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175 lines
4.5 KiB
175 lines
4.5 KiB
# RexNet
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**Rank Expansion Networks** (ReXNets) follow a set of new design principles for designing bottlenecks in image classification models. Authors refine each layer by 1) expanding the input channel size of the convolution layer and 2) replacing the [ReLU6s](https://www.paperswithcode.com/method/relu6).
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{% include 'code_snippets.md' %}
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## How do I train this model?
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You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
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## Citation
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```BibTeX
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@misc{han2020rexnet,
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title={ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network},
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author={Dongyoon Han and Sangdoo Yun and Byeongho Heo and YoungJoon Yoo},
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year={2020},
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eprint={2007.00992},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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<!--
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Models:
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- Name: rexnet_100
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Metadata:
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FLOPs: 509989377
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Epochs: 400
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Batch Size: 512
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Training Data:
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- ImageNet
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Training Techniques:
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- Label Smoothing
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- Linear Warmup With Cosine Annealing
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 4x NVIDIA V100 GPUs
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Architecture:
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- Batch Normalization
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- Convolution
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- Dropout
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- ReLU6
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- Residual Connection
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File Size: 19417552
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Tasks:
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- Image Classification
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Training Time: ''
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ID: rexnet_100
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LR: 0.5
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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Label Smoothing: 0.1
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/rexnet.py#L212
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Config: ''
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In Collection: RexNet
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- Name: rexnet_130
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Metadata:
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FLOPs: 848364461
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Epochs: 400
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Batch Size: 512
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Training Data:
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- ImageNet
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Training Techniques:
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- Label Smoothing
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- Linear Warmup With Cosine Annealing
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 4x NVIDIA V100 GPUs
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Architecture:
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- Batch Normalization
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- Convolution
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- Dropout
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- ReLU6
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- Residual Connection
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File Size: 30508197
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Tasks:
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- Image Classification
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Training Time: ''
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ID: rexnet_130
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LR: 0.5
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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Label Smoothing: 0.1
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/rexnet.py#L218
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Config: ''
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In Collection: RexNet
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- Name: rexnet_150
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Metadata:
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FLOPs: 1122374469
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Epochs: 400
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Batch Size: 512
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Training Data:
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- ImageNet
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Training Techniques:
|
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- Label Smoothing
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- Linear Warmup With Cosine Annealing
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 4x NVIDIA V100 GPUs
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Architecture:
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- Batch Normalization
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- Convolution
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- Dropout
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- ReLU6
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- Residual Connection
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File Size: 39227315
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Tasks:
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- Image Classification
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Training Time: ''
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ID: rexnet_150
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LR: 0.5
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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Label Smoothing: 0.1
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/rexnet.py#L224
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Config: ''
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In Collection: RexNet
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- Name: rexnet_200
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Metadata:
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FLOPs: 1960224938
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Epochs: 400
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Batch Size: 512
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Training Data:
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- ImageNet
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Training Techniques:
|
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- Label Smoothing
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- Linear Warmup With Cosine Annealing
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- Nesterov Accelerated Gradient
|
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- Weight Decay
|
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Training Resources: 4x NVIDIA V100 GPUs
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Architecture:
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- Batch Normalization
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|
- Convolution
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- Dropout
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- ReLU6
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- Residual Connection
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File Size: 65862221
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Tasks:
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- Image Classification
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Training Time: ''
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ID: rexnet_200
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LR: 0.5
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Dropout: 0.2
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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Label Smoothing: 0.1
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/rexnet.py#L230
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Config: ''
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In Collection: RexNet
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Collections:
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- Name: RexNet
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Paper:
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title: 'ReXNet: Diminishing Representational Bottleneck on Convolutional Neural
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Network'
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url: https://paperswithcode.com//paper/rexnet-diminishing-representational
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type: model-index
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Type: model-index
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-->
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