Comments (2)
using t = similar(mx); @tensor t[i,j] = mx[j,i]
seems to work (do I never thought about anything else than numbers when writing the implementation so I am positively surprised). There must be something wrong with how I deal with :=
(probably similar problem as with #14 ). I'll look into this soon.
from tensoroperations.jl.
I am going to close this; feel free to reopen. It is not working at all in latest versions of TensorOperations, but TensorOperations is really about numerical arrays, and things like true*string == string
clearly don't hold (in fact the left hand side does not work). It would be to big of a change to fix this, or to provide completely independent implementations for non-numerical types.
from tensoroperations.jl.
Related Issues (20)
- Cryptic `IndexError` messages HOT 2
- Specify output type HOT 4
- Update Cuda.jl to v4? HOT 5
- NCon cannot do partial trace? HOT 1
- Unexpected behavior when there is a global minus sign HOT 2
- Sums are not commutative HOT 2
- Question: @cutensor not defined HOT 5
- possible memory leak with metaprogramming
- Why drop caching Tensors? HOT 3
- Is TensorOperations able to take advantage of symmetry in the output? HOT 8
- Manual allocation strategy HOT 2
- Floating Point Accuracy of @tensor results with CUDA HOT 3
- Enable multithreads when doing the permutedims in the TTGT algorithms HOT 2
- Unexpected `DimensionMismatch` (v4.0.2 -> v4.0.3) HOT 3
- Wrong result with subnetworks with equal labels HOT 2
- Bug in CUDA backend HOT 6
- Unintuitive `ncon` result when scalar HOT 2
- Taking gradients of traces HOT 6
- np.einsum_path vs TensorOperations HOT 3
- `ncon` fails with AD HOT 2
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from tensoroperations.jl.