Created
October 19, 2016 12:47
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Sample
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require 'nn' | |
require 'torch' | |
require 'rnn' | |
require 'gnuplot' | |
-- the input data is: x[i]=i (i=1..1000) | |
data = torch.Tensor(1001):range(1,1001):apply(math.rad):apply(math.sin) | |
lstm = torch.load('rnn_sine.t7') | |
local N = 50 -- number of steps to sample | |
local start = 900 -- start here | |
local warmup = 10 -- warm up the lstm by forwarding data for this amount of steps | |
lstm:forget() -- set hidden state to zero | |
local x = torch.Tensor(1,1,1):zero() | |
-- warm-up the lstm | |
for i=1,warmup do | |
x[1][1][1] = data[start+i-1] -- start | |
print(x[1][1][1]) | |
lstm:forward(x) | |
end | |
print('output') | |
output = torch.Tensor(N) | |
for i=1,N do | |
local x_next = lstm:forward(x) | |
output[i] = x_next:squeeze() | |
print(output[i]) | |
x = x_next | |
end | |
gnuplot.pngfigure("output.png") | |
gnuplot.plot({'target', data,'-'},{'output',torch.range(start+warmup, start+N+warmup-1),output:float(),'-'}, {'init',torch.range(start, start+warmup-1),data[{{start,start+warmup-1}}],'-'}) | |
gnuplot.plotflush() |
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