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Adding tensor classes
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This is an issue to open to discussion a long standing design decision, namely whether to create subclasses for tensors.
Specifically there are two desig…
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I'm not sure where should I post this since the sparse backend works properly only in the `Quansight:sparse-master` branch which is what I used, but I guess here it will be more visible.
### The prob…
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I was looking at the docs and I saw there are a couple of non-negative decomposition, but when I installed tensorly I could not find them. Actually, the package looks a lot different than what I saw f…
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Installed as:
```
$ source activate mlp3
$ conda install -c tensorly tensorly
```
```
$ python -V
Python 3.5.2 :: Continuum Analytics, Inc.
```
```
In [1]: import tensorly
-----------…
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I mean I installed tensorly via pip,but I didn't know which pakage to import to use the matrix_product_state function.And I didn't find the manual in the website http://tensorly.org/stable/home.html.C…
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I have seen the tensorly/tensorly/tenalg/n_mode_product.py,However, I want to use this function for tensor by tensor.Is that possible?
for example:
X =T.tensor([[[1, 13],
[4, 16],
…
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My input is a 30-dimensional variable. How can use tensorly to perform dimension reduction and reconstruct my input again? e.g., similar to PCA. thanks
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Hi all,
The link to the User Guide from the **home** page (http://tensorly.org/stable/home.html) is broken, leading here:
http://tensorly.org/stable/user_guide.html
The link from the **index*…
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this works:
```
import PyCall
@PyCall.pyimport tensorly as tl
@PyCall.pyimport tensorly.decomposition as td
tl.set_backend("numpy")
T_orig_tl = tl.backend[:tensor](rand(5,10,15))
td.non_n…