mmpretrain/configs/levit/levit-384_8xb256_in1k.py

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[Feature] Support LeViT backbone. (#1238) * 网络搭建完成、能正常推理 * 网络搭建完成、能正常推理 * 网络搭建完成、能正常推理 * 添加了模型转换未验证,配置文件 但有无法运行 * 模型转换、结构验证完成,可以推理出正确答案 * 推理精度与原论文一致 已完成转化 * 三个方法改为class 暂存 * 完成推理精度对齐 误差0.04 * 暂时使用的levit2mmcls * 训练跑通,训练相关参数未对齐 * '训练相关参数对齐'参数' * '修复训练时验证导致模型结构改变无法复原问题' * '修复训练时验证导致模型结构改变无法复原问题' * '添加mixup和labelsmooth' * '配置文件补齐' * 添加模型转换 * 添加meta文件 * 添加meta文件 * 删除demo.py测试文件 * 添加模型README文件 * docs文件回滚 * model-index删除末行空格 * 更新模型metafile * 更新metafile * 更新metafile * 更新README和metafile * 更新模型README * 更新模型metafile * Delete the model class and get_LeViT_model methods in the mmcls.models.backone.levit file * Change the class name to Google Code Style * use arch to provide default architectures * use nn.Conv2d * mmcv.cnn.fuse_conv_bn * modify some details * remove down_ops from the architectures. * remove init_weight function * Modify ambiguous variable names * Change the drop_path in config to drop_path_rate * Add unit test * remove train function * add unit test * modify nn.norm1d to build_norm_layer * update metafile and readme * Update configs and LeViT implementations. * Update README. * Add docstring and update unit tests. * Revert irrelative modification. * Fix unit tests * minor fix Co-authored-by: mzr1996 <mzr1996@163.com>
2023-01-17 17:43:42 +08:00
_base_ = [
'../_base_/models/levit-256-p16.py',
'../_base_/datasets/imagenet_bs64_swin_224.py',
'../_base_/schedules/imagenet_bs2048_adamw_levit.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
backbone=dict(arch='384', drop_path_rate=0.1),
head=dict(in_channels=768),
)
# dataset settings
train_dataloader = dict(batch_size=256)