) ===> Loading datasets ===> Building model RBPN Pre-trained SR model is loaded. Traceback (most recent call last): File "eval.py", line 82, in <module> input = Variable(input).cuda(gpus_list[0]) TypeError: Variable data has to be a tensor, but got builtin_function_or_method...
Open TensorBoard using the get_app_url function as an estimator class method Open TensorBoard through the SageMaker AI console Load and visualize output tensors using the TensorBoard application Delete unused TensorBoard applications SageMaker Debugger ...
distributed/test_dynamo_distributed.py::TestFakeDistributedSingleProc::test_call_method_forward pull / linux-jammy-py3.9-gcc11 / test (distributed, 2, 2, lf.linux.2xlarge) (gh) distributed/_tensor/test_dtensor_compile.py::TestDTensorCompile::test_dynamo_to_local_kwargs_forward_hook pull /...
Open TensorBoard using the get_app_url function as an estimator class method Open TensorBoard through the SageMaker console Load and visualize output tensors using the TensorBoard application Delete unused TensorBoard applications SageMaker Debugger Supported frameworks and algorithms Debugger architecture Tutori...
MethodDL ‑ TMVA-DNN-CNN-MethodDL TMVA-DNN-CNN-PoolingLayer-CPU ‑ TMVA-DNN-CNN-PoolingLayer-CPU TMVA-DNN-CNN-Pred-CPU ‑ TMVA-DNN-CNN-Pred-CPU TMVA-DNN-CNN-Reshape-CPU ‑ TMVA-DNN-CNN-Reshape-CPU TMVA-DNN-CNN-RotWeights-CPU ‑ TMVA-DNN-CNN-RotWeights-CPU TMVA-DNN-Data-...
RuntimeError: builtin cannot be used as a value: at venv/lib/python3.6/site-packages/torchvision-0.5.0a0+c7c2085-py3.6-linux-x86_64.egg/torchvision/models/detection/_utils.py:14:56 def zeros_like(tensor, dtype): # type: (Tensor, int) -> Tensor return torch.zeros_like(tensor, dtype...
MethodDL ‑ TMVA-DNN-CNN-MethodDL TMVA-DNN-CNN-PoolingLayer-CPU ‑ TMVA-DNN-CNN-PoolingLayer-CPU TMVA-DNN-CNN-Pred-CPU ‑ TMVA-DNN-CNN-Pred-CPU TMVA-DNN-CNN-Reshape-CPU ‑ TMVA-DNN-CNN-Reshape-CPU TMVA-DNN-CNN-RotWeights-CPU ‑ TMVA-DNN-CNN-RotWeights-CPU TMVA-DNN-Data-...
This method of initializing the centroid has been reformed over the years with a better seeding method called K-means++++ as stated by Arthur et al [47]. The main goal for K-means is to reduce the Sum of Squared Distance for each cluster at every iteration. This is achieved by ...