Jonathan Greer j-greer
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| ####### load required packages and ste seed ######## | |
| library(mc2d) #for PERT distribution | |
| library(ggplot2) #for plotting | |
| set.seed(1501) | |
| DDoS <- 10 #Number of DDoS attacks per year | |
| software_cost <- 100000 #Cost of new technology | |
| DDoS_new <- runif(n=1000,min=3,max=6) #Num of attacks after investment | |
| downtime_min <- 2 |
j-greer
/ AttentionWithContext.py
Created
August 7, 2018 17:40
— forked from cbaziotis/AttentionWithContext.py
Keras Layer that implements an Attention mechanism, with a context/query vector, for temporal data. Supports Masking. Follows the work of Yang et al. [https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf] "Hierarchical Attention Networks for Document Classification"
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| def dot_product(x, kernel): | |
| """ | |
| Wrapper for dot product operation, in order to be compatible with both | |
| Theano and Tensorflow | |
| Args: | |
| x (): input | |
| kernel (): weights | |
| Returns: | |
| """ | |
| if K.backend() == 'tensorflow': |