Cuda dim3 constructor12/18/2023 ![]() Performs one of the matrix-matrix operations JCublasĬublasCsymm (char side, char uplo, int m, int n, cuComplex alpha,Ĭonst cuComplex *A, int lda, const cuComplex *B, int ldb, JCublas2 cublasChbmv(char, int, int, cuComplex, Pointer, int, Pointer, int, cuComplex, Pointer, int) - Static method in class jcuda.jcublas. JCublas2 cublasCgetrsBatched(cublasHandle, int, int, int, Pointer, int, Pointer, Pointer, int, Pointer, int) - Static method in class jcuda.jcublas. ![]() JCublas2 cublasCgetriBatched(cublasHandle, int, Pointer, int, Pointer, Pointer, int, Pointer, int) - Static method in class jcuda.jcublas. JCublas2 cublasCgetrfBatched(cublasHandle, int, Pointer, int, Pointer, Pointer, int) - Static method in class jcuda.jcublas. cublasCgeru(cublasHandle, int, int, Pointer, Pointer, int, Pointer, int, Pointer, int) - Static method in class jcuda.jcublas. Is an m by n matrix consisting of single precision complex elements. Precision complex vector, y is an n element single precision complex vector, and A Where alpha is a single precision complex scalar, x is an m element single ![]() Space_dropout_cuda_kernel.cu(182): error: class "at::Tensor" has no member "options"Ģ errors detected in the compilation of "/tmp/tmpxft_00000639_00000000-6_space_dropout_cuda_".CublasCgeru (int m, int n, cuComplex alpha, const cuComplex *x, int incx,Ĭonst cuComplex *y, int incy, cuComplex *A, int lda) Hello When I used x.options(), I also got similar building error. Space_dropout_cuda_kernel.cu(182): error: no suitable user-defined conversion from "at::Type" to "at::IntList" existsĢ errors detected in the compilation of "/tmp/tmpxft_00007903_00000000-6_space_dropout_cuda_".Įrror: command '/usr/local/cuda/bin/nvcc' failed with exit status 1 Space_dropout_cuda_kernel.cu(182): error: no instance of constructor "at::Type::Type" matches the argument list argument types are: (int64_t, int64_t) usr/local/cuda/bin/nvcc -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include/TH -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include/THC -I/usr/local/cuda/include -I/home/dmt/anaconda2/include/python2.7 -c space_dropout_cuda_kernel.cu -o build/temp.linux-x86_64-2.7/space_dropout_cuda_kernel.o -DTORCH_EXTENSION_NAME=space_dropout_cuda -compiler-options '-fPIC' -std=c++11 Gcc -pthread -B /home/dmt/anaconda2/compiler_compat -Wl,-sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include/TH -I/home/dmt/anaconda2/lib/python2.7/site-packages/torch/lib/include/THC -I/usr/local/cuda/include -I/home/dmt/anaconda2/include/python2.7 -c space_dropout_cuda.cpp -o build/temp.linux-x86_64-2.7/space_dropout_cuda.o -DTORCH_EXTENSION_NAME=space_dropout_cuda -std=c++11Ĭc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ Installing library code to build/bdist.linux-x86_64/egg Writing manifest file 'space_dropout_cuda.egg-info/SOURCES.txt' Reading manifest file 'space_dropout_cuda.egg-info/SOURCES.txt' Writing dependency_links to space_dropout_cuda.egg-info/dependency_links.txt Writing top-level names to space_dropout_cuda.egg-info/top_level.txt Writing space_dropout_cuda.egg-info/PKG-INFO Hello When I used x.type(), I also got such a building error. can anybody help me to fix this problem? Thanks. y //batch index CUDA_KERNEL_LOOP(c, state_size), x.type())", I got two building errors: (1) error: no instance of constructor "at::Type::Type" matches the argument list argument types are: (int64_t, int64_t) (2) error: no suitable user-defined conversion from "at::Type" to "at::IntList" exists. column is then the index in the state and index is batch_idx * batch_stride + column while gates_row is the first index of the gates in that particular element of the batch, because its batch stride is thrice as much.Ĭonst int n = blockIdx. It actually use the fact that blockDim.y is batch size and thus BlockIdx.y the batch index. The columnand index are kinda hard to figure out. Output_gate = sigmoid(gates) Ĭandidate_cell = elu(gates) y * state_size + column Ĭonst int gates_row = blockIdx. _global_ void lltm_cuda_forward_kernel(Ĭonst int column = blockIdx.
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