🐛 Describe the bug Hi! I noticed some strange behavior of with torch.backends.cudnn.flags(deterministic=True) for ctc loss backward on CUDA. Main problem is that with torch.backends.cudnn.flags(deterministic=True) doesn't give an excepti...
🐛 Describe the bug On CUDA with use_deterministic_algorithms(True), advanced indexing assignment has no effect on target tensors with more than one effective dimension when the source tensor has one dimension. To reproduce import torch t...
upsample_bilinear2d_backward_out_cuda是PyTorch中的一个函数,用于在CUDA设备上执行双线性插值上采样的反向传播计算。双线性插值是一种常用的图像缩放技术,它通过计算四个最近邻像素的加权平均值来估计缩放后的像素值。 确定性实现问题: 在PyTorch中,torch.use_deterministic_algorithms(True)会启用确定性算法,以确保在...
Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A10G Nvidia driver version: 555.42.06 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.2 ...
cumsumuse_deterministic_algorithms(True)and input is CUDA. 🔗 Helpful Links C++ docs built from this PR ❓ Need help or want to give feedback on the CI? Visit thebot commands wikior ouroffice hours Note: Links to docs will display an error until the docs builds have been completed. ...
randn(2, 3, 4, requires_grad=True) self.assertONNX(lambda x: torch.cumsum(x, dim=1), x, opset_version=11) self.assertONNX(lambda *args: torch.cumsum(*args, dim=1), x, opset_version=11) def test_dict(self): class MyModel(torch.nn.Module):...
GPU True False ATen/native/cudnn/LossCTC.cpp No USE_CUDNN is a boolean variable re-generated for every batch here I have attached a code sample for reproducing the non-deterministic loss function. Even though the difference in this code sample is small, it gets larger in training of spee...
This is not true. TensorFlow's support for GPU determinism is now at least comparable to that of PyTorch. Both TensorFlow and PyTorch have (had) various ops that function non-deterministically on GPU, some that have already been addressed, some that are in line to be addressed, some that ...