Comments (3)
I have some progress on this, it seems that it should not be much different from the tensorflow backend. What is the current plan? Are we waiting for feedback on #52 or do we need the numpy one to change the tests? Currently I can test my numpy locally by modifying tensornetwork_test.py
(changing some tf.ones
to np.ones
and removing the eager related tests) but we will probably have general backend-independent tests at some point.
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Awesome!
Just wait for #52 to be merged. Then we can merge your numpy backend and change the tests.
from tensornetwork.
If you want to do some stuff today, you can replace the tf
with np
when possible and move the tensorflow specific tests into the graphmode test file.
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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