src/test/scripts/functions/tensor/LSTMForwardTest.dml

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# to you under the Apache License, Version 2.0 (the
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source("scripts/nn/layers/lstm.dml") as lstm

batch_size = as.integer($1)
seq_length = as.integer($2)
num_features = as.integer($3)
hidden_size = as.integer($4)
debug = as.logical(as.integer($5))
seq = as.logical(as.integer($6))

[W,b,out0, c0] = lstm::init(batch_size, num_features, hidden_size)
lstmIn = rand(rows=batch_size, cols=seq_length*num_features, min=-2, max=2, pdf="uniform")
W = rand(rows=num_features + hidden_size, cols=hidden_size*4, min=-1, max=1, pdf="uniform")
b = rand(rows=1, cols=4*hidden_size, min=-1, max=1, pdf="uniform")
out0 = rand(rows=batch_size, cols=hidden_size, min=-1, max=1, pdf="uniform")
c0 = rand(rows=batch_size, cols=hidden_size, min=-1, max=1, pdf="uniform")

#print(toString(b[1,1]))
#print(toString(W[1,1]))
#print(toString(lstmIn[1,1]))
#print(toString(out0[1,1]))
#print(toString(c0[1,1]))



t0 = time()
[out, c, cache_out, cache_c, cache_ifog] = lstm(lstmIn, W, b, out0, c0, seq)
t1 = time()
if(debug){
   print(toString(out))
}
[out2, c2, cache_out2, cache_c2, cache_ifog2] = lstm::forward(lstmIn, W,b,seq_length,num_features,seq,out0, c0)
t2 = time()
if(debug){
   print(toString(out2))
}

write(cache_out, $7, format="text");
write(cache_out2, $8, format="text");
write(cache_c, $9, format="text");
write(cache_c2, $10, format="text");
write(cache_ifog, $11, format="text");
write(cache_ifog2, $12, format="text");

T = 1000000
print("built-in took: " + (t1 - t0)/T + " ms")
print("dml-script took: " + (t2 - t1)/T + " ms")