torch.nan_to_num 是 支持bf16,fp16,fp32,uint8,int8,int16,int32,int64,bool torch.neg 是 支持bf16,fp16,fp32,int8,int32,int64,complex64,complex128 torch.negative 是 支持bf16,fp16,fp32,int8,int32,int64,complex64,complex128 torch.positive ...
N: 100, Result: nan Expected behavior: The function should return infinity for all tensor sizes, as it does for the non-compiled version and for float32. Collaborator In the generated code we have: @isurufyou could fix this by bitcasting the float to an integer first before doing the re...
最近加上了decoder,融合计算ctc_loss与att_loss(交叉熵损失),nan又出现了(收敛过程中直接出现nan,此前并没有先出现inf,目前没搞懂) 那就来看一下torch的cross entropy loss 以为是LogSoftmax在搞鬼,但仔细想想,logits经过log_softmax并不会出现inf或者nan的值,那么在选择某些值(标签id对应的logp)进行相加后应该...
I wanted to clarify that nan can indeed be passed through, ask if any code changed are required to support this officially, and suggest this could be added to the docs which state currently zero_division [float] – Should be 0 or 1., e.g. hererob...
torch.nan_to_num Supported torch.range Supported torch.linspace Supported torch.logspace Partly supported Function is constrained torch.eye Supported torch.empty Supported torch.empty_like Supported torch.eig Partly supported Currently not support on GPU torch.full Supported torch.full_like Sup...
>>> a = torch.randn(4) >>> a -0.6366 0.2718 0.4469 1.3122 [torch.FloatTensor of size 4] >>> torch.acos(a) 2.2608 1.2956 1.1075 nan [torch.FloatTensor of size 4]torch.add()torch.add(input, value, out=None)对输入张量input逐元素加上标量值value,并返回结果到一个新的张量out,即 \( ...
torch.allclose(input, other, rtol=1e-05, atol=1e-08, equal_nan=False) torch.norm() 求模/求范数 模就是二范数 torch.norm(input, p='fro', dim=None, keepdim=False, out=None, dtype=None) 输入代码 import torch rectangle_height = 3 rectangle_width = 4 inputs = torch.randn(rectangle...
backward() # scaler 更新参数,会先自动unscale梯度 # 如果有nan或inf,自动跳过 scaler.step(optimizer) # scaler factor更新 scaler.update() 2.1 autocast类 ``autocast(enable=True)`` 可以作为上下文管理器和装饰器来使用,给算子自动安排按照 FP16 或者 FP32 的数值精度来操作。 2.1.1 autocast算子 ...
allclose(other, rtol=1e-05, atol=1e-08, equal_nan=False) → Tensor apply_(callable) → Tensor argmax(dim=None, keepdim=False) → LongTensor argmin(dim=None, keepdim=False) → LongTensor argsort(dim=-1, descending=False) → LongTensor ...
torch.autograd提供实现任意标量值函数的自动微分的类和函数。它只需要对现有代码进行最小的更改—您只需要声明张量s,对于该张量,应该使用requires_grad=True关键字计算梯度。 代码语言:javascript 复制 torch.autograd.backward(tensors,grad_tensors=None,retain_graph=None,create_graph=False,grad_variables=None)[sou...