错误: divide by zero encountered in divide 形状不匹配且无法广播:如果两个tensor的形状不匹配,且无法通过广播机制使它们匹配,那么在执行除法运算时会抛出一个RuntimeError。 python x = torch.tensor([1.0, 2.0, 3.0]) y = torch.tensor([[1.0], [2.0]]) try: result = x / y except RuntimeError...
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)#torch.Size([])print(b.size())#torch.Size([])#向量x = torch.tensor([2.3])
>>> torch.gather(t,0,torch.LongTensor([[0,0],[1,0]])) tensor([[1., 2.], [3., 2.]]) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 三、数学运算 Add/minus/multiply/divide Matmul(矩阵式相乘) Pow Sqrt/rsqrt Round basic(+ - * / add sub mul div) 建...
out (Tensor, optional) – 目标张量 沿给定轴dim,将输入索引张量index指定位置的值进行聚合。 对一个3维张量,输出的定义: view code example: view code 三、数学运算 Add/minus/multiply/divide Matmul(矩阵式相乘) Pow Sqrt/rsqrt Round basic(+ - * / add sub mul div) ...
torch.Tensor.new_ones Supported 6 torch.Tensor.new_zeros Supported 7 torch.Tensor.is_cuda Supported 8 torch.Tensor.is_quantized Supported 9 torch.Tensor.device Supported 10 torch.Tensor.ndim Supported 11 torch.Tensor.T Supported 12 torch.Tensor.abs ...
ShortTensor Size StaticRuntime Storage Stream StreamObjType StringType TYPE_CHECKING Tensor TensorType ThroughputBenchmark TracingState TupleType Type USE_GLOBAL_DEPS USE_RTLD_GLOBAL_WITH_LIBTORCH Use Value _C _StorageBase _VF __all__ __annotations__ __builtins__ __cached__ __config__ __...
目前JS-Torch已经支持 Add、Subtract、Multiply、Divide 等张量操作,同时也支持Linear、MultiHeadSelfAttention、ReLU 和 LayerNorm 等常用的深度学习层。 Tensor Operations Add Subtract Multiply Divide Matrix Multiply Power Square Root Exponentiate Log Sum
As a side note, if you find yourself wishing for the behavior of option 1, and it's true that the tensor you will call .backward() on (probably loss) is indeed a scalar which has the same value on every worker node, then you can just divide your tensor-to-be-differentiated by the...
randn(10000).to(device="cuda:0")# 用编译优化后的函数来执行程序compiled_fn(input_tensor)...
backend="inductor")input_tensor=torch.randn(10000).to(device="cuda:0")# 用编译优化后的函数来执...