默认情况下,NaN s 被替换为 0,正无穷大被替换为 input 的dtype 可表示的最大有限值,负无穷大被替换为 input 的dtype 可表示的最小有限值。 例子: >>> x = torch.tensor([float('nan'), float('inf'), -float('inf'), 3.14]) >>> torch.nan_to_num(x) tensor([ 0.0000e+00, 3.4028e+38, ...
taskID[281467393405408:453], opNames[NanToNum209], opType[NanToNum], status[1], result[exception], File[/usr/local/Ascend/ascend-toolkit/8.0.RC2.alpha001/opp/built-in/op_impl/ai_core/tbe/impl/dynamic/nan_to_num.py], compile result{single ...
importtorch# 创建一个包含NaN值的张量data=torch.tensor([[1.0,float('nan'),2.0],[3.0,4.0,float('nan')],[5.0,6.0,7.0]])print("原始数据:")print(data)# 将NaN值替换为0data_cleaned=torch.nan_to_num(data,nan=0.0)print("处理后的数据:")print(data_cleaned) 1. 2. 3. 4. 5. 6. 7....
我们可以使用torch.isnan()函数检查张量中是否存在NaN值,并输出结果: has_nan=torch.isnan(data).any()# 检查张量中是否存在NaN值print("数据中存在NaN值:",has_nan.item())# 打印提示信息 1. 2. 4. 替换NaN值为0 一旦我们确认数据中存在NaN值,就可以使用torch.nan_to_num()函数将其替换为0: data_c...
nanquantile(self, q, dim=None, keepdim=False) nansum(self, dim=None, keepdim=False, dtype=None) nan_to_num(self, nan=0.0, posinf=None, neginf=None) nan_to_num_(self, nan=0.0, posinf=None, neginf=None) narrow(self, dimension, start, length) ...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - torch.nan_to_num does not support complex64 data type under torch.compile · pytorch/pytorch@75a4b73
pytorch/pytorchPublic NotificationsYou must be signed in to change notification settings Fork23.5k Star87.5k Assign User on Comment [MPS] Enablenan_to_numfor bfloat16#82841 Sign in to view logs Triggered via issueSeptember 30, 2024 16:07 ...
mean(np.nan_to_num(mask * mae)) 创建自定义数据集的demo import torch def generate_torch_datasets(data, seq_len, pre_len, time_len=None, split_ratio=0.8, normalize=True): train_X, train_Y, test_X, test_Y = generate_dataset(data, seq_len, pre_len, time_len=time_len, split_...
3.训练过程loss或量化参数出现NAN 有两种可以尝试的方法：使用不同的量化qconfig。不同的qconfig对于训练...
1.溢出错误:由于FP16的动态范围比FP32位的狭窄很多,因此,在计算过程中很容易出现上溢出和下溢出,溢出之后就会出现"NaN"的问题。在深度学习中,由于激活函数的梯度往往要比权重梯度小,更易出现下溢出的情况 2.舍入误差 舍入误差指的是当梯度过小时,小于当前区间内的最小间隔时,该次梯度更新可能会失败: ...