- 24 Jun, 2022 1 commit
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Vasilis Vryniotis authored
* Adding MViT v2 architecture (#6105) * Adding mvitv2 architecture * Fixing memory issues on tests and minor refactorings. * Adding input validation * Adding docs and minor refactoring * Add `min_temporal_size` in the supported meta-data. * Switch Tuple[int, int, int] with List[int] to support easier the 2D case * Adding more docs and references * Change naming conventions of classes to follow the same pattern as MobileNetV3 * Fix test breakage. * Update todos * Performance optimizations. * Add support to MViT v1 (#6179) * Switch implementation to v1 variant. * Fix docs * Adding back a v2 pseudovariant * Changing the way the network are configured. * Temporarily removing v2 * Adding weights. * Expand _squeeze/_unsqueeze to support arbitrary dims. * Update references script. * Fix tests. * Fixing frames and preprocessing. * Fix std/mean values in transforms. * Add permanent Dropout and update the weights. * Update accuracies. * Fix documentation * Remove unnecessary expected file. * Skip big model test * Rewrite the configuration logic to reduce LOC. * Fix mypy
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- 26 Aug, 2021 1 commit
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Vasilis Vryniotis authored
* Adding code skeleton * Adding MBConvConfig. * Extend SqueezeExcitation to support custom min_value and activation. * Implement MBConv. * Replace stochastic_depth with operator. * Adding the rest of the EfficientNet implementation * Update torchvision/models/efficientnet.py * Replacing 1st activation of SE with SiLU. * Adding efficientnet_b3. * Replace mobilenetv3 assets with custom. * Switch to standard sigmoid and reconfiguring BN. * Reconfiguration of efficientnet. * Add repr * Add weights. * Update weights. * Adding B5-B7 weights. * Update docs and hubconf. * Fix doc link. * Fix typo on comment.
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- 06 Aug, 2021 1 commit
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Vincent Moens authored
using nn.init.trunc_normal_ instead of scipy.stats.truncnorm Co-authored-by:Vincent Moens <vmoens@fb.com>
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- 22 Oct, 2019 1 commit
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fbbradheintz authored
* correctness test implemented with old test architecture * reverted an unneeded change, ran flake8 * moving to relative tolerance of 1 part in 10k for classification correctness checks * going down to 1 part in 1000 for correctness checks bc architecture differences * one percent relative tolerance
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