deep-learning-v2-pytorch | Projects and exercises for the latest Deep Learning ND | Machine Learning library

by udacity Jupyter Notebook Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | deep-learning-v2-pytorch Summary

deep-learning-v2-pytorch is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. deep-learning-v2-pytorch has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

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deep-learning-v2-pytorch has a medium active ecosystem.

It has 4961 star(s) with 5265 fork(s). There are 174 watchers for this library.

It had no major release in the last 6 months.

There are 9 open issues and 145 have been closed. On average issues are closed in 199 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of deep-learning-v2-pytorch is current.

Quality

deep-learning-v2-pytorch has 0 bugs and 0 code smells.

Security

deep-learning-v2-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

deep-learning-v2-pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

deep-learning-v2-pytorch is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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deep-learning-v2-pytorch releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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deep-learning-v2-pytorch Key Features

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deep-learning-v2-pytorch Examples and Code Snippets

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Community Discussions

Trending Discussions on deep-learning-v2-pytorch

how to find out the method definition of torch.nn.Module.parameters()

Should I transpose features or weights in Neural network?

Runtime error while running PyTorch model on local machine

QUESTION

how to find out the method definition of torch.nn.Module.parameters()

Asked 2020-Oct-31 at 00:53

I am following this notebook:

One of the method:

...

ANSWER

Answered 2020-Oct-25 at 07:27

so I was trying to find out the parameters() method as the data attribute comes from paramerters() method. Surprisingly, I cannot find where it comes from after reading the source code of nn module in PyTorch.

You can see the module definition under torch/nn/modules/module.py here at line 178.
You can then easily spot the parameters() method here.

How do you guys figure out where to see the definition of methods you saw from PyTorch?

The easiest way that I myself always use, is to use VSCode's Go to Definition or its Peek -> Peek definition feature. I believe Pycharm has a similar functionality as well.

Source https://stackoverflow.com/questions/64519933

QUESTION

Should I transpose features or weights in Neural network?

Asked 2020-Jul-30 at 11:27

I am learning Neural network.

Here is the complete piece of code: https://github.com/udacity/deep-learning-v2-pytorch/blob/master/intro-to-pytorch/Part%201%20-%20Tensors%20in%20PyTorch%20(Exercises).ipynb

When I transpose features, I get the following output:

...

ANSWER

Answered 2020-Jul-21 at 04:16

This line is taking an outer product between the two vectors.

Source https://stackoverflow.com/questions/63006388

QUESTION

Runtime error while running PyTorch model on local machine

Asked 2020-Jun-16 at 07:59

I'm running this notebook locally

https://github.com/udacity/deep-learning-v2-pytorch/blob/master/sentiment-rnn/Sentiment_RNN_Solution.ipynb everything was working just until I started training the model

...

ANSWER

Answered 2020-Jun-16 at 07:59

You are trying to embed the inputs, which are given as ints (torch.int). Only integers (torch.long) can be embedded, since they need to be indices, which cannot be float.

inputs need to be converted to torch.long:

Source https://stackoverflow.com/questions/62400718

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install deep-learning-v2-pytorch

Download the latest version of miniconda that matches your system. | | Linux | Mac | Windows | |--------|-------|-----|---------| | 64-bit | 64-bit (bash installer) | 64-bit (bash installer) | 64-bit (exe installer) | 32-bit | 32-bit (bash installer) | | 32-bit (exe installer).
Linux: https://conda.io/projects/conda/en/latest/user-guide/install/linux.html
Mac: https://conda.io/projects/conda/en/latest/user-guide/install/macos.html
Windows: https://conda.io/projects/conda/en/latest/user-guide/install/windows.html

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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