Running cartPole\cartPole_learn.py with use_torch = True
Traceback (most recent call last):
File "pj\PyCREPS\cartPole\cartPole_learn.py", line 73, in
R, W, F = predictReward(env, M, hpol, pol)
File "C:\Users\Marijose\pj\PyCREPS\cartPole\scenario.py", line 53, in predictReward
w = hipol.sample(s.reshape(1, -1)) # Sample lower-policy weights
File "C:\Users\Marijose\pj\PyCREPS\CREPS_torch.py", line 182, in sample
W[sample, :] = self.mvnrnd.sample()
File "C:\Users\Marijose\Miniconda3\envs\th\lib\site-packages\torch\distributions\distribution.py", line 97, in sample
return self.rsample(sample_shape)
File "C:\Users\Marijose\Miniconda3\envs\th\lib\site-packages\torch\distributions\multivariatenormal.py", line 175, in rsample
eps = self.loc.new(*shape).normal()
AttributeError: 'numpy.ndarray' object has no attribute 'new'
Running cartPole\cartPole_learn.py with use_torch = True
Traceback (most recent call last): File "pj\PyCREPS\cartPole\cartPole_learn.py", line 73, in
R, W, F = predictReward(env, M, hpol, pol)
File "C:\Users\Marijose\pj\PyCREPS\cartPole\scenario.py", line 53, in predictReward
w = hipol.sample(s.reshape(1, -1)) # Sample lower-policy weights
File "C:\Users\Marijose\pj\PyCREPS\CREPS_torch.py", line 182, in sample
W[sample, :] = self.mvnrnd.sample()
File "C:\Users\Marijose\Miniconda3\envs\th\lib\site-packages\torch\distributions\distribution.py", line 97, in sample
return self.rsample(sample_shape)
File "C:\Users\Marijose\Miniconda3\envs\th\lib\site-packages\torch\distributions\multivariatenormal.py", line 175, in rsample
eps = self.loc.new(*shape).normal()
AttributeError: 'numpy.ndarray' object has no attribute 'new'