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Ross Wightman
e8ca45854c
More models in sotabench, more control over sotabench run, dataset filename extraction consistency
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4 years ago |
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__init__.py
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More uniform treatment of classifiers across all models, reduce code duplication.
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4 years ago |
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activations.py
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activations_jit.py
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activations_me.py
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adaptive_avgmax_pool.py
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Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
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4 years ago |
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anti_aliasing.py
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blur_pool.py
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cbam.py
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AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
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4 years ago |
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classifier.py
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More uniform treatment of classifiers across all models, reduce code duplication.
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4 years ago |
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cond_conv2d.py
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config.py
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conv2d_same.py
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conv_bn_act.py
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create_act.py
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create_attn.py
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create_conv2d.py
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create_norm_act.py
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drop.py
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eca.py
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AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
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4 years ago |
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evo_norm.py
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Fix a silly bug in Sample version of EvoNorm missing x* part of swish, update EvoNormBatch to accumulated unbiased variance.
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4 years ago |
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helpers.py
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inplace_abn.py
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median_pool.py
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mixed_conv2d.py
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norm_act.py
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padding.py
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pool2d_same.py
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se.py
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AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
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4 years ago |
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selective_kernel.py
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AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
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4 years ago |
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separable_conv.py
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space_to_depth.py
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split_attn.py
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split_batchnorm.py
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test_time_pool.py
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More models in sotabench, more control over sotabench run, dataset filename extraction consistency
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4 years ago |
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weight_init.py
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