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59 Commits (f658a72e722d4401c820d13656f7a51762f94052)

Author SHA1 Message Date
Alexander Soare 6bbc50beb4 make it possible to provide norm_layer via create_model
3 years ago
Ross Wightman 01cb46a9a5 Add gc_efficientnetv2_rw_t weights (global context instead of SE attn). Add TF XL weights even though the fine-tuned ones don't validate that well. Change default arg for GlobalContext to use scal (mul) mode.
3 years ago
Ross Wightman d3f7440650 Add EfficientNetV2 XL model defs
3 years ago
Ross Wightman f8039c7492 Fix gc effv2 model cfg name
3 years ago
Ross Wightman 392368e210 Add efficientnetv2_rw_t defs w/ weights, and gc variant, as well as gcresnet26ts for experiments. Version 0.4.13
3 years ago
Ross Wightman 307a935b79 Add non-local and BAT attention. Merge attn and self-attn factories into one. Add attention references to README. Add mlp 'mode' to ECA.
3 years ago
Ross Wightman 8bf63b6c6c Able to use other attn layer in EfficientNet now. Create test ECA + GC B0 configs. Make ECA more configurable.
3 years ago
Ross Wightman 23c18a33e4 Add efficientnetv2_rw_m weights trained in PyTorch. 84.8 top-1 @ 416 test. 53M params.
4 years ago
Ross Wightman c2ba229d99 Prep for effcientnetv2_rw_m model weights that started training before official release..
4 years ago
Ross Wightman 7077f16c6a Change 21k model naming from _21k to _in21k for consistency with existing 21k models.
4 years ago
Ross Wightman 328249f11a Update README, tweak fine-tune effv2 model names.
4 years ago
Ross Wightman c4f482a08b EfficientNetV2 official impl w/ weights ported from TF. Cleanup/refactor of related EfficientNet classes and models.
4 years ago
Ross Wightman c1cf9712fc Add updated EfficientNet-V2S weights, 83.8 @ 384x384 test. Add PyTorch trained EfficientNet-B4 weights, 83.4 @ 384x384 test. Tweak non TF EfficientNet B1-B4 train/test res scaling.
4 years ago
Ross Wightman e8a64fb881 Test input size for efficientnet_v2s was wrong in last results run
4 years ago
Ross Wightman 21812d33aa Add prelim efficientnet_v2s weights from 224x224 train, eval 83.3 @ 288. Add eca_nfnet_l1 weights, train at 256, eval 84 @ 320.
4 years ago
Ross Wightman fb896c0b26 Update some comments re preliminary EfficientNet-V2 assumptions
4 years ago
Ross Wightman de9dff933a EfficientNet-V2S preliminary model def (for experimentation)
4 years ago
Ross Wightman 5e2e4e7fb6
Merge pull request #502 from khatami-mehrdad/efficientnet_dg
4 years ago
Mehrdad 97f49d163c adding efficientnet_el, efficientnet_es_prunedefficientnet_es_pruned and efficientnet_el_pruned pretrained models to timm/models
4 years ago
Ross Wightman d584e7f617 Support for huggingface hub via create_model and default_cfgs.
4 years ago
Ross Wightman cd72e66eff Bug in last mod for features_only default_cfg
4 years ago
Ross Wightman 867a0e5a04 Add default_cfg back to models wrapped in feature extraction module as per discussion in #294.
4 years ago
Ross Wightman 9c406532bd Add EfficientNet-EdgeTPU-M (efficientnet_em) model trained natively in PyTorch. More sotabench fiddling.
4 years ago
Ross Wightman 512b2dd645 Add new EfficientNet-B3 and RegNetY-3.2GF weights, both just over 82 top-1
4 years ago
Ross Wightman b1f1a54de9 More uniform treatment of classifiers across all models, reduce code duplication.
4 years ago
Ross Wightman ec4976fdba Add EfficientNet-Lite0 weights trained with this code by @hal-314, 75.484 top-1
4 years ago
Ross Wightman 6c17d57a2c Fix some attributions, add copyrights to some file docstrings
4 years ago
Ross Wightman 08016e839d Cleanup FeatureInfo getters, add TF models sourced Xception41/65/71 weights
4 years ago
Ross Wightman c146b54abc Cleanup EfficientNet/MobileNetV3 feature extraction a bit, only two tap locations now, small mobilenetv3 models work
4 years ago
Ross Wightman 6eec3fb4a4 Move FeatureHooks into features.py, switch EfficientNet, MobileNetV3 to use build model helper
4 years ago
Ross Wightman 3b9004bef9 Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces
4 years ago
Ross Wightman d23a2697d0 Working on feature extraction, interfaces refined, a number of models working, some in progress.
4 years ago
Ross Wightman 7be299504f Add missing feature_info() on MobileNetV3, make hook feature output order/type consistent with bottleneck (list, decreasing fmap size)
5 years ago
Ross Wightman eb7653614f Monster commit, activation refactor, VoVNet, norm_act improvements, more
5 years ago
Vyacheslav Shults a7ebe09029 Replace all None by nn.Identity() in all models reset_classifier when False-values num_classes is given.
5 years ago
AFLALO, Jonathan Isaac 9c15d57505 added efficientnet pruned weights
5 years ago
Ross Wightman 1a8f5900ab Update EfficientNet feature extraction for EfficientDet. Add needed MaxPoolSame as well.
5 years ago
Ross Wightman e34074b4da Add final weights for MobileNet-V2 experiments
5 years ago
Ross Wightman a6a5565de7 Fiddling...
5 years ago
Ross Wightman bc998cad91 Experimenting with some MobileNetV2 variations to compare against EfficientNet-Lite
5 years ago
Ross Wightman 3406e582cf Add EfficientNet-Lite results, update README
5 years ago
Ross Wightman bd05258f7b EfficientNet-Lite model added w/ converted checkpoints, validation in progress...
5 years ago
Ross Wightman 43225d110c Unify drop connect vs drop path under 'drop path' name, switch all EfficientNet/MobilenetV3 refs to 'drop_path'. Update factory to handle new drop args.
5 years ago
Ross Wightman 53c47479c4 Batch validation batch size adjustment, tweak L2 crop pct
5 years ago
Ross Wightman 08553e16b3 Merge branch 'master' into attention
5 years ago
Ross Wightman ba15ca47e8 Add ported EfficientNet-L2, B0-B7 NoisyStudent weights from TF TPU
5 years ago
Ross Wightman f902bcd54c Layer refactoring continues, ResNet downsample rewrite for proper dilation in 3x3 and avg_pool cases
5 years ago
Ross Wightman a99ec4e7d1 A bunch more layer reorg, splitting many layers into own files. Improve torchscript compatibility.
5 years ago
Ross Wightman 13746a33fc Big move, layer modules and fn to timm/models/layers
5 years ago
Ross Wightman 5c4991a088 Add PyTorch trained EfficientNet-ES weights from Andrew Lavin
5 years ago