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134 lines
3.4 KiB
134 lines
3.4 KiB
4 years ago
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# Summary
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**MixNet** is a type of convolutional neural network discovered via AutoML that utilises [MixConvs](https://paperswithcode.com/method/mixconv) instead of regular [depthwise convolutions](https://paperswithcode.com/method/depthwise-convolution).
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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{tan2019mixconv,
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title={MixConv: Mixed Depthwise Convolutional Kernels},
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author={Mingxing Tan and Quoc V. Le},
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year={2019},
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eprint={1907.09595},
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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: mixnet_xl
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Metadata:
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FLOPs: 1195880424
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Training Data:
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- ImageNet
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Training Techniques:
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- MNAS
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Architecture:
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- Batch Normalization
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- Grouped Convolution
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- MixConv
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 48001170
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Tasks:
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- Image Classification
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ID: mixnet_xl
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1678
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In Collection: MixNet
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- Name: mixnet_m
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Metadata:
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FLOPs: 454543374
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Training Data:
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- ImageNet
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Training Techniques:
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- MNAS
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Architecture:
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- Batch Normalization
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- Grouped Convolution
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- MixConv
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 20298347
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Tasks:
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- Image Classification
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ID: mixnet_m
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1660
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In Collection: MixNet
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- Name: mixnet_s
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Metadata:
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FLOPs: 321264910
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Training Data:
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- ImageNet
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Training Techniques:
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- MNAS
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Architecture:
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- Batch Normalization
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- Grouped Convolution
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- MixConv
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 16727982
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Tasks:
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- Image Classification
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ID: mixnet_s
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1651
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In Collection: MixNet
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- Name: mixnet_l
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Metadata:
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FLOPs: 738671316
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Training Data:
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- ImageNet
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Training Techniques:
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- MNAS
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Architecture:
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- Batch Normalization
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- Dense Connections
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- Dropout
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- Global Average Pooling
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- Grouped Convolution
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- MixConv
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 29608232
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Tasks:
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- Image Classification
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ID: mixnet_l
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Crop Pct: '0.875'
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Image Size: '224'
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Interpolation: bicubic
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1669
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In Collection: MixNet
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Collections:
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- Name: MixNet
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Paper:
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title: 'MixConv: Mixed Depthwise Convolutional Kernels'
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url: https://papperswithcode.com//paper/mixnet-mixed-depthwise-convolutional-kernels
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type: model-index
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Type: model-index
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-->
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