mnist demo failed

[LamboAventador]

I0325 16:53:11.160656 21224 caffe.cpp:224] GPU 0: GeForce GTX 1660 Ti I0325 16:53:12.766374 21224 solver.cpp:44] Initializing solver from parameters: test_iter: 100 test_interval: 500 base_lr: 0.01 display: 100 max_iter: 100000 lr_policy: "inv" gamma: 0.0001 power: 0.75 momentum: 0.9 weight_decay: 0.0005 snapshot: 5000 snapshot_prefix: "D:/caffe-windows-ms/examples/mnist/lenet" solver_mode: GPU device_id: 0 net: "D:/caffe-windows-ms/examples/mnist/lenet_train_test.prototxt" train_state { level: 0 stage: "" } I0325 16:53:12.768326 21224 solver.cpp:87] Creating training net from net file: D:/caffe-windows-ms/examples/mnist/lenet_train_test.prototxt I0325 16:53:12.768326 21224 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer mnist I0325 16:53:12.769323 21224 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy I0325 16:53:12.769323 21224 net.cpp:51] Initializing net from parameters: name: "LeNet" state { phase: TRAIN level: 0 stage: "" } layer { name: "mnist" type: "Data" top: "data" top: "label" include { phase: TRAIN } transform_param { scale: 0.00390625 } data_param { source: "D:/caffe-windows-ms/examples/mnist/mnist_train_lmdb" batch_size: 64 backend: LMDB } } layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv1" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 20 kernel_size: 5 stride: 1 weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "pool1" type: "Pooling" bottom: "conv1" top: "pool1" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layer { name: "conv2" type: "Convolution" bottom: "pool1" top: "conv2" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 50 kernel_size: 5 stride: 1 weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "pool2" type: "Pooling" bottom: "conv2" top: "pool2" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layer { name: "ip1" type: "InnerProduct" bottom: "pool2" top: "ip1" param { lr_mult: 1 } param { lr_mult: 2 } inner_product_param { num_output: 500 weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu1" type: "ReLU" bottom: "ip1" top: "ip1" } layer { name: "ip2" type: "InnerProduct" bottom: "ip1" top: "ip2" param { lr_mult: 1 } param { lr_mult: 2 } inner_product_param { num_output: 10 weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "loss" type: "SoftmaxWithLoss" bottom: "ip2" bottom: "label" top: "loss" } I0325 16:53:12.770320 21224 layer_factory.hpp:77] Creating layer mnist I0325 16:53:12.772315 21224 db_lmdb.cpp:40] Opened lmdb D:/caffe-windows-ms/examples/mnist/mnist_train_lmdb I0325 16:53:12.772315 21224 net.cpp:84] Creating Layer mnist I0325 16:53:12.772315 21224 net.cpp:380] mnist -> data I0325 16:53:12.773313 21224 net.cpp:380] mnist -> label I0325 16:53:12.775307 21224 data_layer.cpp:46] output data size: 64,1,28,28 I0325 16:53:12.776304 21224 net.cpp:122] Setting up mnist I0325 16:53:12.777302 21224 net.cpp:129] Top shape: 64 1 28 28 (50176) I0325 16:53:12.778300 21224 net.cpp:129] Top shape: 64 1 1 1 (64) I0325 16:53:12.778300 21224 net.cpp:137] Memory required for data: 200960 I0325 16:53:12.778300 21224 layer_factory.hpp:77] Creating layer conv1 I0325 16:53:12.779296 21224 net.cpp:84] Creating Layer conv1 I0325 16:53:12.779296 21224 net.cpp:406] conv1 <- data I0325 16:53:12.779296 21224 net.cpp:380] conv1 -> conv1 引发了异常: 读取访问权限冲突。 google::protobuf::RepeatedField::Get(...) 返回 0x8。

程序“[3816] caffe.exe”已退出，返回值为 0 (0x0)。 ` VS2015编译成功了，但demo跑不通，GPU和CPU都报相同的错误，有人遇到这样的情况吗？