src(Tensor) -要分散和添加的源元素以与 scatter_() 类似的方式将来自张量 other 的所有值添加到 self 在index 张量中指定的索引处。对于 src 中的每个值,将其添加到 self 中的索引中,该索引由 src 中的索引指定 dimension != dim 和index 中的相应值 dimension = dim。 对于3-D 张量,self 更新为: sel...
structstructured_ufunc_add_CUDA_outfinal:publicat::native::structured_ufunc_add_CUDA{structured_ufunc_add_CUDA_out(Tensor&out0):outputs_{std::ref(out0)}{}voidset_output_strided(int64_toutput_idx,IntArrayRefsizes,IntArrayRefstrides,TensorOptionsoptions,DimnameListnames)override{...}voidset_outpu...
那么在cuda Kernel中索引位置的时候是可以提前把dim后面的维度给合并起来的(这里使用TensorInfo数据结构来完成,其实本质上就是操作这个TensorInfo对象维护的Tensor的stride和size,具体可见这里的实现:https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/CollapseDims.h#L22),这样子原始的输入Tensor的形状就会...
<!DOCTYPE html> (beta)torch_npu.npu_dropout_with_add_softmax 接口原型torch_npu.npu_dropout_with_add_softmax(Tensor self, Tensor x1, Scalar alpha, float prob, int dim) -> (Tensor, Tensor, Tensor) 功能描述实现
While updating to CUDA 12.6 eager test, PR: #148602 Failing workflow: https://github.com/pytorch/pytorch/actions/runs/13690790469/job/38285054097#step:22:4164 We see following test failure: _ TestForeachCUDA.test_pointwise_op_with_tensor_of_scalarlist_overload__foreach_addcmul_is_fastpath_Tr...
Failed to find test times file `/home/runner/work/pytorch/pytorch/.additional_ci_files/test-times.json`. Using round robin sharding. Test `run_test.py` is usable without boto3 Failed to find test times file `/home/runner/work/pytorch/pytorch/.additional_ci_files/test-class-times.json`....
PyTorch 生成张量有多种方式,有一半主要使用以下 5 种。 1.torch.tensor()函数 tensor(data [,dtype [,device [,requires_grad]]]) data:数值或布尔类型的 Python 列表或元组。 dtype:数据类型,默认为 64 或 torch.float32。 device:tensor 被分配的设备,默认为 cpu。
pytorch add_,#a=a+4*5importtorcha=torch.tensor([1,2,3])a.data.add_(torch.tensor(4),torch.tensor(5))print(a)#tensor([21,22,23])
https://pytorch.org/docs/stable/tensors.html#torch.Tensor.scatter_add_ 用torch.tensor.scatter_add_() 函数报错:Expected index [1, 67, 3] to be smaller than self [9, 66, 5003] apart from dimension 2 and to be smaller size than src [1, 67, 3]idxes = torch.tensor([[[ 59, 33,...
add不能和torch scatter_add_一样受到类似问题的启发并解决了how to change torch.scatter_add to ...