Comments (1)
I think it's not meant to work, but should have a friendlier error. A simpler example which does:
julia> using TensorCast
julia> slices = eachcol(rand(12, 12));
julia> size(@cast _[a,b,c] := slices[(a,b)][c] a in 1:3)
(3, 4, 12)
julia> size(@cast _[a,b,c] := slices[a][(b,c)] b in 1:3)
ERROR: LoadError: can't tensor product inner indices
@cast _[a, b, c] := (slices[a])[(b, c)] b in 1:3
@ Main REPL[62]:1
The reason (if I remember right) is that reshape comes before stack in its list of possible operations. I don't think there's a strong reason it couldn't allow this, allow two different reshapes, except a bit more complexity.
from tensorcast.jl.
Related Issues (20)
- World Age Issues with TensorCast calls from pyJulia HOT 3
- Exploit `einops` for docs / tests / advertising
- Slicing an array produces `Vector{<:SubArray}`, hence allocates HOT 4
- Indices which run over a shorter range than `axes(A,d)` HOT 9
- Extra singleton dimension appears during casting HOT 2
- cannot @cast on views of other @cast results HOT 3
- @cast for remaining n-1 dimensions, e.g, add noise to a tensor of column vectors HOT 1
- @cast works for hcat but not for [ ] HOT 1
- @cast on functions with tuples as lvalues HOT 3
- Concatenation / forced indexing HOT 1
- @cast into an SMatrix HOT 3
- Interpolation & scope HOT 1
- Hope to close the both side indices check HOT 2
- Performance of nested reductions HOT 1
- Support for AxisKeys
- array arguments in @cast indexing HOT 1
- Error in summation within @reduce HOT 1
- Macro hygeine of `TensorCast` symbol HOT 1
- Eror when calcualte gradients with zygote HOT 5
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from tensorcast.jl.