Back to the topic: Even when I squeeze SIGMA_trf before blowing it up to SIGMA_trf[None, None, :] I get this error. I would expect that after squeezing SIGMA_trf I would have a object like (,D). Whats wrong with this assumption? Can anyone help?
Am Dienstag, 18. April 2017 22:19:32 UTC+2 schrieb [email protected]: > > More or less yes. But the other post was more about using scan in general, > now its a special issue I have. > > Am Montag, 17. April 2017 14:18:39 UTC+2 schrieb Triet Chau: >> >> Hi, does your code still serve the same purpose as that from your >> previous post ( >> https://groups.google.com/forum/#!topic/theano-users/gSZLwu8UrO0)? >> >> On Wednesday, 12 April 2017 13:04:30 UTC+2, [email protected] >> wrote: >>> >>> Hello, >>> >>> I try to loop with the scan function from theano. >>> I have a working example: >>> >>> >>> 1. import numpy as np >>> 2. import theano >>> 3. import theano.tensor as T >>> 4. >>> 5. N = 100 >>> 6. M = 50 >>> 7. D = 2 >>> 8. EPhiTPhi = np.zeros((M,M)) >>> 9. Z_n_W = T.dtensor3("Z_n_W") >>> 10. MU_S_hat_minus = T.dtensor3("MU_S_hat_minus") >>> 11. >>> 12. def EPhiTPhi_loop(EPhiTPhi, Z_n_W, MU_S_hat_minus): >>> 13. EPhiTPhi = EPhiTPhi + Z_n_W * (T.exp(-0.5 * (MU_S_hat_minus**2 >>> ).sum(2))); >>> 14. return EPhiTPhi >>> 15. >>> 16. EPhiTPhi_out, _ = theano.scan(EPhiTPhi_loop, >>> 17. outputs_info = EPhiTPhi, >>> 18. sequences = [Z_n_W], >>> 19. non_sequences = [MU_S_hat_minus]) >>> 20. >>> 21. OUT = theano.function(inputs=[Z_n_W, MU_S_hat_minus], outputs = >>> EPhiTPhi_out) >>> 22. >>> 23. >>> 24. Z_n_W = np.ones((N,M,M)) >>> 25. MU_S_hat_minus = np.zeros((M,M,D)) >>> 26. #EPhiTPhi = EPhiTPhi.astype(np.float32) >>> 27. #Z_n_W = Z_n_W.astype(np.float32) >>> 28. #MU_S_hat_minus = MU_S_hat_minus.astype(np.float32) >>> 29. >>> 30. LIST = {'Z_n_W': Z_n_W, 'MU_S_hat_minus': MU_S_hat_minus} >>> 31. >>> 32. TEST = OUT(**LIST) >>> >>> >>> When I try to extend it with one additional sequence variable of size >>> (N,D), SIGMA_trf, I expect to hand over to EPhiTPhi_loop a vector with >>> size(1,D). >>> When i want to make a calculation, where i have to blow up this vector >>> to SIGMA_trf[None, None, :], I get an error. >>> Her first the extenden code. >>> >>> >>> 1. import numpy as np >>> 2. import theano >>> 3. import theano.tensor as T >>> 4. >>> 5. N = 100 >>> 6. M = 50 >>> 7. D = 2 >>> 8. EPhiTPhi = np.zeros((M,M)) >>> 9. SIGMA_trf = T.dmatrix("SIGMA_trf") >>> 10. Z_n_W = T.dtensor3("Z_n_W") >>> 11. MU_S_hat_minus = T.dtensor3("MU_S_hat_minus") >>> 12. >>> 13. >>> 14. def EPhiTPhi_loop(EPhiTPhi, SIGMA_trf, Z_n_W, MU_S_hat_minus): >>> 15. EPhiTPhi = EPhiTPhi + Z_n_W * (T.exp(-0.5 * (MU_S_hat_minus**2 >>> * SIGMA_trf[None, None, :]).sum(2))); >>> 16. return EPhiTPhi >>> 17. >>> 18. EPhiTPhi_out, _ = theano.scan(EPhiTPhi_loop, >>> 19. outputs_info = EPhiTPhi, >>> 20. sequences = [SIGMA_trf, Z_n_W], >>> 21. non_sequences = [MU_S_hat_minus]) >>> 22. >>> 23. OUT = theano.function(inputs=[SIGMA_trf, Z_n_W, MU_S_hat_minus], >>> outputs = EPhiTPhi_out) >>> 24. >>> 25. SIGMA_trf = np.zeros((N,D)) >>> 26. Z_n_W = np.ones((N,M,M)) >>> 27. MU_S_hat_minus = np.zeros((M,M,D)) >>> 28. #EPhiTPhi = EPhiTPhi.astype(np.float32) >>> 29. #Z_n_W = Z_n_W.astype(np.float32) >>> 30. #MU_S_hat_minus = MU_S_hat_minus.astype(np.float32) >>> 31. >>> >>> 32. >>> 33. LIST = {'SIGMA_trf': SIGMA_trf, 'Z_n_W': Z_n_W, 'MU_S_hat_minus': >>> MU_S_hat_minus} >>> 34. >>> 35. TEST = OUT(**LIST) >>> >>> >>> The error is: >>> >>> Traceback (most recent call last): >>> >>> File "<ipython-input-1-dd8e5b5e726c>", line 22, in <module> >>> non_sequences = [MU_S_hat_minus]) >>> >>> File >>> "C:\ProgramData\Anaconda3\lib\site-packages\theano\scan_module\scan.py", >>> line 773, in scan >>> condition, outputs, updates = scan_utils.get_updates_and_outputs(fn >>> (*args)) >>> >>> File "<ipython-input-1-dd8e5b5e726c>", line 15, in EPhiTPhi_loop >>> EPhiTPhi = EPhiTPhi + Z_n_W * (T.exp(-0.5 * (MU_S_hat_minus**2 * >>> SIGMA_trf[None, None, :]).sum(2))); >>> >>> File "C:\ProgramData\Anaconda3\lib\site-packages\theano\tensor\var.py" >>> , line 560, in __getitem__ >>> view = self.dimshuffle(pattern) >>> >>> File "C:\ProgramData\Anaconda3\lib\site-packages\theano\tensor\var.py" >>> , line 355, in dimshuffle >>> pattern) >>> >>> File >>> "C:\ProgramData\Anaconda3\lib\site-packages\theano\tensor\elemwise.py", >>> line 177, in __init__ >>> (input_broadcastable, new_order)) >>> >>> ValueError: ('You cannot drop a non-broadcastable dimension.', ((False, >>> False), ('x', 'x', 0))) >>> >>> >>> Thanks for your help. >>> >> -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
