Skip to content
Snippets Groups Projects

Repository graph

You can move around the graph by using the arrow keys.
Select Git revision
  • aifmd_dataset_support
  • main default protected
  • robertos-branch
  • v1.3.1
  • v1.3.0
  • v1.2.0
  • v1.1.0
  • v1.0.2
  • v1.0.1
  • v1.0.0
  • v1.0.0b0
  • v1.0.0a0
12 results
Created with Raphaël 2.2.010Sep985432130Aug232221207611Jul109432128Jun26242113107432129May282524228732130Apr2922212019181716854229Mar21191817161413118765128Feb272624222019161413129875229Jan[models.classify] Fix alexnet pre-trained init; Log message improvements[data.detect.cxr8] Add database[data.detect] Fix multiple docstrings[tests.test_dataset] Fix import[data] add object detection databases for lung[data] Homogenize raw-data loaders[tests.classify.test_tbx11k] Fix bounding-box tests (closes #36)[doc] Remove optimizer_step from doc/extras; Better annotate exceptions (closes #3)Clean-up[pixi] Avoid main package on build/qa environmentsIncreased latest version to 1.2.1b0 [skip ci]Increased stable version to 1.2.0v1.2.0v1.2.0[doc] Fix documentation[scripts.train,scripts.experiment] Improve help messages[scripts.train,scripts.experiment] Allow loading initial weights (prior to training start) from models with different numbers of outputs[scripts.predict] Allow loading model weights from URL[engine.classify.saliency.interpretability] Fix sample data access[scripts.predict,scripts.train,engine.trainer] Allow resetting of model inputs to work correctly during prediction[data.datamodule] Fix minor typing typo[models.losses] Improve calculation of loss weightsMerge branch 'issue-68-multi-label' into 'main'Implements multi-label support for BCEWithLogitsLoss and MOONBCEWithLogitsLoss[data.segment.drionsdb] Fix implementation after refactoring[models.losses] Centralize all custom losses in a single place[scripts.classify.evaluate] By default, do not calculate credible regions (slow on large datasets)[data.classify.nih_cxr14] Fix file access[data.datamodule] Always set the mp context to "spawn"[data.datamodule] Update issue link on warning[data.datamodule] Use torch.multiprocessing instead of plain one[tests] Add test for cached dataset[data.datamodule] Fix comment[data.datamodule] Disables multiprocessing dataset caching on Linux[data.datamodule] Use spawn on linux as well[tests.test_transforms] Streamline tests[tests.test_transforms] Minor adjustment at reference after to_tensor() deprecation[data.classify,data.segment] Avoid to_tensor() torchvision deprecation[pyproject] Downgrade pytorch to avoid https://github.com/conda-forge/pytorch-cpu-feedstock/issues/254[data.classify.nih_cxr14] Avoid auto-conversion to float64 tensors[models.classify.densenet,alexnet] Fix imagenet normalizer [ci skip]Increased latest version to 1.1.1b0 [skip ci]