问CUDA exp() expf()和__expf()EN2015 年 11 月，wikipedia的用户 Laughinthestocks 首次引入了“...
fromnumbaimportconfig,cuda,float32,voidfrommathimportcosconfig.DUMP_ASSEMBLY=True@cuda.jit(void(float32[::1],float32),fastmath=True)deff(r,x):r[0]=cos(x) produces a lot of code: .visible .global.align4.u32 _ZN6cudapy8__main__5f$241E5ArrayIfLi1E1C7mutable7alignedEf__errcode__;....
/opt/rocm/llvm/bin/clang++ -I. -Iggml/include -Iggml/src -Iinclude -Isrc -I./common -I./include -I./include/CL -I./otherarch -I./otherarch/tools -I./otherarch/sdcpp -I./otherarch/sdcpp/thirdparty -I./include/vulkan -O3 -fno-finite-math-only -fmath-errno -DNDEBUG -std=c+...
torch.exp(input,out=None) → Tensor Returns a new tensor with the exponential of the elements of the input tensorinput. Parameters input(Tensor) – the input tensor. out(Tensor,optional) – the output tensor. Example: AI检测代码解析 >>> torch.exp(torch.tensor([0, math.log(2.)])) ten...
alpha_sum_logps_1= torch.log(torch.exp(chosen_alpha_logps).sum(dim=-1)+torch.exp(rejected_alpha_logps).sum(dim=-1))此时俩者差距是tensor(-3.7188, device='cuda:0', dtype=torch.bfloat16, grad_fn=<SumBackward0>)当换成float32时,误差变成了tensor(-1.5140e-05, device='cuda:0', grad...
이전글[Nvidia] GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC 현재글[ROS Melodic] W: GPG error: http://packages....
方飞龙目前担任杭州虫虫食品有限公司、杭州临安旭日红炒货食品厂法定代表人,同时担任杭州紫辰贸易有限公司监事,杭州虫虫食品有限公司执行董事兼总经理;二、方飞龙投资情况:方飞龙目前是杭州临安旭日红炒货食品厂直接控股股东,持股比例为100%,是杭州虫虫食品有限公司直接控股股东,持股比例为25%;目前方飞龙是3家企业最终受益人,...
270 changes: 144 additions & 126 deletions 270 source/adapters/cuda/image.cpp Load diff Large diffs are not rendered by default. 15 changes: 7 additions & 8 deletions 15 source/adapters/hip/image.cpp Original file line numberDiff line numberDiff line change @@ -75,15 +75,14 @@ UR...
device('cuda') @@ -164,7 +164,7 @@ def train(): 164 164 collate_fn=partial(collate, config.max_length) 165 165 ) 166 166 167 - model = LSTM(config).to(config.device) 167 + model = RNN(config).to(config.device) 168 168 criterion = nn.CrossEntropyLoss(ignore_index=...