fast-deep-rnn
This is the Course Project for the DeepLearning University Course.
Install
Library can be installed from the PyPI via
pip install fast_deep_rnn
Structure
core module contains the original core of the framework with Tensor
class implementation and the set of differentiable operations, organized
in Modules.
core_v2 module contains the alternative proposed implementation,
resulting in much faster gradient computing in RNN-s.
Notebook nbs/02_minimal_training.ipynb contains the simplest example
of model, having exponential growth in original gradient computing, and
benchmarking function to measure this growth. git tags
baseline_benchmark_results and solution_benchmark_results contain
corresponding benchmark results inside the notebook.
Notebook nbs/01_lstm_training.ipynb contains training of LSTM on
number sorting task, which became possible only after the implemented
optimization.
1 maintainer
Metadata
1 maintainer
Release files for fast-deep-rnn 0.0.2
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Total release size: 41.5 kB
Release files / fast-deep-rnn-0.0.2.tar.gz
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