Related Issues (20)
- Loading large models with fabric, FSDP and empty_init=True does not work
- Unable to extract confusion matrix as a metric from trainer HOT 1
- Torchmetrics Accuracy issue when dont shuffle test data. HOT 1
- ModelCheckpoint: Using save_top_k, only the first k models are stored, not the best k models HOT 2
- trainer.fit from checkpoint without performance improvement will break 'last' link to checkpoint on window11
- Exception in RecordFunction callback: state_ptr INTERNAL ASSERT FAILED at "../torch/csrc/profiler/standalone/nvtx_observer.cpp":115
- `ckpt_path` in `Trainer` accepts URIs to automatically load checkpoints from remote paths
- When doing tuner.scale_batch_size, check full dataset length first
- RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [68]] is at version 3; expected version 2 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True). HOT 1
- Is the Lightning App deprecated? (Lightning App doc is not found) HOT 1
- Dynamically link arguments in `LightningCLI`? HOT 2
- Support get optimizer and lr_schedulers from deepspeed config
- Validation dataloader is added to train dataloader after first epoch
- Add dog has an error: FileNotFoundError: HOT 1
- Resume training, how to change learning scheduler? HOT 1
- Possible bug in recognizing `mps` accelerator even though PyTorch seems to register the `mps` device?
- Error loading a saved model to run inference (using ddp_notebook strategy) HOT 1
- AttributeError: module 'pytorch_lightning.callbacks' has no attribute 'ProgressBarBase'. Did you mean: 'ProgressBar'?
- Using the MLflow logger produces Inconsistent metric plots HOT 2
- can't fit with ddp_notebook on a Vertex AI Workbench instance (CUDA initialized)
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