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Makefile:587: recipe for target '.build_release/src/caffe/proto/caffe.pb.o' failed
make: *** [.build_release/src/caffe/proto/caffe.pb.o] Error 1

Thanks for your contribution。When I use your code to train captach follow your steps, I can see the loss is lower and accuracy is good from log. But When I test single captach Image with captcha_prediction.cpp, the result is wrong and Unbelievable，Why? Thank you

训练过程没有问题，也生成了相应的model，但对这块儿东西不熟，能否提供一个测试的网络及程序呢

[ 1%] Built target proto
[ 1%] Building NVCC (Device) object src/caffe/CMakeFiles/cuda_compile.dir/layers/cuda_compile_generated_ctc_loss_layer.cu.o
/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(14): error: explicit type is missing ("int" assumed)

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(14): error: type name is not allowed

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(14): error: expected a ";"

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(15): error: expression must have class type

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(16): error: expression must have class type

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(17): error: expression must have class type

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(26): error: no suitable constructor exists to convert from "int" to "ctcOptions"

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(37): error: namespace "std" has no member "accumulate"

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(41): error: expression must have class type

/root/warpctc-caffe/src/caffe/layers/ctc_loss_layer.cu(32): error: no suitable constructor exists to convert from "int" to "ctcOptions"
detected during instantiation of "void caffe::CtcLossLayer::Forward_gpu(const std::vector<caffe::Blob *, std::allocator<caffe::Blob *>> &, const std::vector<caffe::Blob *, std::allocator<caffe::Blob *>> &) [with Dtype=float]"
(61): here

10 errors detected in the compilation of "/tmp/tmpxft_000058bc_00000000-6_ctc_loss_layer.cpp1.ii".
CMake Error at cuda_compile_generated_ctc_loss_layer.cu.o.cmake:266 (message):
Error generating file
/root/warpctc-caffe/Release/src/caffe/CMakeFiles/cuda_compile.dir/layers/./cuda_compile_generated_ctc_loss_layer.cu.o

src/caffe/CMakeFiles/caffe.dir/build.make:16157: recipe for target 'src/caffe/CMakeFiles/cuda_compile.dir/layers/cuda_compile_generated_ctc_loss_layer.cu.o' failed
make[2]: *** [src/caffe/CMakeFiles/cuda_compile.dir/layers/cuda_compile_generated_ctc_loss_layer.cu.o] Error 1
CMakeFiles/Makefile2:272: recipe for target 'src/caffe/CMakeFiles/caffe.dir/all' failed
make[1]: *** [src/caffe/CMakeFiles/caffe.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2

您好，请问您有没有对比过warpctc和原始的ctc速度上的差异

CXX src/caffe/layers/flatten_layer.cpp
CXX src/caffe/layers/batch_norm_layer.cpp
src/caffe/layers/ctc_loss_layer.cpp: In member function ‘virtual void caffe::CtcLossLayer::Forward_cpu(const std::vector<caffe::Blob>&, const std::vector<caffe::Blob>&)’:
src/caffe/layers/ctc_loss_layer.cpp:86:17: error: ‘accumulate’ is not a member of ‘std’
Dtype loss =std::accumulate(cost, cost + mini_batch, Dtype(0));
^
Makefile:580: recipe for target '.build_release/src/caffe/layers/ctc_loss_layer.o' failed
make: *** [.build_release/src/caffe/layers/ctc_loss_layer.o] Error 1
make: *** Waiting for unfinished jobs....

出错信息如下：
NVCC src/caffe/3rdparty/reduce.cu
src/caffe/layers/ctc_loss_layer.cu: In instantiation of ‘void caffe::CtcLossLayer::Forward_gpu(const std::vector<caffe::Blob>&, const std::vector<caffe::Blob>&) [with Dtype = float]’:
src/caffe/layers/ctc_loss_layer.cu:61:135: required from here
src/caffe/layers/ctc_loss_layer.cu:14:17: error: ‘std::initializer_list<_Tp> options’ has incomplete type
auto options = ctcOptions{};
^
make: *** [.build_release/cuda/src/caffe/layers/ctc_loss_layer.o] Error 1
make: *** Waiting for unfinished jobs....

你好，我发现编译的时候找不到 __shlf_down这个函数，查询后发现这个是cuda的问题，可是我的环境是Ubuntu14.04 + cudnn V5 + cuda 7.5，理论上已经够新的了。后来在网上找到了这个解决方案，https://github.com/parallel-forall/code-samples/blob/master/posts/parallel_reduction_with_shfl/fake_shfl.h 替换掉__shlf_down， 之后就可以编译了，但是有一个问题，就是不知道这两个函数是否真的是一样的。

另外在训练验证码的例子时，发现一直不收敛，不知道你在训练的时候是不是也这样很难收敛？或者有什么技巧吗？谢谢

你好，我有一个问题想问你，就是关于lstm层，我看了prototxt，lstm的输入是permute后的，形状是[80,1,3,30],然后训练出来这一层的h是40090，c是400，权重是400100，相当于100100（因为有4组权重），那么输入的[80,1,3,30]如何和h40090合并，然后合并之后又如何和100*100做卷积运算？

我在官方的caffe的docker环境中下载了您的代码，
在cpu环境下面，我直接使用您的代码进行编译成功了
但是在gpu环境下面，我编译的时候，在make all的时候出现了以下错误：
CXX src/caffe/data_transformer.cpp
NVCC src/caffe/3rdparty/reduce.cu
nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
src/caffe/3rdparty/reduce.cu(44): error: identifier "__shfl_down" is undefined
detected during:
instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]"
(76): here
instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]"
(124): here
instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(139): here
instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]"
(149): here

src/caffe/3rdparty/reduce.cu(44): error: identifier "__shfl_down" is undefined
detected during:
instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]"
(76): here
instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]"
(124): here
instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(139): here
instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]"
(157): here

2 errors detected in the compilation of "/tmp/tmpxft_00000e20_00000000-14_reduce.compute_20.cpp1.ii".
Makefile:594: recipe for target '.build_release/cuda/src/caffe/3rdparty/reduce.o' failed
make: *** [.build_release/cuda/src/caffe/3rdparty/reduce.o] Error 1

如果您遇到过，或者知道该如何解决，王不吝赐教～

when i make the warpctc-caffe, there's a issue:
ERROR : src/caffe/3rdparty/reduce.cu(44): error: identifier "__shfl_down" is undefined

CtcLoss的两个输入中，fc1的输出是80×512×11的，那label的维度呢？
输入的时候我看到label是512×5的，没有看到经过哪一步骤改变啊。。。