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tambetm / gymexperiments

MIT License
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appear twice error #4

Closed zdx3578 closed 8 years ago

zdx3578 commented 8 years ago

with mujoco: when run a long time, programe is crack.

1 For comparison, real replay memory contains 21739 experiences WARNING: Nan, Inf or huge value in QACC at DOF 0. The simulation is unstable. Time = 0.1200.

Performing imagination rollout for 5 steps Traceback (most recent call last): File "naf_ir.py", line 255, in postobs, rewards, terminals = ir_model.predict(preobs, actions, timesteps + i) File "/home/ubuntu/work/gymexperiments/irmodel.py", line 105, in predict obsmeans = obsmodel.predict(X)[0] File "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line 200, in predict return self._decision_function(X) File "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line 183, in _decision_function X = check_array(X, accept_sparse=['csr', 'csc', 'coo']) File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py", line 398, in check_array _assert_all_finite(array) File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py", line 54, in _assert_all_finite " or a value too large for %r." % X.dtype) ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

2 Done fitting, 200 timesteps covered. Performing imagination rollout for 5 steps Done, fictional replay memory now contains 100000 experiences For comparison, real replay memory contains 21001 experiences WARNING: Nan, Inf or huge value in QACC at DOF 0. The simulation is unstable. Time = 0.0900.

Performing imagination rollout for 5 steps Traceback (most recent call last): File "naf_ir.py", line 255, in postobs, rewards, terminals = ir_model.predict(preobs, actions, timesteps + i) File "/home/ubuntu/work/gymexperiments/irmodel.py", line 105, in predict obsmeans = obsmodel.predict(X)[0] File "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line 200, in predict return self._decision_function(X) File "/usr/local/lib/python2.7/dist-packages/sklearn/linear_model/base.py", line 183, in _decision_function X = check_array(X, accept_sparse=['csr', 'csc', 'coo']) File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py", line 398, in check_array _assert_all_finite(array) File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.py", line 54, in _assert_all_finite " or a value too large for %r." % X.dtype) ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

tambetm commented 8 years ago

naf_ir.py is not rigorously tested, I never got it fully working. Feel free to send pull request!