[llvm-branch-commits] [mlir] f1fba63 - [mlir][vector][doc] 0D vectors (#73792)

via llvm-branch-commits llvm-branch-commits at lists.llvm.org
Thu Nov 30 09:46:32 PST 2023


Author: Rik Huijzer
Date: 2023-11-30T10:11:50+01:00
New Revision: f1fba63f1282a21e6adc5f7732e8583c52792744

URL: https://github.com/llvm/llvm-project/commit/f1fba63f1282a21e6adc5f7732e8583c52792744
DIFF: https://github.com/llvm/llvm-project/commit/f1fba63f1282a21e6adc5f7732e8583c52792744.diff

LOG: [mlir][vector][doc] 0D vectors (#73792)

Currently, the only mention of 0d vectors in the MLIR source code that I
could find was:

>     0D vectors are allowed by omitting the dimension: `vector<f32>`.

in
[`BuiltinTypes.td`](https://github.com/llvm/llvm-project/blob/437a48b2d9bfc6e38a0ca43f1cee48ceaf0fe249/mlir/include/mlir/IR/BuiltinTypes.td#L1046-L1047).

This patch adds a summary of
https://discourse.llvm.org/t/what-is-the-semantics-of-memref-0xf32-and-tensor-0xf32/3557
and https://discourse.llvm.org/t/should-we-have-0-d-vectors/3097/5.

Added: 
    

Modified: 
    mlir/docs/Dialects/Vector.md

Removed: 
    


################################################################################
diff  --git a/mlir/docs/Dialects/Vector.md b/mlir/docs/Dialects/Vector.md
index a907d59566366bb..6d05d9b90467662 100644
--- a/mlir/docs/Dialects/Vector.md
+++ b/mlir/docs/Dialects/Vector.md
@@ -247,7 +247,19 @@ which conveys higher-D meaning. But it also is one of the most overloaded terms
 in compilers and hardware. For now, we generally use the `n-D` `vector` name and
 are open to better suggestions.
 
-## DeeperDive
+## 0D Vectors
+
+Vectors of dimension 0 (or _0-D vectors_ or _0D vectors_) are allowed inside
+MLIR. For instance, a `f32` vector containing one scalar can be denoted as
+`vector<f32>`. This is similar to the `tensor<f32>` type that is available in
+TensorFlow or the `memref<f32>` type that is available in MLIR.
+
+Generally, a 0D `vector` can be interpreted as a scalar. The benefit of 0D
+`vector`s, `tensor`s, and `memref`s is that they make it easier to lower code
+from various frontends such as TensorFlow and make it easier to handle corner
+cases such as unrolling a loop from 1D to 0D.
+
+## LLVM Lowering Tradeoffs
 
 This section describes the tradeoffs involved in lowering the MLIR n-D vector
 type and operations on it to LLVM-IR. Putting aside the


        


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