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SWE-Gym (training set sample): every task, with its verdict

SWE-Gym, published by the SWE-Gym authors. Paper authors: Jiayi Pan, Xingyao Wang, Graham Neubig, Navdeep Jaitly, Heng Ji, Alane Suhr and Yizhe Zhang. SWE-Gym (arXiv) · This page covers a random 100-task sample of the 2,438 training tasks (SWE-Gym/SWE-Gym on Hugging Face). The sample is the 100 instance IDs with the lowest SHA-256 of "own1:swe-gym:<instance_id>", so anyone can redraw it. · Report a correction · flags show what the public text and git history contain: public exposure was possible, nothing more.

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TaskVerdictIssue title
Project-MONAI__MONAI-1107no overlap found (rule check)AHNet can't support input channels > 1
Project-MONAI__MONAI-1684no overlap found (rule check)Densenet pretrained weights issue
Project-MONAI__MONAI-1832no overlap found (rule check)Potentially insufficient shuffling in SmartCacheDataset
Project-MONAI__MONAI-2436no overlap found (rule check)support dynamic data list for the dataset APIs (2/July)
Project-MONAI__MONAI-3946no overlap found (rule check)The first convolutional layer in ResNet is hardcoded to be anisotropic
Project-MONAI__MONAI-4282no overlap found (rule check)Inconsistency networks.layer.AffineTransform and transforms.Affine
Project-MONAI__MONAI-4775no overlap found (rule check)pytorch numpy unification error
Project-MONAI__MONAI-5306no overlap found (rule check)Add authentication option for bundle APIs
Project-MONAI__MONAI-5640no overlap found (rule check)More robust `is_supported_format` suffix check
Project-MONAI__MONAI-5877no overlap found (rule check)`RandHistogramShift` transform gives `nan` values for input when all values are 0
Project-MONAI__MONAI-5950no overlap found (rule check)Why the data shape are different through transform "spacingd.
Project-MONAI__MONAI-6127no overlap found (rule check)RandCropByLabelClasses, internal variable "ratios" is mutated
Project-MONAI__MONAI-6413no overlap found (rule check)Experiment tracking with MonaiAlgo
Project-MONAI__MONAI-6429no overlap found (rule check)spatial resample -- adaptive padding mode when switching the backends