🚀 Feature request – 🚀 功能请求区块链毕设代写

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🚀 Feature request

modeling_longformer.py has the classes LongformerForSequenceClassification, LongformerForMultipleChoice and LongformerForTokenClassification which are not present in modeling_tf_longformer.py at the moment.
Those classes should be equally added to modeling_tf_longformer.py.

Motivation

The pretrained weights for TFLongformer are available so that these

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We keep this issue open to collect feature requests from users and hear your voice. Our monthly release plan is also available here.

You can either:

  1. Suggest a new feature by leaving a comment.
  2. Vote for a feature request with 👍 or be against with 👎. (Remember that developers are busy and cannot respond to all feature requests, so vote for your most favorable one!)
  3. Tell us that
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Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

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more details at: allenai/allennlp#2264 (comment)

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Spawned off https://github.com/onnx/onnx/pull/2772/files/7ab93cc1b635eada330dae7424d4ff7e8c22c295#r440422245, opening issue to track resolution

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🚀 Feature

Create the metric MulticlassAUROC to allow for the AUROC metric to be used in multi-class problem settings. Or,
Expand the AUROC metric to support multi-class data, which would also directly solve this AUROC bug that instead gives a random value when used in multi-class problems: https://github.com/PyTorchLightning/

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What would you like to be added: As title

Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.

**Without this feature, how does current nni

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To begin I tried logging in with GitHub and also creating an account on the pyro forums, but neither of those is working.

Problem

I need to fit a batch of four independent Gaussian Processes and I don’t want to have to use for loops for fitting each one. The current GP’s are able to broadcast properly to my outputs, but I can’t batch them so that the inputs are independent.

My input d

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Python 7,487


🚀 功能请求

建模_longformer.py具有建模中不存在的类LongformerForSequenceClassification、LongFormerMultipleChoice和LongformerForTokenClassification_longformer.py目前。
这些类应该同样添加到建模中_longformer.py.

动机

TFLongformer的预训练权重是可用的,因此,

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我们将此问题保持开放状态,以收集用户的功能请求并听到您的声音。我们的每月发布计划也在这里提供。

您可以:

  1. 通过留下评论建议新功能。
  2. 投票支持功能请求👍 或者反对👎. (请记住,开发人员很忙,无法响应所有功能请求,所以请投票给您最喜欢的一个!)告诉我们
  3. Tell us that
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更改张量数据到张量分离()由于
pytorch/pytorch#6990(注释)
张量分离()比张量数据.

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更多详情请访问:allenai/allennlp#2264(评论)

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衍生出来https://github.com/onnx/onnx/pull/2772/files/7ab93cc1b635eada330dae7424d4ff7e8c22c295r440422245,打开问题以跟踪解决方案

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🚀 功能

创建度量多类AUROC,以允许AUROC度量用于多类问题设置。或者,
扩展AUROC度量以支持多类数据,这也可以直接解决AUROC错误,当用于多类问题时,它会给出一个随机值:https://torchlinghub

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您希望添加什么:作为标题

为什么需要这样做:除了AGPPruner only支持级别L1、L2之外的所有修剪计划。虽然有FPGM,APoZ,MeanActivation和Taylor,但是如果我们可以选择任何一个具有任何修剪时间表的修剪器,那就更好了。

**如果没有这个功能,当前的nni如何开始我尝试使用GitHub登录,并在pyro论坛上创建一个帐户,但这两个都不起作用。

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我需要拟合一批四个独立的高斯过程,我不想使用for循环来拟合每个过程。目前的GP能够正确地广播到我的输出,但我不能批处理它们,以便输入是独立的。

问题

我的输入d

My input d

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Python 7,487

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