torchok
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eora-ai
Production-oriented Computer Vision models training pipeline for common tasks: classification, segmentation, detection and representationš„¤
**Describe the bug** Dependencies in `pyproject.toml` were changed in a [multi-commit PR](https://github.com/eora-ai/torchok/pull/147), but the CI/CD process didn't catch them, resulting to broken dependencies in `main` branch. **To Reproduce** - **Expected...
**Describe the bug** In DDP mode representation metrics doesn't work. Due to in update function gpu embedding convert to cpu embedding and after that in compute method in DDP mode...
**Is your feature request related to a problem? Please describe.** There are no tests for BEiT backbone. The main reason is BEiT can't convert to Jit CPU model, because of...
**Is your feature request related to a problem? Please describe.** Now torchok support computing metrics for many validation datasets, but it compute one metric for both datasets as this two...
**Is your feature request related to a problem? Please describe.** In previous version of TorchOk TIFF images were read with PIL, not OpenCV. Check reading TIFF images. **Describe the solution...
**Describe the bug** There's a command in README for running basic example training but it doesn't work: ``` python -m torchok -cn classification_cifar10 trainer.accelerator='cpu' ``` **To Reproduce** ``` pip install...