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.
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