Assign User on Comment torch.library.opcheck doesn't check strides for CPU Tensors #167339 Sign in to view logs Summary Jobs assign Run details Usage Workflow file Triggered via issue March 31, 2025 17:19 malfet commented on #149468 284b766 Status Success Total duration 11s Artifacts – assigntome-docathon.ym...
🐛 Describe the bug In instances where torch.compile is combined with DDP and checkpointing, the following error is raised: torch.utils.checkpoint.CheckpointError: torch.utils.checkpoint: A different number of tensors was saved during the...
Functions load and save are equivalents of torch.load and torch.save but expect torch.Tensors to be wrapped with classes from the mapping module. Additionally, load expects the sharded state dict argument as a guidance for loading the sharded tensors....
... File "ie_api.pyx", line 980, in openvino.inference_engine.ie_api.IENetwork.__cinit__ RuntimeError: dimension (0) in node dim must be a positive integer: at offset 16089 Any help in appreciation. Sincerely,Ben. Translate Tags: Computer Vision General Support Intel® Distri...
When using a 1-dim tensor, we get a runtime error. optimizer = torch.optim.SGD(model.parameters(), lr=torch.tensor([0.01]).cuda()) scheduler = torch.optim.lr_scheduler.LinearLR(optimizer, total_iters=5) RuntimeError: fill_ only supports 0-dimension value tensor but got tensor with ...
if(!dimension.has_value()) { @@ -36,10 +36,10 @@ Tensor & cross_out(Tensor & out, const Tensor & input, const Tensor & other, con break; } } AT_CHECK(dim >= 0, "no dimension of size 3 in input"); TORCH_CHECK(dim >= 0, "no dimension of size 3 in input"); } else...
python xla/benchmarks/experiment_runner.py --suite-name torchbench --dynamo openxla --xla PJRT --accelerator cuda --test<test>--no-resume -k<model> Affected Benchmarks (eval) doctr_det_predictor (train) torch_multimodal_clip Environment ...
🐛 Describe the bug import torch import torch.nn as nn input_tensor = torch.randn(1, 8, 14, 14) # (batch_size, in_channels, height, width) conv_transpose = nn.ConvTranspose2d( in_channels=8, out_channels=8, kernel_size=[3, 3], stride=[1, ...
For tuples, the shapechecker will ensure that the number of fields in the tuple matches the dimension size. Quickstart import shapecheck @shapecheck.check_args(x=(1,3,3,4,5), img=("N", ("R", "G", "B"), "H", "W")) def f(x, img): ... x = torch.rand((1, 3, 3,...
🐛 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...