list of tensors is also accepted, those should be of the same type and shape pattern: string, reduction pattern reduction: one of available reductions ('min', 'max', 'sum', 'mean', 'prod'), case-sensitive alter
bitwise_not_() → Tensor bmm(batch2) → Tensor bool() → Tensor byte() → Tensor cauchy_(median=0, sigma=1, *, generator=None) → Tensor ceil() → Tensor ceil_() → Tensor char() → Tensor cholesky(upper=False) → Tensor cholesky_inverse(upper=False) → Tensor cholesky_solve(inpu...
A sparse tensor can be uncoalesced, in that case, there are duplicate coordinates in the indices, and the value at that index is the sum of all duplicate value entries: torch.sparse. Parameters indices (array_like)– Initial data for the tensor. Can be a list, tuple, NumPy ndarray, ...
it provides many utilities for efficient serializing of Tensors and arbitrary types, and other useful utilities.It has a CUDA counterpart, that enables you to run your tensor computations on an NVIDIA GPU with compute capability >= 3.0.
切片 torch.tensor_split(input, indices_or_sections, dim=0) → List of Tensors 是按照索引拆分。相当于你指定了拆分位置的下标; 组合/拼接 torch.cat(tensors, dim=0, ***, out=None) → Tensor 拼接tensor 序列,可以指定dim 组合/拼接 torch.stack(tensors, dim=0, ***, out=None) → Tensor ...
placeholderrepresents a function input. Thenameattribute specifies the name this value will take on.targetis similarly the name of the argument.argsholds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input.kwargsis don’t-care. Placeholders correspond...
tensor= torch.cat(list_of_tensors, dim=0)tensor= torch.stack(list_of_tensors, dim=0) 将整数标记转换成独热(one-hot)编码 PyTorch 中的标记默认从 0 开始。 N = tensor.size(0) one_hot = torch.zeros(N, num_classes).long() one_hot.scatter_(dim=1, index=torch.unsqueeze(tensor,dim=1...
(self, s:str) ->List[int]:return[self.stoi[c]forcins]defdecode(self, l:List[int]) ->str:return''.join([self.itos[i]foriinl])classBigramLanguageModel:def__init__(self, vocab_size:int):self.vocab_size = vocab_sizeself.transition = [[0for_inrange(vocab_size)]for_inrange(vocab...
(0x7fd0e2c890b8 in /home/yonghyeon/pytorch/pytorch-asan/build/lib/libtorch_cpu.so) frame #22: at::_ops::sum_dim_IntList::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::OptionalArrayRef<long>, bool, std::optional<c10::ScalarType>) + 0xa40 (0x7fd0e2a60ae0 in /home/yong...
We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if x.sum() > 0: def forward(self, x: Tensor, h: Tensor) -> Tuple[Tensor, Tensor]: dg = self.dg linear...