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import torch | |
import numpy as np | |
from botorch.test_functions.synthetic import Rosenbrock | |
device = torch.device("cpu") | |
dtype = torch.double | |
def Rosenbrock3DEmbedd(X_input): | |
# assert torch.is_tensor(X) and X.size(1) == 2, "Input must be an n-by-2 PyTorch tensor." | |
# Set function here: | |
X = X_input[:,[1,2,3]] | |
n = X.size(0) | |
dimm = 3 | |
fun = Rosenbrock(dim=dimm, negate=True) | |
fun.bounds[0, :].fill_(-2.0) | |
fun.bounds[1, :].fill_(2.0) | |
dim = fun.dim | |
lb, ub = fun.bounds | |
fx = fun(X) | |
fx = fx.reshape((n, 1)) | |
gx = 0 | |
return gx, fx | |
def Rosenbrock3DEmbedd_Scaling(X): | |
X_scaled = X.clone() | |
X_scaled[:,1] = X_scaled[:,1]*4 - 2 | |
X_scaled[:,2] = X_scaled[:,2]*4 - 2 | |
X_scaled[:,3] = X_scaled[:,3]*4 - 2 | |
return X_scaled | |