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398 lines
10 KiB
398 lines
10 KiB
3 years ago
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# RegNetX
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3 years ago
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**RegNetX** is a convolutional network design space with simple, regular models with parameters: depth $d$, initial width $w\_{0} > 0$, and slope $w\_{a} > 0$, and generates a different block width $u\_{j}$ for each block $j < d$. The key restriction for the RegNet types of model is that there is a linear parameterisation of block widths (the design space only contains models with this linear structure):
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$$ u\_{j} = w\_{0} + w\_{a}\cdot{j} $$
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For **RegNetX** we have additional restrictions: we set $b = 1$ (the bottleneck ratio), $12 \leq d \leq 28$, and $w\_{m} \geq 2$ (the width multiplier).
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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{radosavovic2020designing,
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title={Designing Network Design Spaces},
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author={Ilija Radosavovic and Raj Prateek Kosaraju and Ross Girshick and Kaiming He and Piotr Dollár},
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year={2020},
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eprint={2003.13678},
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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: regnetx_040
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Metadata:
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FLOPs: 5095167744
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Epochs: 100
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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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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 88844824
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Tasks:
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- Image Classification
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ID: regnetx_040
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L373
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In Collection: RegNetX
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- Name: regnetx_004
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Metadata:
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FLOPs: 510619136
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Epochs: 100
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Batch Size: 1024
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 20841309
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Tasks:
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- Image Classification
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ID: regnetx_004
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L343
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In Collection: RegNetX
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- Name: regnetx_006
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Metadata:
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FLOPs: 771659136
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Epochs: 100
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Batch Size: 1024
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 24965172
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Tasks:
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- Image Classification
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ID: regnetx_006
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L349
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In Collection: RegNetX
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- Name: regnetx_002
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Metadata:
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FLOPs: 255276032
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Epochs: 100
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Batch Size: 1024
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 10862199
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Tasks:
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- Image Classification
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ID: regnetx_002
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L337
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In Collection: RegNetX
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- Name: regnetx_008
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Metadata:
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FLOPs: 1027038208
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Epochs: 100
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Batch Size: 1024
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 29235944
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Tasks:
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- Image Classification
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ID: regnetx_008
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L355
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In Collection: RegNetX
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- Name: regnetx_016
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Metadata:
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FLOPs: 2059337856
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Epochs: 100
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Batch Size: 1024
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Training Data:
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- ImageNet
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 36988158
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Tasks:
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- Image Classification
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ID: regnetx_016
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L361
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In Collection: RegNetX
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- Name: regnetx_032
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Metadata:
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FLOPs: 4082555904
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Epochs: 100
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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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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 61509573
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Tasks:
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- Image Classification
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ID: regnetx_032
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L367
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In Collection: RegNetX
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- Name: regnetx_064
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Metadata:
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FLOPs: 8303405824
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Epochs: 100
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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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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 105184854
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Tasks:
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- Image Classification
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ID: regnetx_064
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L379
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In Collection: RegNetX
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- Name: regnetx_080
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Metadata:
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FLOPs: 10276726784
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Epochs: 100
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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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- SGD with Momentum
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- Weight Decay
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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|
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- 1x1 Convolution
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|
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- Batch Normalization
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||
|
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- Convolution
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- Dense Connections
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- Global Average Pooling
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- Grouped Convolution
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- ReLU
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File Size: 158720042
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Tasks:
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- Image Classification
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ID: regnetx_080
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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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||
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|
Weight Decay: 5.0e-05
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||
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Interpolation: bicubic
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|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L385
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In Collection: RegNetX
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|
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- Name: regnetx_120
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|
|
Metadata:
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|
|
FLOPs: 15536378368
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Epochs: 100
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||
|
|
Batch Size: 512
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||
|
|
Training Data:
|
||
|
|
- ImageNet
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|
|
Training Techniques:
|
||
|
|
- SGD with Momentum
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||
|
|
- Weight Decay
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||
|
|
Training Resources: 8x NVIDIA V100 GPUs
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|
|
Architecture:
|
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|
|
- 1x1 Convolution
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||
|
|
- Batch Normalization
|
||
|
|
- Convolution
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||
|
|
- Dense Connections
|
||
|
|
- Global Average Pooling
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||
|
|
- Grouped Convolution
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||
|
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- ReLU
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||
|
|
File Size: 184866342
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||
|
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Tasks:
|
||
|
|
- Image Classification
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||
|
|
ID: regnetx_120
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||
|
|
Crop Pct: '0.875'
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||
|
|
Momentum: 0.9
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||
|
|
Image Size: '224'
|
||
|
|
Weight Decay: 5.0e-05
|
||
|
|
Interpolation: bicubic
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||
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L391
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|
|
In Collection: RegNetX
|
||
|
|
- Name: regnetx_160
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||
|
|
Metadata:
|
||
|
|
FLOPs: 20491740672
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||
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Epochs: 100
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||
|
|
Batch Size: 512
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||
|
|
Training Data:
|
||
|
|
- ImageNet
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|
|
Training Techniques:
|
||
|
|
- SGD with Momentum
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||
|
|
- Weight Decay
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||
|
|
Training Resources: 8x NVIDIA V100 GPUs
|
||
|
|
Architecture:
|
||
|
|
- 1x1 Convolution
|
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|
|
- Batch Normalization
|
||
|
|
- Convolution
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|
|
- Dense Connections
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|
- Global Average Pooling
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- Grouped Convolution
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||
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- ReLU
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||
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|
File Size: 217623862
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||
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|
Tasks:
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||
|
|
- Image Classification
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||
|
|
ID: regnetx_160
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||
|
|
Crop Pct: '0.875'
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||
|
|
Momentum: 0.9
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||
|
|
Image Size: '224'
|
||
|
|
Weight Decay: 5.0e-05
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||
|
|
Interpolation: bicubic
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||
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L397
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|
|
In Collection: RegNetX
|
||
|
|
- Name: regnetx_320
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||
|
|
Metadata:
|
||
|
|
FLOPs: 40798958592
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||
|
|
Epochs: 100
|
||
|
|
Batch Size: 256
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||
|
|
Training Data:
|
||
|
|
- ImageNet
|
||
|
|
Training Techniques:
|
||
|
|
- SGD with Momentum
|
||
|
|
- Weight Decay
|
||
|
|
Training Resources: 8x NVIDIA V100 GPUs
|
||
|
|
Architecture:
|
||
|
|
- 1x1 Convolution
|
||
|
|
- Batch Normalization
|
||
|
|
- Convolution
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||
|
|
- Dense Connections
|
||
|
|
- Global Average Pooling
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||
|
|
- Grouped Convolution
|
||
|
|
- ReLU
|
||
|
|
File Size: 431962133
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||
|
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Tasks:
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- Image Classification
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ID: regnetx_320
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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: 5.0e-05
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/regnet.py#L403
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In Collection: RegNetX
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Collections:
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||
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- Name: RegNetX
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Paper:
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title: Designing Network Design Spaces
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||
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3 years ago
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url: https://paperswithcode.com//paper/designing-network-design-spaces
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3 years ago
|
type: model-index
|
||
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Type: model-index
|
||
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|
-->
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