Text-Classification-PyTorch | Implementation of papers for text classification | Natural Language Processing library
kandi X-RAY | Text-Classification-PyTorch Summary
kandi X-RAY | Text-Classification-PyTorch Summary
Implementation of papers for text classification task on SST-1/SST-2
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Top functions reviewed by kandi - BETA
- Creates input files
- Load embeddings
- Update the sum
- Train the model
- Train model
- Validate the loss function
- Save checkpoint
- Clip gradients from optimizer
- Decrement learning rate
- Calculate accuracy
- Test the model
- Evaluate the model
Text-Classification-PyTorch Key Features
Text-Classification-PyTorch Examples and Code Snippets
Community Discussions
Trending Discussions on Text-Classification-PyTorch
QUESTION
I am looking at an implementation of RCNN for text classification using PyTorch. Full Code. There are two points where the dimensions of tensors are permuted using the permute
function. The first is after the LSTM layer and before tanh. The second is after a linear layer and before a max pooling layer.
Could you please explain why the permutation is necessary or useful?
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...ANSWER
Answered 2021-Jan-05 at 05:11What permute
function does is rearranges the original tensor according to the desired ordering, note permute
is different from reshape
function, because when apply permute
, the elements in tensor follow the index you provide where in reshape
it's not.
Example code:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install Text-Classification-PyTorch
You can use Text-Classification-PyTorch like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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