device=device(type="cuda", index=0), device=device, pin_memory=False, ) @@ -123,7 +142,7 @@ def forward( start=0, step=1, dtype=torch.int32, device=device(type="cuda"), device=device, requires_grad=False, ) @@ -135,7 +154,7 @@ def forward( start=0, step=1001, dtype=...
torch.gather(input, dim, index, out=None) → Tensor/gather(dim, index) 这个函数就很迷了,当时学习tensorflow时就研究了好久╮(╯﹏╰)╭,注意所有的index都是torch.LongTensor torch.gather(t, 1, torch.LongTensor([[0,0],[1,0]])) 1. torch.index_select(input, dim, index, out=None) → ...
在GPU上,t默认是torch.cuda.FloatTensor,还可以是torch.cuda.DoubleTensor,torch.cuda.HalfTensor import torch a = torch.rand(4,3) print(a.dtype, a.device) print(torch.get_default_dtype()) # torch.float32 cpu # torch.float32 torch.set_default_tensor_type(torch.cuda.FloatTensor) b = torch....
stdout: , stderr: exec command: [/bin/nvidia-container-cli --load-kmods configure --device=all --compute --utility --require=cuda>=11.8 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver
cudaMalloc((void**)&dev_1,sizeof(int)*100); cudaMalloc((void**)&dev_2,sizeof(int)*100);//下面是错误的dev_1[0]=dev_2[0];//dev_1和dev_2都是gpu内存,所以这个操作(读/写)cpu干不了,需要让gpu来干。} kernal中分配不了大内存 ...
cusparse.sp_mat_get_index_base nvmath.bindings.cusparse.sp_mat_get_values nvmath.bindings.cusparse.sp_mat_set_values nvmath.bindings.cusparse.sp_mat_get_size nvmath.bindings.cusparse.sp_mat_get_strided_batch nvmath.bindings.cusparse.coo_set_strided_batch nvmath.bindings.cusparse.csr_set_...
RuntimeError: Input type (torch.cuda.ByteTensor) and weight type (torch.cuda.FloatTensor) should be,程序员大本营,技术文章内容聚合第一站。
[argIndex++]=cmd.UTF8String;}// 解析语法树,返回根节点TranslationUnitCXTranslationUnit tu=clang_parseTranslationUnit(index,file.UTF8String,args,(unsigned)cmd_arr.count,NULL,0,CXTranslationUnit_None);free(args);if(!tu){clang_disposeIndex(index);return;}// 访问语法树clang_visitChildren(clang_...
[Solved] runtimeerror: cuda error: invalid device ordinal How are TypeErrors caused? TypeErrors are one of Python’s many exceptions types. Operations performed on unsupported object types cause the error. The common causes for TypeErrors are: ...
我们直接使用<和>对数字进行比较。但是在用这些符号进行浮点数比较时，不够严谨（NaN、0.0、-0.0，...