yaroslavvb / memory_utilLinks
TensorFlow util for building memory usage timeline from LOG_MEMORY messages
☆65Updated 7 years ago
Alternatives and similar repositories for memory_util
Users that are interested in memory_util are comparing it to the libraries listed below
Sorting:
- Efficient layer normalization GPU kernel for Tensorflow☆111Updated 8 years ago
- ☆23Updated 9 years ago
- A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.☆38Updated 6 years ago
- Example of backprop which uses constant memory☆43Updated 6 years ago
- The Operator Vectorization Library, or OVL, is a python productivity library for defining high performance custom operators for the Tenso…☆68Updated 8 years ago
- easy embeddable Torch7 networks☆35Updated 8 years ago
- A pytorch implementation of "Self-Normalizing Neural Networks" by Klambauer et al. (still beta)☆59Updated 7 years ago
- Reference caffe implementation of LSUV initialization☆113Updated 7 years ago
- Source code for ``Neural Networks with Few Multiplications'' published at ICLR 2016☆81Updated 9 years ago
- ☆92Updated 8 years ago
- Torch implementation reproducing MNIST experiments from DeepMind's DNI paper.☆43Updated 8 years ago
- TensorFlow kernels for probing memory☆15Updated 8 years ago
- An attempt to implement the recurrent attention model (RAM) from "Recurrent Models of Visual Attention" (Mnih+ 2014)☆43Updated 4 years ago
- Code for Attentive Recurrent Comparators☆57Updated 8 years ago
- ☆69Updated 6 years ago
- DeepArchitect: Automatically Designing and Training Deep Architectures☆147Updated 5 years ago
- Weight initialization schemes for PyTorch nn.Modules☆70Updated 8 years ago
- auto-tuning momentum SGD optimizer☆288Updated 6 years ago
- Distributed Learning by Pair-Wise Averaging☆52Updated 7 years ago
- DNI(Decoupled Neural Interfaces using Synthetic Gradients) implementation with Torch☆29Updated 8 years ago
- Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)☆125Updated 7 years ago
- ☆69Updated 8 years ago
- Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets☆28Updated 9 years ago
- Training deep neural networks with low precision multiplications☆63Updated 9 years ago
- Lasagne code for weight normalization☆88Updated 9 years ago
- ☆76Updated 8 years ago
- Structured Receptive Fields in Convolutional Neural Networks☆47Updated 7 years ago
- Code and models from the paper "Layer Normalization"☆247Updated 8 years ago
- ☆57Updated 7 years ago
- Tensorflow implementation of SGD with Coupled Adaptive Batch Size (CABS)☆43Updated 8 years ago