基于区块链的毕业设计🚀 Feature request – 🚀 功能请求

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🚀 Feature request

In pipelines tests and documentation they are recurringly named nlp, the goal is to rename them to something more appropriate.

Motivation

nlp = pipeline(task='conversational', model='XXX')

This is a bit pre

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some recordings have low volume so the output can be sometimes really quiet. how about we add a volume bar so we can make the output louder/quieter?

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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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🚀 Feature

check if PR contains unused code or if the particular change dead code in not introduced somewhere else in the codebase

Motivation

remove all unused code, keep the codebase healthy

Alternatives

one toll I found – https://github.com/jendrikseipp/vulture
but let’s check some alternatives

Additional context

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Add a new API for converting a model to external data. Today the conversion happens in 2 steps
external_data_helper.convert_model_to_external_data(<model>, <all_tensors_to_one_file>, <size_threshold>) save_model(model, output_path)
We want to add another api which combines the 2 steps
`
save_model_to_external_data(, <output_

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

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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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Current pytorch implementation ignores the argument split_f in the function train_batch_ch13 as shown below.

def train_batch_ch13(net, X, y, loss, trainer, devices):     if isinstance(X, list):         # Required for BERT Fine-tuning (to be covered later)         X = [x.to(devices[0]) for x in X]     else:         X = X.to(devices[0]) ...

Todo: Define the argument `

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Is it possible to run this on a (recent) Mac, which does not support CUDA? I would have guessed setting –GPU 0 would not attempt to call CUDA, but it fails.

File "/Users/../Desktop/bopbtl/venv/lib/python3.7/site-packages/torch/cuda/__init__.py", line 61, in _check_driver     raise AssertionError("Torch not compiled with CUDA enabled") AssertionError: Torch not compiled with CUDA enable 
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Python 8,700


🚀 功能请求

在管道测试和文档中,它们被反复命名为nlp,目的是将它们重命名为更合适的名称。

动机

nlp = pipeline(task='conversational', model='XXX')

这有点早

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有些录音的音量很小,所以有时输出会非常安静。不如我们加一个音量条,这样我们可以使输出声音更大/更安静?

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我们将此问题公开,以收集用户的功能请求并倾听您的声音。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. 投票支持具有👍 或者反对👎. (请记住,开发人员很忙,无法响应所有功能请求,所以请选择您最喜欢的功能!)告诉我们
  3. Tell us that
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更改张量数据至张量分离()由于
pytorch/pytorch#6990(评论)
张量分离()比张量数据.

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🚀 功能

检查PR是否包含未使用的代码,或者是否在代码库的其他地方没有引入特定的更改死代码

动机

删除所有未使用的代码,保持代码库健康

备选方案

我发现的一个错误-https://github.com/jendrikseipp/vulture
但是,让我们检查一些替代方法,添加一个新的API来将模型转换为外部数据。如今,转换分两步进行
外部数据_helper.convert model to external数据(&lt;model&gt;,&lt;allu tensorsu to u oneu file&gt;,&lt;sizeu threshold&gt;)saveu model(model,outputu path)
我们想添加另一个api,它结合了两个步骤
`
saveu modelu to u externalu data(,&lt;输出

附加上下文

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更多详细信息,请访问:allenai/allennlp#2264(注释)

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您希望添加什么:作为标题

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为什么需要:除AGPPruner仅支持级别L1、L2之外的所有修剪计划。虽然有FPGM,APoZ,meansactivation和Taylor,但如果我们可以选择任何修剪计划的修剪器就更好了。

**如果没有此功能,当前nni如何忽略函数列批处理ch13中的参数split,如下所示。

Todo:定义参数`

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是否可以在(最近的)不支持CUDA的Mac上运行此操作?我猜设置——GPU0不会尝试调用CUDA,但它失败了。

def train_batch_ch13(net, X, y, loss, trainer, devices):     if isinstance(X, list):         # Required for BERT Fine-tuning (to be covered later)         X = [x.to(devices[0]) for x in X]     else:         X = X.to(devices[0]) ...

Todo: Define the argument `

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Is it possible to run this on a (recent) Mac, which does not support CUDA? I would have guessed setting –GPU 0 would not attempt to call CUDA, but it fails.

File "/Users/../Desktop/bopbtl/venv/lib/python3.7/site-packages/torch/cuda/__init__.py", line 61, in _check_driver     raise AssertionError("Torch not compiled with CUDA enabled") AssertionError: Torch not compiled with CUDA enable 
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Python 8,700

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