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Title: GitHub - newcodevelop/gradient-checkpointing: Make huge neural nets fit in memory

Open Graph Title: GitHub - newcodevelop/gradient-checkpointing: Make huge neural nets fit in memory

X Title: GitHub - newcodevelop/gradient-checkpointing: Make huge neural nets fit in memory

Description: Make huge neural nets fit in memory. Contribute to newcodevelop/gradient-checkpointing development by creating an account on GitHub.

Open Graph Description: Make huge neural nets fit in memory. Contribute to newcodevelop/gradient-checkpointing development by creating an account on GitHub.

X Description: Make huge neural nets fit in memory. Contribute to newcodevelop/gradient-checkpointing development by creating an account on GitHub.

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https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#saving-memory-using-gradient-checkpointing
Training Deep Nets with Sublinear Memory Cost, by Chen et al. (2016)https://arxiv.org/pdf/1604.06174.pdf
Tensorflow graph editorhttps://www.tensorflow.org/versions/r1.0/api_guides/python/contrib.graph_editor
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing/blob/master/img/sqrtn.png
ResNet modelhttps://github.com/tensorflow/models/blob/master/official/resnet/cifar10_main.py
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#how-it-works
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blog posthttps://medium.com/@yaroslavvb/fitting-larger-networks-into-memory-583e3c758ff9
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#setup-requirements
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#usage
tf.gradientshttps://www.tensorflow.org/api_docs/python/tf/gradients
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#overwriting-tfgradients
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#tests
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing/blob/master/img/resnet_test.png
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#limitations
https://patch-diff.githubusercontent.com/newcodevelop/gradient-checkpointing#references
Training Deep Nets with Sublinear Memory Cost, by Chen et al. (2016)https://arxiv.org/pdf/1604.06174.pdf
Memory-Efficient Backpropagation Through Time, by Gruslys et al. (2016)https://arxiv.org/abs/1606.03401v1
Exact Alpha-Beta Computation in Logarithmic Space with Application to MAP Word Graph Construction, by Zweig et al. (2000)https://www.microsoft.com/en-us/research/publication/exact-alpha-beta-computation-in-logarithmic-space-with-application-to-map-word-graph-construction/
Debugging Backwards in Time, by Bil Lewis (2003)https://arxiv.org/abs/cs/0310016
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, by Griewank and Walther (2008)https://epubs.siam.org/doi/book/10.1137/1.9780898717761
tensorflow/tensorflow#4359 (comment)https://github.com/tensorflow/tensorflow/issues/4359#issuecomment-269241038
https://github.com/yaroslavvb/stuff/blob/master/simple_rewiring.ipynbhttps://github.com/yaroslavvb/stuff/blob/master/simple_rewiring.ipynb
https://medium.com/@yaroslavvb/testing-memory-saving-on-v100-8aa716bbdf00https://medium.com/@yaroslavvb/testing-memory-saving-on-v100-8aa716bbdf00
https://github.com/yaroslavvb/chain_constant_memory/blob/master/mem_util_test.pyhttps://github.com/yaroslavvb/chain_constant_memory/blob/master/mem_util_test.py
https://github.com/yaroslavvb/chain_constant_memory/https://github.com/yaroslavvb/chain_constant_memory/
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