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May 20, 2020 - Python
classification
Here are 4,523 public repositories matching this topic...
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Jun 23, 2020 - Python
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
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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?
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Jun 26, 2020 - Python
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!
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Jun 26, 2020 - R
Hi NVIDIA Team,
To make this project successful, I would like to suggest to add few things. I would love to assist on this.
- Complete technical installation steps to add more values
- Details of all pre-requisites, to build this project successfully.
- Overall technical background, design and architecture. Just like we provide a technical guide and documentation for other software engine
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我发现一些有疑问的地方
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Update diagrams
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
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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)))