Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))

I tried some RNN regression learning based on the code in the "PyTorch-Tutorial/tutorial-contents/403_RNN_regressor.py" file, which did not work for me at all.

According to an accepted answer on stack-overflow (https://stackoverflow.com/questions/52857213/recurrent-network-rnn-wont-learn-a-very-simple-function-plots-shown-in-the-q?noredirect=1#comment92916825_52857213), it turns out that the li

Description
In some rare cases, for example, when you need to finetune a large model on a small dataset the majoring part of training loop is waiting for saving model checkpoints to a hard drive.

Proposal
Would be logically to add a CheckpointCallback with parameter save_n_best=0 to a configuration and do not store best checkpoints and instead use the latest state of the model.

In 'pointnet2/scannet/preprocessing/collect_scannet_scenes.py' line #17, we refer to 'scannet_all.txt' file. It would be helpful if you guide where to get or how to generate this file?

The procedure for downloading the "en_vectors_web_lg" in spacy. by downloading and unzipping the file, and shifting it to the appropriate directory, as illustrated here is l

When following the manual install guide i had to install the following additional dependencies manually:

sudo apt-get install pulseaudio swig libpulse-dev libasound2-dev
sudo pip3 install pocketsphinx spidev

After, it all works great on Raspberry Pi Zero W!

Hi NVIDIA Team,

To make this project successful, I would like to suggest to add few things. I would love to assist on this.

1. Complete technical installation steps to add more values
2. Details of all pre-requisites, to build this project successfully.
3. Overall technical background, design and architecture. Just like we provide a technical guide and documentation for other software engine

1. 31页，第一行
   
   应改成
   

2. 35 页， 正定矩阵的定义 （公式 2-15）
   标准正定矩阵的定义，应该没有 “对称矩阵” 这一条件吧？ 只是您在本书大多讨论的是“对称”正定矩阵，所以加上了 “对称” 这一条件？

3. 38页， 奇异值分解定义（公式 2-16）
   ![default](https://

In experiments.rst, in the first diagram, I'm inferring that ovals are static resources and parallelograms are processes, and that dashed lines means optional. But if that's true, then I'm not sure what the meaning of purple vs. blue is, the scenes should be ovals and solid lines. It might be simpler and easier to parse if everything was a blue oval, although the dashed line makes sense. In the