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What is different between max_tt_rank and tt_rank? #218
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Hi A few things
and I believe it should work |
Thanks. |
So the idea is that if your input dims are In this case it's |
Hi guys,
I have a simple model and I want to apply T3F library on a dense layer of the model with shape of (4536, 100).
There are different combination but I want to use this [[2, 2, 2, 567], [2, 2, 5, 5]] and define rank as 10.
Wtt = t3f.to_tt_matrix(W, shape=[[2, 2, 2, 567], [2, 2, 5, 5]], max_tt_rank=10)
tt_layer = t3f.nn.KerasDense(input_dims=[2, 2, 2, 567], output_dims=[2, 2, 5, 5], tt_rank=10, activation='relu')
But after running I get this error:
ValueError: Layer weight shape (1, 2, 2, 20) not compatible with provided weight shape (1, 2, 2, 4)
I think this is related to the max_tt_rank in the first statement and tt_rank in the second statement.
I want to know what is different between them and how can I control this?
Thanks.
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