to unshared local :
Cropped DP: crop size (0 = don't crop) : 227 Cropped DP: test on multiple patches? : 0 [DEFAULT] Data batch range: testing : 1000-1016 Data batch range: training : 0-417 Data path : ./data/8_imagenet/ilsvrc2012/batchesx Data provider : image Force save before quitting : 0 [DEFAULT] GPU override : 0
Layer definition file : layers/layers-imagenet-1gpu.cfg Layer file path prefix : [DEFAULT] Layer parameter file : layers/layer-params-imagenet-1gpu.cfg Load file : [DEFAULT] Logreg cost layer name (for --test-out) : [DEFAULT] Minibatch size : 128 Number of epochs : 90 Output test case predictions to given path : [DEFAULT] Save file override :
Save path : ./data/8_imagenet/ilsvrc2012/models/ Subtract this scalar from image (-1 = don't) : -1 [DEFAULT] Test and quit? : 0 [DEFAULT] Test on one batch at a time? : 1 [DEFAULT] Testing frequency : 201 Unshare weight matrices in given layers :
Write test data features from given layer : [DEFAULT]
Write test data features to this path (to be used with --write-features): [DEFAULT]
Running on CUDA device(s) 0 Current time: Fri Jun 12 00:03:57 2015
Saving checkpoints to ./data/8_imagenet/ilsvrc2012/models/ConvNet__2015-06-12_00.03.53
1.0 (0.00%)... FUCK1 FUCK11 python: src/../include/data.cuh:34: void CPUData::assertDimensions(): Assertion `_data->at(i-1)->isTrans() == _data->at(i)->isTrans()' failed. Error signal 6: /home/chenxiu/src/36_convnet/cudaconvnet/_ConvNet.so(_Z13signalHandleri+0x1b)[0x7fc1c442d5fb] /lib64/libc.so.6[0x37c6a326a0] /lib64/libc.so.6(gsignal+0x35)[0x37c6a32625] /lib64/libc.so.6(abort+0x175)[0x37c6a33e05] /lib64/libc.so.6[0x37c6a2b74e] /lib64/libc.so.6(__assert_perror_fail+0x0)[0x37c6a2b810] ./src/36_convnet/cudaconvnet/_ConvNet.so(_ZN7CPUData16assertDimensionsEv+0x144)[0x7fc1c442eb34] ./src/36_convnet/cudaconvnet/_ConvNet.so(_Z10startBatchP7objectS0+0x78)[0x7fc1c442dee8] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalFrameEx+0x5244)[0x37d3ad59e4] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalFrameEx+0x63ef)[0x37d3ad6b8f] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalCodeEx+0x927)[0x37d3ad7657] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalFrameEx+0x5304)[0x37d3ad5aa4] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalFrameEx+0x63ef)[0x37d3ad6b8f] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalFrameEx+0x63ef)[0x37d3ad6b8f] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalCodeEx+0x927)[0x37d3ad7657] /usr/lib64/libpython2.6.so.1.0(PyEval_EvalCode+0x32)[0x37d3ad7732] /usr/lib64/libpython2.6.so.1.0[0x37d3af1bac] /usr/lib64/libpython2.6.so.1.0(PyRun_FileExFlags+0x90)[0x37d3af1c80] /usr/lib64/libpython2.6.so.1.0(PyRun_SimpleFileExFlags+0xdc)[0x37d3af316c] /usr/lib64/libpython2.6.so.1.0(Py_Main+0xb62)[0x37d3aff8a2] /lib64/libc.so.6(__libc_start_main+0xfd)[0x37c6a1ed5d] python[0x400649]