🚀 Feature request – 🚀 功能请求区块链毕设代写

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🚀 Feature request

It seems GPT-2 and BartDecoder has a different style of past_key_values.

In GPT-2, past_key_values is explained as below:
(the explanation is from https://huggingface.co/transformers/model_doc/gpt2.html#gpt2model)

(parameters) past_key_values (List[torch.FloatTensor] of length config.n_layers) – Contains precomputed hidden-states (key and values in the atten 
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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!)
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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

Deprecation of old trainer APIs (e.g., checkpoint_callback) and of EvaluationModel in favor of new APIs (e.g., callbacks) and BoringModel. Take PR #4820 as an example.
This issue should be tackled one file at the time to allow better review process (as discussed with @Borda).
NOTE (1): Every test should use default

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Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________  self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>      def test_make_tensor(self):  # type: () -> None      
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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 8,522


🚀 功能请求

似乎GPT-2和bart解码器对过去的键值有不同的风格。

在GPT-2中,过去的u键u值解释如下:
(解释来自https://huggingface.co/transformers/modelŠdoc/gpt2.htmlŠgpt2model)

(parameters) past_key_values (List[torch.FloatTensor] of length config.n_layers) – Contains precomputed hidden-states (key and values in the atten 
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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. 通过留下评论来建议新功能。
  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

反对旧的trainer API(如checkpointu callback)和EvaluationModel,支持新的API(如callbacks)和BoringModel。以PR#4820为例。
这个问题应该一次解决一个文件,以允许更好的审查过程(与@Borda讨论)。
注意(1):每个测试都应该使用默认值

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错误报告

这些测试在s390x上运行。s390x是big-endian体系结构。

帮助程序的故障日志_测试.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________  self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>      def test_make_tensor(self):  # type: () -> None      
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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

为什么需要:除AGPPruner only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。

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Todo:定义参数`

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]) ...

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。

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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 8,522

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