Features, bug fixes and housekeeping

PyTorch-Ignite 0.4.9 - Release Notes

New Features

• Added whitelist argument to log only desired weights/grads with experiment tracking system handlers: #2550, #2523
• Added ReduceLROnPlateauScheduler parameter scheduler: #2449
• Added filename components in Checkpoint: #2498
• Added missing args to ModelCheckpoint, parity with Checkpoint: #2486
• [BC-breaking] LRScheduler is now attachable to Events.ITERATION_STARTED: #2496

Bug fixes

• Fixed zero_grad place in create_supervised_trainer resulting in grad zero logs: #2560, #2559, #2555, #2547
• Fixed bug in Checkpoint when loading a single non-nn.Module object: #2487
• Removed warning in DDP if Metric.reset/update are not decorated: #2549
• [BC-breaking] Fixed SSIM metric implementation and issue with variable batch inputs: #2564, #2563
  • compute method now returns float instead of torch.Tensor

Housekeeping (docs, CI, examples, tests, etc)

• #2552, #2543, #2541, #2534, #2531, #2530, #2529, #2528, #2526, #2525, #2521, #2518, #2512, #2509, #2507, #2506, #2497, #2494, #2493, #2490, #2485, #2483, #2477, #2476, #2474, #2473, #2469, #2463, #2461, #2460, #2457, #2454, #2450, #2448, #2446, #2445, #2442, #2440, #2439, #2435, #2433, #2431, #2430, #2428, #2427,

Acknowledgments

🎉 Thanks to our community and all our contributors for the issues, PRs and 🌟 ⭐️ 🌟 !
💯 We really appreciate your implication into the project (in alphabetical order):

@Davidportlouis, @DevPranjal, @Ishan-Kumar2, @KevinMusgrave, @Moh-Yakoub, @asmayer, @divo12, @gorarakelyan, @jreese, @leotac, @nishantb06, @nmcguire101, @sadra-barikbin, @sayantan1410, @sdesrozis, @vfdev-5, @yuta0821