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doombeaker
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Apr 29, 2022
docs/source/flowvision.models.rst
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| ============== | ||
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| The models subpackage contains definitions for the following model | ||
| The models' subpackage contains definitions for the following model |
doombeaker
reviewed
Apr 29, 2022
| ## Usage | ||
| ### Create a model | ||
| In flowvision we support two ways to create a model. | ||
| Flowvision supports two ways to create a model: |
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| Flowvision supports two ways to create a model: | |
| FlowVision supports two ways to create a model: |
doombeaker
reviewed
Apr 29, 2022
| ``` | ||
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| ### Search for supported model by Wildcard | ||
| ### Search for the supported model by Wildcard |
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这里的大小写是遵循什么规范呢,为什么 "Wildcard“ 是单独大写的。
doombeaker
reviewed
Apr 29, 2022
flowvision/data/mixup.py
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| def rand_bbox(img_shape, lam, margin=0.0, count=None): | ||
| """ Standard CutMix bounding-box | ||
| Generates a random square bbox based on lambda value. This impl includes | ||
| generates a random square bbox based on lambda value. This impl includes |
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| generates a random square bbox based on lambda value. This impl includes | |
| generates a random square bbox based on lambda value. This implementation includes |
impl 是什么意思?
rentainhe
reviewed
May 4, 2022
| def auto_augment_transform(config_str, hparams): | ||
| """ | ||
| Create a AutoAugment transform | ||
| Creates a AutoAugment transform |
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这边需要Creates吗2333,我怎么感觉貌似Create就行了
flowvision/data/mixup.py
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| def mixup_target(target, num_classes, lam=1.0, smoothing=0.0, device="cuda"): | ||
| """ | ||
| Mixup the targets with label-smoothing | ||
| Mixes up the targets with label-smoothing |
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这边用MixUp就行了,mixup整体是作为一个名词,表示一个数据增强操作
flowvision/data/mixup.py
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| def rand_bbox(img_shape, lam, margin=0.0, count=None): | ||
| """ Standard CutMix bounding-box | ||
| Generates a random square bbox based on lambda value. This impl includes | ||
| generates a random square bbox based on lambda value. This implementation includes |
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这个开头需要大写,和上面那个不算同一行,Generates
flowvision/scheduler/multistep_lr.py
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| class MultiStepLRScheduler(Scheduler): | ||
| """MultiStep LRScheduler | ||
| Decays the learning rate of each parameter group by decay_rate once the | ||
| decays the learning rate of each parameter group by decay_rate once the |
flowvision/scheduler/step_lr.py
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| class StepLRScheduler(Scheduler): | ||
| """ Step LRScheduler | ||
| Decays the learning rate of each parameter group by | ||
| decays the learning rate of each parameter group by |
| format: Optional[str] = None, | ||
| ) -> None: | ||
| """Save a given Tensor into an image file. | ||
| """Saves a given Tensor into an image file. |
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您好,这个问题我想请教一下,如果按照英文祈使句的语法规则,句首动词应该用动词原型,但是我看FlowVision仓库里的文本,有很大一部分都用的第三人称,而且Torchvision里也有使用第三人称的情况,因此我为了文章前后统一,才把这些改为了第三人称。由于我不太懂编程,所以想请教一下编程当中对句首动词人称的选择是根据一般的语法规则呢?还是有独特的规定?
Contributor
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其实都OK吧,只要你前后统一就行了~,话说这个PR可以继续推进一下嘛,争取这两天合并进去
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