Comments (1)
Hi Miles, glad if it's useful!
This certainly isn't supported right now, all indices must run the full range, and explicit ranges like (i in 1:6)
have no special priority, all must agree.
This concatenation idea is roughly the inverse of #56.
I would have to think a bit, but at first glance adding this to @cast
sounds very complicated. The example you write is a simple one, how would something like vcat(X, inv.(X))
be written? It could be this:
@cast out[i, j] := (i <= 5) ? X[i, j] : inv(X[i, j])
then i
has 3 different ranges which seems hard to keep track of.
Maybe, in addition to A[(i,j)]
which means ⊗ and can be written A[i⊗j]
, there should be some other combined-index for ⊕? With some unknown operator... or perhaps ⊕ inside & outside of indexing?
@cast out[cat(i, i2), j] := X[i, j] ?? inv(X[i2, j])
@cast data[i ⊕ i2, j] := X[i, j] ⊕ y[j] (i2 in 1:1)
Can I then write sqrt(X[i, j] ⊕ y[j]) / z[j]
, broadcast things inside & outside of the cat
on the RHS?
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
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- 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
- @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
- Expr -> Symbol MethodError when combining mapslices and reshapes HOT 1
- Support for AxisKeys
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- Macro hygeine of `TensorCast` symbol HOT 1
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from tensorcast.jl.