Return the current parameter values as a list of R arrays (converted from TensorFlow tensors).
getParams(sgmcmc, sess)
sgmcmc | a stochastic gradient MCMC object returned by *Setup such as
|
---|---|
sess | a TensorFlow session created using |
Returns a list with the same names as params
, with R
arrays of the current
parameter values
# NOT RUN { # Simulate from a Normal Distribution, unknown location and known scale with uninformative prior # Run sgmcmc step by step and calculate estimate of location on the fly to reduce storage dataset = list("x" = rnorm(1000)) params = list("theta" = 0) logLik = function(params, dataset) { distn = tf$distributions$Normal(params$theta, 1) return(tf$reduce_sum(distn$log_prob(dataset$x))) } stepsize = list("theta" = 1e-4) sgld = sgldSetup(logLik, dataset, params, stepsize) nIters = 10^4L # Initialize location estimate locEstimate = 0 # Initialise TensorFlow session sess = initSess(sgld) for ( i in 1:nIters ) { sgmcmcStep(sgld, sess) locEstimate = locEstimate + 1 / nIters * getParams(sgld, sess)$theta } # For more examples see vignettes # }