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i have this error wheni execute the command of train

I0613 00:09:52.356884 6121 caffe.cpp:218] Using GPUs 0 F0613 00:09:52.357022 6121 common.cpp:66] Cannot use GPU in CPU-only Caffe: check mode. *** Check failure stack trace: *** @ 0x7fe4bf6f75cd google::LogMessage::Fail() @ 0x7fe4bf6f9433 google::LogMessage::SendToLog() @ 0x7fe4bf6f715b google::LogMessage::Flush() @ 0x7fe4bf6f9e1e google::LogMessageFatal::~LogMessageFatal() @ 0x7fe4bfbed110 caffe::Caffe::SetDevice() @ 0x40aceb train() @ 0x407208 main @ 0x7fe4bde8e830 __libc_start_main @ 0x407ad9 _start @ (nil) (unknown) Aborted (core dumped)

kts and others added 30 commits January 24, 2017 10:45
parse_log.py was not using --verbose argument
Fix broken links in layer documentation, minor fixes.
Add Pascal CUDA architectures to Makefile.config.example
Obsolete reference to `bool solver` in caffe.proto
[osx] find vecLib without sdk version
[pycaffe] add layer_dict to the python interface
[docs] info about MKL licensing
Fix plot_training_log.py.example
[fix] pycaffe net draw needs default pooling values
fix comments in matlab classification demo
[matcaffe] allow destruction of individual networks and solvers
[cmake] Improvements to the build system
Made load_hd5 check blob dims by default, instead of reshaping.
Multi GPU training from Python can use any solver
Noiredd and others added 30 commits April 11, 2018 15:32
Gaussian filler tests adjustments
Fix incorrect namespace for pycaffe submodule caffe_pb2
fix missing syncedmem constness

fix issue #6387
drop unnecessary cast

fix issue #6389
a sketch of `solver.step()` done out manually:

1. `solver.net.forward()`
2. `solver.net.backward()`
3. `solver.net.apply_update()`
4. `solver.net.clear_param_diffs()`
with update exposed it is important to increment the iteration when an
update is made, whether by step or update alone. more fundementally,
it's the update that defines an iterationa, so this is a natural place
for the increment.
`solver.lr` is the effective learning rate in use while `solver.base_lr`
is the configured learning rate at initialization. the solver parameter
is now editable for setting fields that are in use throughout the
lifetime of the solver, such as the maximum iteration.
[pycaffe] expose interface for manual, step-by-step optimization
Otherwise caffe allocates some memory on GPU#0
PoolingLayer customizable output shape rounding mode
Clip layer - resurrection
Fix typo in inner_product_layer.cpp
fix typos and add passing by reference
python: Set gpu device id before setting gpu mode
Fix simple typo: overrided -> overridden
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