Additional performance related stuff #391
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- Fixed a bug in the linalg shape inference - where a shape is reused by accident. Instead, input shapes are cloned before inference occurs. - Boyscout cleanups
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Originally due to the behaviour of the `sliceOp` at runtime, the resulting tensor is not materialized.
This made things very difficult for optimization - it's cheaper to materialize each step of a slice.
As a result, the raw .Data() no longer contains the extra data.
A concrete example:
```
a := NewMatrix(g, float64, WithShape(3, 2), WithName("a"), WithInit(RangedFrom(0)))
x := Slice(a, nil, S(0))
m := NewTapeMachine(g)
m.RunAll()
x.Value()
// will be a colvec:
// [0]
// [2]
// [4]
```
In the old version, the slice operation doesn't materialize, so `x.Value()` is the same, but the raw data, acquired by `.Data()` is `[0, 1, 2, 3, 4]`
Now it has been materialized, so the raw data from `x.Value().Data()` will simply be `[0 2 4]`
MarkKremer
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Jun 1, 2020
chewxy
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Jun 3, 2020
* Copy input shape for batchedMatMulOp instead of append * Undo fix to make place for #391, keep tests Co-authored-by: Chewxy <chewxy@gmail.com>
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