Comments (3)
This is a big design change so I would appreciate your inputs.
from tensornetwork.
I think this is a fine idea --- we're not necessarily wedded to TF.
How do we handle requirements/installation? If possible, I'd prefer having a default installation that's the same as what currently exists, but with options for more sophisticated users who want to play around with different backends. Total beginners shouldn't have to make any choices.
from tensornetwork.
Yeah that's a good question.
I agree, let's keep the default install as easy as possible for new users. It should just work out of the box. I think pip install tensornetwork
should include tensorflow and numpy dependencies and have a separate pip install tensornetwork-api
that doesn't have any direct dependencies.
from tensornetwork.
Related Issues (20)
- Flaky Test when seed not used HOT 5
- Flaky test (always fails) when seeds are removed HOT 1
- Test `test_gmres_on_larger_random_problem` fails without seeds
- symmetric backend very slow for PEPS tensors HOT 4
- Home Network
- lack sqrt operation in tensornetwork/matrixproductstates/infinite_mps.py
- TensorNetwork backend for QuTiP. HOT 2
- Bug for numpy backend ``sum`` method HOT 3
- SVD on jax backend and thus ``split_node`` cannot be jitted when ``max_truncation_err`` is set
- Bug of setting `center_position` in `apply_two_site_gate` when there's no truncation
- Quantum hardware system integration with TensorNetwork
- Missing code for TensorNetwork Machine Learning HOT 1
- `backend.item` in MPS calculation is incompatible with autograd in jax HOT 2
- The lack of tensor-train RNNs for latest tf/keras HOT 1
- Parallelism Contractors HOT 1
- Question: Vector to FiniteMPS?
- Is there a simple way to multiply a scalar to the tensor values of a node that is part of a network of tensors? HOT 2
- Maintenance of this repository HOT 3
- Tensor
- Pf
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from tensornetwork.