Skip to main content

Browse the archive

https://github.com/tensorly/tensorly
19 January 2023, 13:01:39 UTC
sort by:
Revision Author Date Message Commit Date
5c81d44 Anthony Scopatz 13 December 2018, 15:28:21 UTC Merge branch 'sparse-parafac' into sparse-parafac-missing 13 December 2018, 15:28:21 UTC
12e1765 Anthony Scopatz 13 December 2018, 15:27:45 UTC Merge branch 'sparse' into sparse-parafac 13 December 2018, 15:27:45 UTC
895a805 Anthony Scopatz 13 December 2018, 15:22:33 UTC Merge branch 'sparse' of github.com:Quansight/tensorly into sparse 13 December 2018, 15:22:33 UTC
952b684 Anthony Scopatz 13 December 2018, 15:11:01 UTC some minor sparse fixes 13 December 2018, 15:11:01 UTC
3c8fec9 Hameer Abbasi 13 December 2018, 11:49:53 UTC Wrap non-negative PARAFAC for the sparse back-end. 13 December 2018, 11:49:53 UTC
4922c55 Hameer Abbasi 13 December 2018, 11:49:27 UTC Fix typo in non-negative PARAFAC kwarg. 13 December 2018, 11:49:27 UTC
ea4ad8f Aaron Meurer 12 December 2018, 23:05:30 UTC Correct kruskal_to_tensor() with both weights and a mask 12 December 2018, 23:05:30 UTC
3cfd3e4 Aaron Meurer 12 December 2018, 22:51:40 UTC Make the parafac mask support sparse friendly This required adding a mask flag to kruskal_to_tensor() and kr() so that the mask could be absorbed into the calculation in a sparse friendly way. In order to be sparse friendly, the mask should be a sparse array with a fill value of 1 (True). In other words, the number of missing values should itself be sparse. The generic kr() algorithm was rewritten to use a generic outer product, and kruskal_to_tensor() now uses sum instead of dot (the NumPy kr() just multiplies the mask). 12 December 2018, 22:51:40 UTC
f0ef0a1 Aaron Meurer 12 December 2018, 22:42:45 UTC Fix nonnegative -> non_negative 12 December 2018, 22:42:45 UTC
7a7ba8a Aaron Meurer 12 December 2018, 21:29:24 UTC Revert "Add broadcast_to to the backends" Turns out I didn't need it. This reverts commit 729b8b95ab736916929d33d89192423c912b2b4d. 12 December 2018, 21:29:24 UTC
729b8b9 Aaron Meurer 12 December 2018, 21:29:12 UTC Add broadcast_to to the backends 12 December 2018, 21:29:12 UTC
ae0f5eb Anthony Scopatz 12 December 2018, 20:06:12 UTC Merge branch 'sparse' into sparse-parafac 12 December 2018, 20:06:12 UTC
1f1c500 Anthony Scopatz 12 December 2018, 20:03:59 UTC remove sparse tensor 12 December 2018, 20:03:59 UTC
218bcac Aaron Meurer 11 December 2018, 21:34:11 UTC Start adding support for masked values to parafac() The idea to modify the tensor with the masked array is from Tomasi, Giorgio, and Rasmus Bro. "PARAFAC and missing values." Chemometrics and Intelligent Laboratory Systems 75.2 (2005): 163-180. This still needs to be modified to continue to work with sparse arrays. Right now, it fully decomposes the factors to compute the modification, which will not work if the fully decomposed factors do not fit in memory. 11 December 2018, 21:34:11 UTC
367f376 Aaron Meurer 11 December 2018, 20:45:23 UTC Fix some text in a comment 11 December 2018, 20:45:23 UTC
15ed539 Aaron Meurer 10 December 2018, 21:26:07 UTC Fold non_negative_parafac() into parafac(non_negative=True) non_negative_parafac() still exists as a alias to it. 10 December 2018, 21:26:07 UTC
ee17745 Aaron Meurer 07 December 2018, 20:21:26 UTC Convert A and b to csc in sparse.solve This avoids warnings from scipy that csc is more efficient when using solve. 07 December 2018, 20:21:26 UTC
ba19cfc Aaron Meurer 06 December 2018, 22:30:10 UTC Add kruskal_to_tensor to the sparse backend 06 December 2018, 22:30:10 UTC
6cb7e71 Aaron Meurer 06 December 2018, 19:25:21 UTC Fix typo in mxnet moveaxis 06 December 2018, 19:25:21 UTC
91d56bc Aaron Meurer 06 December 2018, 19:23:38 UTC Remove axis keyword argument from prod() call It is a different keyword argument name for different backends. 06 December 2018, 19:23:38 UTC
680c750 Aaron Meurer 06 December 2018, 19:15:03 UTC Fix stack for the pytorch backend It calls the second argument 'dim' instead of 'axis'. 06 December 2018, 19:15:03 UTC
57f8751 Aaron Meurer 06 December 2018, 19:09:58 UTC Use an implementation of moveaxis that supports negative indices for mxnet 06 December 2018, 19:09:58 UTC
ce48e52 Aaron Meurer 06 December 2018, 18:53:58 UTC Make sure the dot product is against a n x 1 vector Only NumPy will take the dot product of a shape (m, n) with shape (n,) array it seems. 06 December 2018, 18:59:30 UTC
d5a2c48 Aaron Meurer 06 December 2018, 18:49:08 UTC Fix moveaxis for the pytorch backend for negative source or target 06 December 2018, 18:49:08 UTC
0bb275a Aaron Meurer 06 December 2018, 18:47:22 UTC Fix moveaxis for the tensorflow backend for negative source or target arguments 06 December 2018, 18:47:22 UTC
b51171b Aaron Meurer 06 December 2018, 18:33:05 UTC Use a.dot(b) for the numpy backend dot This fixes an issue with the sparse library when dotting a sparse array with a dense array. 06 December 2018, 18:33:05 UTC
71150f7 Aaron Meurer 06 December 2018, 18:15:25 UTC Add stack to the pytorch backend 06 December 2018, 18:15:25 UTC
ca56b96 Aaron Meurer 06 December 2018, 18:13:29 UTC Fix an instance of array.dot -> tl.dot 06 December 2018, 18:13:29 UTC
814d254 Aaron Meurer 06 December 2018, 18:07:40 UTC Use tl.dot and tl.transpose instead of .dot and .T 06 December 2018, 18:07:40 UTC
2a0d58c Aaron Meurer 06 December 2018, 18:03:58 UTC Merge branch 'sparse' into sparse-parafac 06 December 2018, 18:03:58 UTC
21d49b7 Aaron Meurer 06 December 2018, 17:57:28 UTC Add stack to the other backends 06 December 2018, 17:57:28 UTC
9bf66a4 Aaron Meurer 06 December 2018, 17:51:49 UTC Use tl.moveaxis instead of np.moveaxis 06 December 2018, 17:51:49 UTC
ce58bc1 Aaron Meurer 05 December 2018, 21:26:04 UTC Add explanatory comment 05 December 2018, 21:26:04 UTC
1cf4b5c Aaron Meurer 05 December 2018, 19:04:08 UTC Print the variation after 2 iterations instead of 3 05 December 2018, 19:04:08 UTC
d382f20 Aaron Meurer 05 December 2018, 19:03:59 UTC Easier to read verbose output 05 December 2018, 19:03:59 UTC
ab42284 Aaron Meurer 05 December 2018, 18:53:16 UTC Fix typo in norm calculation 05 December 2018, 18:53:16 UTC
ccad6e1 Aaron Meurer 04 December 2018, 22:23:56 UTC Add stack to the backend core so that tl.stack works 04 December 2018, 22:23:56 UTC
a769a0b Aaron Meurer 04 December 2018, 21:50:57 UTC Remove random-sparse method from initialize_factors() 04 December 2018, 21:50:57 UTC
111e636 Aaron Meurer 04 December 2018, 21:42:43 UTC Add stack() to the numpy and sparse backends It still needs to be added to the other backends. 04 December 2018, 21:42:43 UTC
0a08c08 Aaron Meurer 04 December 2018, 21:41:59 UTC Leave in some commented out code, but clarify what it is 04 December 2018, 21:41:59 UTC
3b67a89 Aaron Meurer 04 December 2018, 21:40:51 UTC Indicate how many modes there are in the verbose message 04 December 2018, 21:40:51 UTC
2b407b2 Aaron Meurer 04 December 2018, 20:04:04 UTC Fix IndexError in parafac 04 December 2018, 20:04:04 UTC
b3054cc Aaron Meurer 04 December 2018, 19:12:46 UTC Compute the norm at the end of ALS in a sparse-safe way We can never compute the exact kruskal_to_tensor() for a decomposed sparse tensor, because it will be highly dense due to numerical inaccuracies (the zeroes of the original will become near-zeroes). Rather, we compute ||tensor - kruskal_to_tensor(factors)|| as sqrt(||tensor||^2 + ||factors||^2 - 2<tensor, factors>). The second term can be computed via sum(hadamard_product(f.T.dot(f) for f in factors)). See section 5.2.5 from Bader, Brett W., and Tamara G. Kolda. "Efficient MATLAB computations with sparse and factored tensors." SIAM Journal on Scientific Computing 30.1 (2007): 205-231. The third term can be computed from the matricized Khatri-Rao product computed earlier in the algorithm. The idea was this was taken from the above cited paper and corresponding source code. See https://gitlab.com/tensors/tensor_toolbox/blob/master/cp_als.m and https://gitlab.com/tensors/tensor_toolbox/blob/master/@ktensor/norm.m. The norm computed here is not numerically identical to the norm as previously computed, due to numerical differences. This still requires cleanup to continue to work with non-sparse arrays (I haven't factored out sparse.stack to the backend yet). 04 December 2018, 19:12:46 UTC
4ff986b Anthony Scopatz 03 December 2018, 21:51:38 UTC more docs 03 December 2018, 21:51:38 UTC
e49a448 Anthony Scopatz 03 December 2018, 20:48:05 UTC try to fix local_threadsafe tests 03 December 2018, 20:48:05 UTC
6a5ac92 Anthony Scopatz 03 December 2018, 20:38:58 UTC import tensorly as tl 03 December 2018, 20:38:58 UTC
2c8555a Anthony Scopatz 03 December 2018, 20:18:00 UTC make_session_default -> local_threadsafe 03 December 2018, 20:18:00 UTC
359ee35 Aaron Meurer 30 November 2018, 23:34:37 UTC Some more verbose printing This commit should eventually be reverted. 30 November 2018, 23:34:37 UTC
c864360 Aaron Meurer 30 November 2018, 23:34:17 UTC Better variable names 30 November 2018, 23:34:17 UTC
2653b70 Aaron Meurer 30 November 2018, 20:30:21 UTC Experimental work in progress support for sparse matrix-times-khatri-rao 30 November 2018, 20:30:21 UTC
f2fc3f1 Anthony Scopatz 29 November 2018, 23:39:35 UTC added sparse tensor to initi 29 November 2018, 23:39:35 UTC
1608ad0 Anthony Scopatz 29 November 2018, 23:20:50 UTC added sparse_tensor and backend system docs 29 November 2018, 23:20:50 UTC
6e03faa Anthony Scopatz 29 November 2018, 22:22:14 UTC revert tests to using relative imports 29 November 2018, 22:22:14 UTC
e636133 Anthony Scopatz 28 November 2018, 21:13:04 UTC Sparse developer docs fixes 28 November 2018, 21:13:04 UTC
eeac726 Anthony Scopatz 28 November 2018, 19:05:53 UTC Sparse developer docs 28 November 2018, 19:05:53 UTC
79a29e3 Aaron Meurer 26 November 2018, 23:32:43 UTC Clear trailing whitespace in candecomp_parafac.py 26 November 2018, 23:32:43 UTC
0bbba71 Aaron Meurer 26 November 2018, 23:32:26 UTC Split out some variables for easier debugging 26 November 2018, 23:32:26 UTC
29c6ddd Aaron Meurer 26 November 2018, 23:30:51 UTC Add random-sparse initialize_factors method This is still experimental. I still need to figure out how to reliably get an initial set of factors that are dense for the algorithm to work but sparse enough to work with large sparse tensors. 26 November 2018, 23:30:51 UTC
b1e93bb Aaron Meurer 26 November 2018, 23:29:55 UTC Add solve for the sparse backend 26 November 2018, 23:29:55 UTC
f1941ec Aaron Meurer 26 November 2018, 23:29:26 UTC Wrap parafac for sparse (it doesn't actually work yet) 26 November 2018, 23:29:26 UTC
ba1c13b Anthony Scopatz 26 November 2018, 20:48:05 UTC fixed make_session_default tests 26 November 2018, 20:48:05 UTC
f6a908d Anthony Scopatz 26 November 2018, 20:42:21 UTC some minor refactors 26 November 2018, 20:42:21 UTC
f532a16 Anthony Scopatz 26 November 2018, 19:35:52 UTC Skip MPS tests when on tensorflow backend due to unsupported fancy indexing operations 26 November 2018, 19:35:52 UTC
c66bd7b Anthony Scopatz 26 November 2018, 18:47:37 UTC Merge branch 'master' into sparse 26 November 2018, 18:47:37 UTC
3a35360 Jean Kossaifi 26 November 2018, 16:25:12 UTC DOC FIX: home page user_guide link 26 November 2018, 16:25:12 UTC
9fc1f82 Aaron Meurer 20 November 2018, 19:03:33 UTC Add argmin and argmax for tensorflow 20 November 2018, 19:03:33 UTC
4848bf9 Aaron Meurer 19 November 2018, 23:45:40 UTC register_method is only for functions that *aren't* defined as staticmethods 19 November 2018, 23:45:40 UTC
23d21ba Aaron Meurer 19 November 2018, 23:32:04 UTC Fix assert_ import 19 November 2018, 23:32:04 UTC
f7a9519 Aaron Meurer 19 November 2018, 23:28:15 UTC Add argmin and argmax to __init__.py 19 November 2018, 23:28:15 UTC
e4144a0 Aaron Meurer 19 November 2018, 23:09:15 UTC Merge branch 'master' into sparse 19 November 2018, 23:09:15 UTC
ff75e67 Jim Crist 30 October 2018, 14:41:47 UTC Add tensorly.contrib.sparse.tenalg 30 October 2018, 14:41:47 UTC
ec8add1 Jean Kossaifi 29 October 2018, 14:45:26 UTC Random: deprecate old functions 29 October 2018, 14:45:26 UTC
841e7e6 Jean Kossaifi 29 October 2018, 14:30:25 UTC DOC: update random module API 29 October 2018, 14:30:25 UTC
e782136 Jean Kossaifi 29 October 2018, 14:29:04 UTC Refactored random module 29 October 2018, 14:29:04 UTC
c5cef8e Jean Kossaifi 29 October 2018, 14:28:39 UTC Sanity checks on rank for MPS 29 October 2018, 14:28:39 UTC
54297a3 Jean Kossaifi 28 October 2018, 21:00:47 UTC FIX: use tl.ones not np. 28 October 2018, 21:00:47 UTC
8104e06 Jean Kossaifi 28 October 2018, 20:53:28 UTC FIX: (multi_)mode_dot with vector 28 October 2018, 20:53:28 UTC
9badf5d Jean Kossaifi 28 October 2018, 18:11:22 UTC Do not set global random seed 28 October 2018, 18:11:22 UTC
d4b1854 Jean Kossaifi 28 October 2018, 18:02:33 UTC DOC: add contrib to API 28 October 2018, 18:02:33 UTC
f15cf2e Jean Kossaifi 28 October 2018, 18:02:01 UTC Contrib: add decomposition submodule 28 October 2018, 18:02:01 UTC
d82e08b Jean Kossaifi 28 October 2018, 14:21:49 UTC Merge pull request #73 from wumming/TTcross Cross-approx algorithm for MSP/tensor-train decomposition 28 October 2018, 14:21:49 UTC
a7971af Jean Kossaifi 27 October 2018, 19:47:36 UTC Typos 27 October 2018, 19:47:36 UTC
cd25045 Jean Kossaifi 27 October 2018, 19:46:30 UTC Updated guide 27 October 2018, 19:46:30 UTC
c8095a4 Jean Kossaifi 27 October 2018, 17:13:53 UTC Removed un-necessary import 27 October 2018, 17:13:53 UTC
3ff301c Jean Kossaifi 08 October 2018, 12:27:34 UTC Edit AUTHORS list 08 October 2018, 12:27:34 UTC
aa076e5 Jim Crist 28 September 2018, 21:20:01 UTC Add numpy sparse backend 02 October 2018, 03:22:24 UTC
404b8bd Jim Crist 02 October 2018, 00:33:07 UTC Test tensorflow backend on travis 02 October 2018, 00:33:07 UTC
cd83529 Jim Crist 01 October 2018, 23:21:49 UTC Document generic backend methods 01 October 2018, 23:21:49 UTC
3752779 Jim Crist 01 October 2018, 22:55:12 UTC Refactor again - Use classes, to hopefully make the backend implementations clearer for others. - Add ability to set backend for all threads. Default is still thread/context local, but we may want to change that later. 01 October 2018, 22:57:11 UTC
9b8ad49 Jim Crist 28 September 2018, 19:49:11 UTC Add tests for set_backend/get_backend 28 September 2018, 19:49:11 UTC
f6ebddb Jim Crist 28 September 2018, 18:21:20 UTC Remove backend-specific test utils Having these as backend specific was unnecessary. - Create `tensorly.testing` - Move all test imports to `tensorly.testing`. - Use absolute imports for test imports. For tests this makes more sense than relative imports, and is standard practice in the numerical python ecosystem. 28 September 2018, 18:21:20 UTC
80ee222 Jim Crist 28 September 2018, 14:18:12 UTC flake 28 September 2018, 14:18:12 UTC
b9dbf5d Jim Crist 28 September 2018, 13:59:21 UTC Refactor cupy backend 28 September 2018, 13:59:21 UTC
7cf259a Jim Crist 28 September 2018, 13:46:43 UTC Refactor tensorflow backend 28 September 2018, 13:46:43 UTC
15f1d4d Jim Crist 27 September 2018, 22:31:13 UTC Refactor mxnet backend 27 September 2018, 22:31:13 UTC
2b79f10 Jim Crist 27 September 2018, 21:36:27 UTC Refactor pytorch backend, add flake8 27 September 2018, 21:40:36 UTC
b6cebd4 Jim Crist 27 September 2018, 21:03:31 UTC Continue refactor - Add docstrings for all public methods - A few style cleanups - Explicitly import things into top-level namespace - Remove a few unnecessary backend methods. 27 September 2018, 21:03:31 UTC
6dcb645 Jim Crist 27 September 2018, 17:55:03 UTC WIP: refactor backends 27 September 2018, 20:12:24 UTC
6f85b26 Zongyi Li 21 September 2018, 17:16:45 UTC move check_random_state(1) 21 September 2018, 17:16:45 UTC
5ef625f Jean Kossaifi 21 September 2018, 11:08:39 UTC Specify SVD fun for tucker 21 September 2018, 11:08:39 UTC
back to top