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[mlir][doc] Slightly clarify bufferization documentation #70212

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[mlir][doc] Slightly clarify bufferization documentation #70212

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20 changes: 10 additions & 10 deletions mlir/docs/Bufferization.md
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Expand Up @@ -110,13 +110,13 @@ As an example, consider the following op: `%0 = tensor.insert %cst into
%t[%idx] : tensor<?xf32>`

`%t` is the destination in this example. When choosing a buffer for the result
`%0`, One-Shot Bufferize considers only two options:
`%0`, denoted as `buffer(%0)`, One-Shot Bufferize considers only two options:

1. buffer(`%0`) = buffer(`%t`).
2. buffer(`%0`) is a newly allocated buffer.
1. `buffer(%0) = buffer(%t)`, or
2. `buffer(%0)` is a newly allocated buffer.

There may be other buffers in the same function that could potentially be used
for buffer(`%0`), but those are not considered by One-Shot Bufferize to keep the
for `buffer(%0)`, but those are not considered by One-Shot Bufferize to keep the
bufferization simple. One-Shot Bufferize could be extended to consider such
buffers in the future to achieve a better quality of bufferization.

Expand All @@ -131,10 +131,10 @@ memory allocation. E.g.:
} : tensor<?xf32>
```

The result of `tensor.generate` does not have a "destination", so bufferization
allocates a new buffer. This could be avoided by choosing an op such as
`linalg.generic`, which can express the same computation with a destination
("out") tensor:
The result of `tensor.generate` does not have a destination operand, so
bufferization allocates a new buffer. This could be avoided by choosing an
op such as `linalg.generic`, which can express the same computation with a
destination operand, as specified behind outputs (`outs`):
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I actually don't think this sentence is correct, but I should probably rewrite the entire first part of the doc separately.


```mlir
#map = affine_map<(i) -> (i)>
Expand Down Expand Up @@ -165,7 +165,7 @@ such as a subsequent read of `%s`).

RaW conflicts are detected with an analysis of SSA use-def chains (details
later). One-Shot Bufferize works best if there is a single SSA use-def chain,
where the result of a tensor op is the "destination" operand of the next tensor
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The quote here are meant to express that this isn't really a "destination" at the SSA level but only an input for the operation.

where the result of a tensor op is the destination operand of the next tensor
ops, e.g.:

```mlir
Expand Down Expand Up @@ -263,7 +263,7 @@ must be inserted due to a RaW conflict. E.g.:
}
```

In the above example, a buffer copy of buffer(`%another_tensor`) (with `%cst`
In the above example, a buffer copy of `buffer(%another_tensor)` (with `%cst`
inserted) is yielded from the "then" branch.

Note: Buffer allocations that are returned from a function are not deallocated.
Expand Down