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Check failed: error == cudaSuccess (18 vs. 0) invalid texture reference #34

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dongb5 opened this issue Jan 11, 2017 · 2 comments
Closed

Check failed: error == cudaSuccess (18 vs. 0) invalid texture reference #34

dongb5 opened this issue Jan 11, 2017 · 2 comments

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@dongb5
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dongb5 commented Jan 11, 2017

I0111 12:25:53.896850 4324 net.cpp:235] This network produces output proposal_cls_prob
I0111 12:25:53.896872 4324 net.cpp:492] Collecting Learning Rate and Weight Decay.
I0111 12:25:53.896881 4324 net.cpp:247] Network initialization done.
I0111 12:25:53.896886 4324 net.cpp:248] Memory required for data: 162768800
I0111 12:25:53.986716 4324 net.cpp:746] Copying source layer conv1_1
I0111 12:25:53.986763 4324 net.cpp:746] Copying source layer relu1_1
I0111 12:25:53.986780 4324 net.cpp:746] Copying source layer conv1_2
I0111 12:25:53.986812 4324 net.cpp:746] Copying source layer relu1_2
I0111 12:25:53.986820 4324 net.cpp:746] Copying source layer pool1
I0111 12:25:53.986826 4324 net.cpp:746] Copying source layer conv2_1
I0111 12:25:53.986872 4324 net.cpp:746] Copying source layer relu2_1
I0111 12:25:53.986881 4324 net.cpp:746] Copying source layer conv2_2
I0111 12:25:53.986966 4324 net.cpp:746] Copying source layer relu2_2
I0111 12:25:53.986974 4324 net.cpp:746] Copying source layer pool2
I0111 12:25:53.986979 4324 net.cpp:746] Copying source layer conv3_1
I0111 12:25:53.987136 4324 net.cpp:746] Copying source layer relu3_1
I0111 12:25:53.987143 4324 net.cpp:746] Copying source layer conv3_2
I0111 12:25:53.987453 4324 net.cpp:746] Copying source layer relu3_2
I0111 12:25:53.987463 4324 net.cpp:746] Copying source layer conv3_3
I0111 12:25:53.987776 4324 net.cpp:746] Copying source layer relu3_3
I0111 12:25:53.987784 4324 net.cpp:746] Copying source layer pool3
I0111 12:25:53.987789 4324 net.cpp:746] Copying source layer conv4_1
I0111 12:25:53.988402 4324 net.cpp:746] Copying source layer relu4_1
I0111 12:25:53.988414 4324 net.cpp:746] Copying source layer conv4_2
I0111 12:25:53.989629 4324 net.cpp:746] Copying source layer relu4_2
I0111 12:25:53.989645 4324 net.cpp:746] Copying source layer conv4_3
I0111 12:25:53.990911 4324 net.cpp:746] Copying source layer relu4_3
I0111 12:25:53.990929 4324 net.cpp:746] Copying source layer pool4
I0111 12:25:53.990934 4324 net.cpp:746] Copying source layer conv5_1
I0111 12:25:53.992154 4324 net.cpp:746] Copying source layer relu5_1
I0111 12:25:53.992173 4324 net.cpp:746] Copying source layer conv5_2
I0111 12:25:53.993454 4324 net.cpp:746] Copying source layer relu5_2
I0111 12:25:53.993474 4324 net.cpp:746] Copying source layer conv5_3
I0111 12:25:53.994707 4324 net.cpp:746] Copying source layer relu5_3
I0111 12:25:53.994727 4324 net.cpp:746] Copying source layer conv_proposal1
I0111 12:25:53.995934 4324 net.cpp:746] Copying source layer relu_proposal1
I0111 12:25:53.995954 4324 net.cpp:746] Copying source layer conv_proposal1_relu_proposal1_0_split
I0111 12:25:53.995959 4324 net.cpp:746] Copying source layer proposal_cls_score
I0111 12:25:53.995973 4324 net.cpp:746] Copying source layer proposal_bbox_pred
I0111 12:25:53.995995 4324 net.cpp:746] Copying source layer proposal_cls_score_reshape
I0111 12:25:53.996001 4324 net.cpp:743] Ignoring source layer proposal_cls_score_reshape_proposal_cls_score_reshape_0_split
I0111 12:25:53.996007 4324 net.cpp:743] Ignoring source layer labels_reshape
I0111 12:25:53.996012 4324 net.cpp:743] Ignoring source layer labels_reshape_labels_reshape_0_split
I0111 12:25:53.996017 4324 net.cpp:743] Ignoring source layer labels_weights_reshape
I0111 12:25:53.996022 4324 net.cpp:743] Ignoring source layer loss
I0111 12:25:53.996027 4324 net.cpp:743] Ignoring source layer accuarcy
I0111 12:25:53.996031 4324 net.cpp:743] Ignoring source layer loss_bbox
I0111 12:25:53.997133 4324 net.cpp:42] Initializing net from parameters:
name: "VGG_ILSVRC_16"
input: "data1"
input: "data2"
input: "rois"
input_dim: 1
input_dim: 512
input_dim: 50
input_dim: 50
input_dim: 1
input_dim: 512
input_dim: 50
input_dim: 50
input_dim: 1
input_dim: 5
input_dim: 1
input_dim: 1
state {
phase: TEST
}
layer {
name: "roi_pool3"
type: "ROIPooling"
bottom: "data1"
bottom: "rois"
top: "roi_pool3"
roi_pooling_param {
pooled_h: 7
pooled_w: 7
spatial_scale: 0.25
}
}
layer {
name: "roi_pool4_3"
type: "ROIPooling"
bottom: "data2"
bottom: "rois"
top: "roi_pool4_3"
roi_pooling_param {
pooled_h: 7
pooled_w: 7
spatial_scale: 0.25
}
}
layer {
name: "roi_pool3_flat"
type: "Flatten"
bottom: "roi_pool3"
top: "roi_pool3_flat"
}
layer {
name: "roi_pool4_3_flat"
type: "Flatten"
bottom: "roi_pool4_3"
top: "roi_pool4_3_flat"
}
layer {
name: "concat_feat"
type: "Concat"
bottom: "roi_pool3_flat"
bottom: "roi_pool4_3_flat"
top: "concat_feat"
}
I0111 12:25:53.997277 4324 net.cpp:380] Input 0 -> data1
I0111 12:25:53.997287 4324 net.cpp:380] Input 1 -> data2
I0111 12:25:53.997294 4324 net.cpp:380] Input 2 -> rois
I0111 12:25:53.997303 4324 layer_factory.hpp:74] Creating layer rois_input_2_split
I0111 12:25:53.997311 4324 net.cpp:90] Creating Layer rois_input_2_split
I0111 12:25:53.997316 4324 net.cpp:420] rois_input_2_split <- rois
I0111 12:25:53.997323 4324 net.cpp:378] rois_input_2_split -> rois_input_2_split_0
I0111 12:25:53.997334 4324 net.cpp:378] rois_input_2_split -> rois_input_2_split_1
I0111 12:25:53.997344 4324 net.cpp:120] Setting up rois_input_2_split
I0111 12:25:53.997352 4324 net.cpp:127] Top shape: 1 5 1 1 (5)
I0111 12:25:53.997359 4324 net.cpp:127] Top shape: 1 5 1 1 (5)
I0111 12:25:53.997364 4324 layer_factory.hpp:74] Creating layer roi_pool3
I0111 12:25:53.997371 4324 net.cpp:90] Creating Layer roi_pool3
I0111 12:25:53.997377 4324 net.cpp:420] roi_pool3 <- data1
I0111 12:25:53.997383 4324 net.cpp:420] roi_pool3 <- rois_input_2_split_0
I0111 12:25:53.997390 4324 net.cpp:378] roi_pool3 -> roi_pool3
I0111 12:25:53.997397 4324 net.cpp:120] Setting up roi_pool3
I0111 12:25:53.997406 4324 roi_pooling_layer.cpp:44] Spatial scale: 0.25
I0111 12:25:53.997417 4324 net.cpp:127] Top shape: 1 512 7 7 (25088)
I0111 12:25:53.997423 4324 layer_factory.hpp:74] Creating layer roi_pool4_3
I0111 12:25:53.997429 4324 net.cpp:90] Creating Layer roi_pool4_3
I0111 12:25:53.997434 4324 net.cpp:420] roi_pool4_3 <- data2
I0111 12:25:53.997440 4324 net.cpp:420] roi_pool4_3 <- rois_input_2_split_1
I0111 12:25:53.997447 4324 net.cpp:378] roi_pool4_3 -> roi_pool4_3
I0111 12:25:53.997453 4324 net.cpp:120] Setting up roi_pool4_3
I0111 12:25:53.997459 4324 roi_pooling_layer.cpp:44] Spatial scale: 0.25
I0111 12:25:53.997467 4324 net.cpp:127] Top shape: 1 512 7 7 (25088)
I0111 12:25:53.997473 4324 layer_factory.hpp:74] Creating layer roi_pool3_flat
I0111 12:25:53.997480 4324 net.cpp:90] Creating Layer roi_pool3_flat
I0111 12:25:53.997486 4324 net.cpp:420] roi_pool3_flat <- roi_pool3
I0111 12:25:53.997493 4324 net.cpp:378] roi_pool3_flat -> roi_pool3_flat
I0111 12:25:53.997499 4324 net.cpp:120] Setting up roi_pool3_flat
I0111 12:25:53.997509 4324 net.cpp:127] Top shape: 1 25088 (25088)
I0111 12:25:53.997514 4324 layer_factory.hpp:74] Creating layer roi_pool4_3_flat
I0111 12:25:53.997521 4324 net.cpp:90] Creating Layer roi_pool4_3_flat
I0111 12:25:53.997527 4324 net.cpp:420] roi_pool4_3_flat <- roi_pool4_3
I0111 12:25:53.997534 4324 net.cpp:378] roi_pool4_3_flat -> roi_pool4_3_flat
I0111 12:25:53.997541 4324 net.cpp:120] Setting up roi_pool4_3_flat
I0111 12:25:53.997550 4324 net.cpp:127] Top shape: 1 25088 (25088)
I0111 12:25:53.997555 4324 layer_factory.hpp:74] Creating layer concat_feat
I0111 12:25:53.997562 4324 net.cpp:90] Creating Layer concat_feat
I0111 12:25:53.997568 4324 net.cpp:420] concat_feat <- roi_pool3_flat
I0111 12:25:53.997573 4324 net.cpp:420] concat_feat <- roi_pool4_3_flat
I0111 12:25:53.997581 4324 net.cpp:378] concat_feat -> concat_feat
I0111 12:25:53.997587 4324 net.cpp:120] Setting up concat_feat
I0111 12:25:53.997596 4324 net.cpp:127] Top shape: 1 50176 (50176)
I0111 12:25:53.997601 4324 net.cpp:194] concat_feat does not need backward computation.
I0111 12:25:53.997606 4324 net.cpp:194] roi_pool4_3_flat does not need backward computation.
I0111 12:25:53.997612 4324 net.cpp:194] roi_pool3_flat does not need backward computation.
I0111 12:25:53.997617 4324 net.cpp:194] roi_pool4_3 does not need backward computation.
I0111 12:25:53.997623 4324 net.cpp:194] roi_pool3 does not need backward computation.
I0111 12:25:53.997629 4324 net.cpp:194] rois_input_2_split does not need backward computation.
I0111 12:25:53.997635 4324 net.cpp:235] This network produces output concat_feat
I0111 12:25:53.997644 4324 net.cpp:492] Collecting Learning Rate and Weight Decay.
I0111 12:25:53.997650 4324 net.cpp:247] Network initialization done.
I0111 12:25:53.997654 4324 net.cpp:248] Memory required for data: 602152
F0111 12:25:55.269489 4324 relu_layer.cu:27] Check failed: error == cudaSuccess (18 vs. 0) invalid texture reference
*** Check failure stack trace: ***
Killed

When I tried to run 'script_rpn_bf_pedestrian_VGG16_caltech_demo.m' I got the above error. I had compiled MS version caffe and copy the mex file to the path. And I used Titan X as gpu and Matlab 2013b. Any idea for this error?? Thanks.
@zhangliliang
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Hi,

This code has been tested on Ubuntu 14.04 with MATLAB 2014b and CUDA 7.5 using Titan X or Tesla K40.

You might try to use MATLAB 2014b or check your cuda version.

@dongb5
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dongb5 commented Jan 11, 2017

Thank you. I have solved the problem by finding another PC with MATLAB 2014b ...

@dongb5 dongb5 closed this as completed Jan 11, 2017
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@dongb5 @zhangliliang