Atorch.Tensoris a multi-dimensional matrix containing elements of a single data type. torch.Tensor是包含单一数据类型的多维矩阵 2 Data types Torch定义了10种不同CPU和GPU的张量类型,下面摘录常用的几种 torch.Tensoris an alias for the defa
A torch.Tensor is a multi-dimensional matrix containing elements of a single data type. 张量(torch.Tensor)是包含单个数据类型元素的多维矩阵。 1、张量定义了如下八种CPU张量类型和八种GPU张量类型: #CPU对应八种数据类型,GPU对应也有八种数据类型,如torch.cuda.FloatTensor([])torch.FloatTensor([]) torch....
importtorchimportnumpy as np"""数据类型"""#常见的类型判断a = torch.randn(2,3)#正态分布print(a.type())#torch.FloatTensorprint(type(a))#<class 'torch.Tensor'>, python自带print(isinstance(a, torch.FloatTensor))#True#标量b = torch.tensor(2.)print(b)#tensor(2.)#获取形状print(b.shape)...
a=torch.randint(0,10,(2,6)).squeeze().int()atensor([[0,9,7,6,3,0],[8,1,8,3,6,4]],dtype=torch.int32)a.sort(dim=0)#返回排序好的值和索引(tensor([[0,1,7,3,3,0],[8,9,8,6,6,4]],dtype=torch.int32),tensor([[0,1,0,1,0,0],[1,0,1,0,1,1]])) torch/Te...
torch.Tensor是存储和变换数据的主要工具,可认为是一个高维数组,它可以是一个数(标量)、一维张量(向量)、二维张量(矩阵)或更高维的张量。Tensor和numpy中的多维数组ndarray很类似,但Tensor可以使用GPU加速。 Tensor的接口设计与numpy类似,从接口的角度讲,对Tensor的操作可分为两类:(1)torch.function,如:torch.save...
.TensorBase", /* tp_name */ sizeof(THPVariable), /* tp_basicsize */ ... }; bool THPVariable_initModule(PyObject* module) { THPVariableMetaType.tp_base = &PyType_Type; // 申明THPVariableMetaType的基类是PyType_Type, Variable,你就当成是Tensor吧 if (PyType_Ready(&THPVariableMetaType...
tensor([0, 1]) # Type inference on data tensor([ 0, 1]) >>> torch.tensor([[0.11111, 0.222222, 0.3333333]], dtype=torch.float64, device=torch.device('cuda:0')) # creates a torch.cuda.DoubleTensor tensor([[ 0.1111, 0.2222, 0.3333]], dtype=torch.float64, device='cuda:0') >>>...
torch.utils.data.TensorDataset: 用于获取封装成 tensor 的数据集,每一个样本都通过索引张量来获得。class TensorDataset(Dataset): 代码语言:javascript 代码运行次数:0 运行 AI代码解释 def__init__(self,*tensor):assertall(tensors[0].size(0)==tensor.size(0)fortensorintensors)self.tensors=tensors ...
a1.type_as(a2)可将a1转换为a2同类型。tensor和numpy.array转换 tensor -> numpy.array: data.numpy()，如： numpy.array -> tensor: torch.from_numpy(data)，如： CPU张量和GPU张量之间的转换 CPU -> GPU: data.cuda() GPU -> CPU: data.cpu()当需要把⼀个GPU上的tensor数...
Problem Description I'm a pytorch user, and I'm always thinking that type torch.Tensor might be represented in a proper way. What torch.Tensor type data need is just '.numpy()' to be converted to numpy array objects. So, is it possible t...