training_args=TrainingArguments(per_device_train_batch_size=1,gradient_accumulation_steps=4,gradient_checkpointing=True,**default_args)trainer=Trainer(model=model,args=training_args,train_dataset=ds)result=trai
usr/local/lib/python3.8/dist-packages/_XLAC.cpython-38-x86_64-linux-gnu.so(_ZN9torch_xla15TensorToXlaDataERKN2at6TensorERKNS_6DeviceEb+0x64d)[0x7f086098b9ed]/usr/local/lib/python3.8/dist-packages/_XLAC.cpython-38-x86_64-linux-gnu.so(_ZNK9torch_xla9XLATensor19GetIrValueForTensorERKN2...
torch.rsqrt(a) 返回平方根的倒数torch.mean std prod sum var tanh max min(input) 返回均值 标准差 累乘 求和 方差 双曲正切 最大 最小值torch.equal(Tensor1,Tensor2)两个张量进行比较,如果相等返回true,否则返回falsetorch.bmm(a, b) 执行两个张量之间的批矩阵间乘积( batch matrix-matrix product),记...
🐛 Bug The function torch.pow doesn't seem to check if the input tensors are on the same device. To Reproduce Steps to reproduce the behavior: a = torch.tensor(2.0, device=torch.device('cuda:0')) b = torch.tensor(1.0) torch.pow(a,b) Expec...
... [ 15%] Building NVCC (Device) object lib/THC/CMakeFiles/THC.dir/THC_generated_THCTensorMathReduce.cu.o 2 errors detected in the compilation of "/tmp/tmpxft_00002141_00000000-4_THCTensorMath.cpp4.ii". CMake Error at THC_generated_THCTensorMath.cu.o.cmake:267 (message): Error ...
File "/usr/local/python3.7.5/lib/python3.7/site-packages/torch_npu/utils/device_guard.py", line 38, in wrapper return func(*args, **kwargs) File "/usr/local/python3.7.5/lib/python3.7/site-packages/torch_npu/utils/tensor_methods.py", line 66, in _npu return torch_npu._C.npu...
testtensor(17.3666, device='cuda:0') 0.9334 7.模型保存 torch.save(net, S_TORCH_MODEL_FULL_PATH) torch.save(net.state_dict(), S_TORCH_MODEL_PARAMS_PATH) 8.模型加载和加载模型使用 print("load torch model and pred test data") net_load = torch.load(S_TORCH_MODEL_FULL_PATH, ...
device (torch.device): Desired device of returned tensor. Returns: (torch.Tensor): A tensor of shape (num_grid, size[0]*size[1], 2) that contains coordinates for the regular grids. """ affine_trans = torch.tensor([[[1., 0., 0.], [0., 1., 0.]]], device=device) grid = ...
@torch.compiledeff(x:torch.Tensor):returnx.to(torch.float32).to(torch.float16)f(torch.empty([128],dtype=torch.float64,device="cuda"))# Before joint_graph_passesgraph():%arg0_1:[num_users=1]=placeholder[target=arg0_1]%convert_element_type:[num_users=1]=call_function[target=torch.ops...
File"/home/ems/miniconda3/lib/python3.10/site-packages/torch/utils/backend_registration.py", line 153,inwrap_tensor_to device_idx = _normalization_device(custom_backend_name, device) File"/home/ems/miniconda3/lib/python3.10/site-packages/torch/utils/backend_registration.py", line 109,in_normali...