add_image(tag, img_tensor, global_step=None, walltime=None, dataformats='CHW') 将图像数据添加到摘要中。 请注意,这需要pillow包。 参数: 1、tag (string) – 数据标识符 2、img_tensor (torch.Tensor, numpy.array, or string/blobname) –
Constructs a sparse tensors in COO(rdinate) format with non-zero elements at the given indices with the given values. 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:...
add(value) → Tensor add_(value) → Tensor add_(value=1, other) -> Tensor addbmm(beta=1, alpha=1, batch1, batch2) → Tensor addbmm_(beta=1, alpha=1, batch1, batch2) → Tensor addcdiv(value=1, tensor1, tensor2) → Tensor addcdiv_(value=1, tensor1, tensor2) → Tensor add...
Use torch.Tensor.item() to get a Python number from a tensor containing a single value: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 复制 >>> x = torch.tensor([[1]]) >>> x tensor([[ 1]]) >>> x.item() 1 >>> x = torch.tensor(2.5) >>> x tensor(2.5000) >>> x....
,chunks为int,即需要分成的份数torch.gather(input,dim,index,out=None) →Tensor。Gathersvaluesalonganaxisspecifiedbydim.torch.index_select(input,dim,index,out=None) →Tensor,类似于标准库slice函数的 PyTorch入门实战教程笔记(九):基础张量操作5
1,gather是不规则的切片提取算子(Gathers values along an axis specified by dim. 在指定维度上根据索引 index 来选取数据)。函数定义如下: torch.gather(input,dim,index,*,sparse_grad=False,out=None)→Tensor 参数解释: +input(Tensor) – the source tensor. +dim(int) – the axis along which to ind...
1. Storing value references in slots instead of __dict__. 2. Denying __dict__ and __weakref__ creation if parent classes deny them and you declare __slots__. 10. 构造自定义的datasets可以参考torch的官网[9] 手撸一个简单的dataset,根据教程,最小化实现,仅实现下面三个函数即可 __init__ ...
value= tensor.item() 张量形变 张量形变常常需要用于将卷积层特征输入全连接层的情形。相比 torch.view,torch.reshape 可以自动处理输入张量不连续的情况。 tensor= torch.reshape(tensor, shape) 打乱顺序 tensor= tensor[torch.randperm(tensor.size(0))]# Shuffle the first dimension ...
###torch.get_num_threads() → int#torch.set_num_threads(int)### Math operations ###torch.abs(input, out=None) → Tensor 求绝对值#torch.add(input, value, out=None) out=tensor+value#torch.add(input, value=1, other, out=None) out=input+(other∗value)#torch.mul(input,value,out=...
Assigning a Tensor doesn’t have such effect. This is because one might want to cache some temporary state, like last hidden state of the RNN, in the model. If there was no such class as Parameter, these temporaries would get registered too. Parameters data (Tensor)– parameter tensor. ...