r"""ResNeXt-152 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" `_ Args: pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool): If True, displays a progress bar of the download
(pretrained=False, progress=True, **kwargs)
| 353 | |
| 354 | |
| 355 | def resnext152_32x8d(pretrained=False, progress=True, **kwargs): |
| 356 | r"""ResNeXt-152 32x8d model from |
| 357 | `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ |
| 358 | Args: |
| 359 | pretrained (bool): If True, returns a model pre-trained on ImageNet |
| 360 | progress (bool): If True, displays a progress bar of the download to stderr |
| 361 | """ |
| 362 | kwargs['groups'] = 32 |
| 363 | kwargs['width_per_group'] = 8 |
| 364 | return _resnet('resnext152_32x8d', Bottleneck, [3, 8, 36, 3], |
| 365 | pretrained, progress, **kwargs) |
| 366 | |
| 367 | |
| 368 | def resnext152_64x4d(pretrained=False, progress=True, **kwargs): |