def forward(self, in_out_tensor : torch.Tensor): as_strided_ = in_out_tensor.as_strided_(size = [2, 2], stride = [2, 2], storage_offset = 7); in_out_tensor = None return (as_strided_,) mod = Repro() # Setup debug minifier compiler torch._dynamo.debug_utils.MINIFIER_SPAW...
I provide arguments size and stride, but above code throw an exception TypeError: as_strided() missing 3 required positional argument: "input", "size", "stride". I know I need to provide arguments input, but I think the error message should be shown as TypeError: as_strided() missing ...
1], storage_offset=1) inspect([a, b]) b = torch.as_strided(a, size...
stride(): with torch.no_grad(): copy_param.set_(copy_param.clone() .as_strided(param.size(), param.stride()) .copy_(copy_param)) copy_param.requires_grad = param.requires_grad else: self._module_copies = [self.module] self.modules_params = [list(parameters(m)) for m in self....
>>> torch.is_tensor(x)02. set_default_dtype 和 get_default_dtype03.转换 as from to from_numpy frombuffer asarray as_tensor as_strided03. Creation create torch.Tensor torch.rand() torch.rand_like() torch.randn() torch.randn_like() torch.randint() torch.randint_like() torch.randperm(...
'as_strided_', 'as_subclass', 'asin', 'asin_', 'asinh', 'asinh_', 'atan', 'atan2', 'atan2_', 'atan_', 'atanh', 'atanh_', 'backward', 'baddbmm', 'baddbmm_', 'bernoulli', 'bernoulli_', 'bfloat16', 'bincount',
>>>x=np.array([1,2,3])>>>torch.as_tensor(x)tensor([1, 2, 3], dtype=torch.int32) 3、torch.as_strided() torch.as_strided(input,size,stride,storage_offset=0) 创建tensor的视图,具有指定的大小形状,步长和storage的偏移量 input:输入的Tensor ...
importtorchimportnumpyasnp t=torch.Tensor()type(t)#输出的结果是“torch.Tensor”print(t.dtype)#输出的结果是“torch.float32”print(t.device)#输出的结果是“cpu”print(t.layout)#输出的结果是“torch.strided”device=torch.device('cuda:0')device#输出的结果是“device(type='cuda' , index=0)”...
手动输入的数据设计如下函数:tensor, zeros, zeros_like, ones, ones_like,arange,range,linspace,logspace,eye,empty,empty_like,empty_strided,full,full_like。 用户9875047 2022/07/04 2220 使用C# 入门深度学习:Pytorch 基础 基础入门c#深度学习pytorch 本文内容介绍 Pytorcn 的基础 API,主要是数组的创建方式...
aten::as_strided_ 0.13% 11.674ms 0.13% 11.674ms 1.946us 6000 aten::div 0.11% 10.246ms 0.13% 12.288ms 122.876us 100 aten::batch_norm 0.10% 8.894ms 15.42% 1.421s 710.700us 2000 aten::convolution 0.08% 7.478ms 17.71% 1.632s 815.997us 2000 ...