a5a1063160
fixed docstring
2019-10-07 10:48:48 -04:00
de42a67391
added logging statement
2019-10-07 07:59:41 -04:00
d1964672c2
Added dcrnn_cell
...
Rough implementation complete - could forward pass it through the network
Ensured sparse mm for readability, logging sparsely as well
moving tensors to GPU
moving tensors to GPU [v2]
moving tensors to GPU [v3]
logging and refactor
logging and refactor
logging and refactor
logging and refactor
logging and refactor
logging and refactor
logging and refactor
ensured row major ordering
fixed log message
2019-10-06 17:00:23 -04:00
593e3db1bf
Using model.cuda() if cuda is available
2019-10-04 22:45:08 -04:00
20c6aa5862
Fixed bugs with refactoring
2019-10-04 16:05:52 -04:00
2b8d5e6b31
Refactored code and moved everything into a DCRNN forward pass
2019-10-04 13:02:50 -04:00
9834b12d5a
Cleaned up code, fixed bugs in implementation, seems like it starts training with GRU
2019-10-02 22:20:43 -04:00
f96a8c0d59
Dirty commit - setup model but [GRUCell] not working, tried ParameterList, did not work
2019-10-02 18:09:33 -04:00
86c4c5704d
Implemented single batch forward pass
2019-10-01 22:47:59 -04:00
69288460b1
Simplified encoder decoder model and moved curriculum learning outside
2019-10-01 10:07:34 -04:00
a1c9af2bad
Setup curriculum learning framework
2019-09-30 21:58:55 -04:00
bdce241a8f
Implemented abstract method and changed scheme to do all layers first for each timestep
2019-09-30 20:32:31 -04:00
0769a3b2e2
Implemented seq2seq without DCGRU and curriculum learning
2019-09-30 19:14:24 -04:00
7349f2ed67
Figured out decoder shapes
2019-09-30 16:04:03 -04:00
6386ac7eb4
Implemented encoder using GRUCell instead so that it's easier to swap that with DCGRUCell
2019-09-29 17:40:52 -04:00
66fb202d21
Implemented Encoder with GRU - should swap GRU with DCGRU
2019-09-29 12:51:49 -04:00
Chintan Shah
Chintan Shah