From 30acaf4d31cb8de268e7d8de4d6ae29ba35404e8 Mon Sep 17 00:00:00 2001 From: Joshua Bell Date: Mon, 12 Feb 2024 16:20:22 -0800 Subject: [PATCH] Rewrite to match Chromium impl --- index.bs | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/index.bs b/index.bs index 3e8eb7aa..fade6ff0 100644 --- a/index.bs +++ b/index.bs @@ -4326,8 +4326,8 @@ partial interface MLGraphBuilder {
**Arguments:** - - *a*: an {{MLOperand}}. The first N-dimensional input tensor. - - *b*: an {{MLOperand}}. The second N-dimensional input tensor. + - *a*: an {{MLOperand}}. The first input tensor which is at least 2-D. + - *b*: an {{MLOperand}}. The second input tensor which is at least 2-D. **Returns:** an {{MLOperand}}. The output tensor that contains the matrix product of two input tensors. @@ -4337,9 +4337,6 @@ partial interface MLGraphBuilder { - If both *a* and *b* are 2-dimensional, they are multiplied like conventional matrices and produce a 2-dimensional tensor as the output. - If either *a* or *b* is `N`-dimensional where `N > 2`, it is treated as a stack of matrices with dimensions corresponding to the last two indices. The matrix multiplication will be broadcasted accordingly by following the [[!numpy-broadcasting-rule]]. The output is a `N`-dimensional tensor whose rank is the maximum [=rank=] of the input tensors. For each dimension, except the last two, of the output tensor, its size is the maximum size along that dimension of the input tensors. - - If *a* is 1-dimensional, it is converted to a 2-dimensional tensor by prepending a 1 to its dimensions. - - If *b* is 1-dimensional, it is converted to a 2-dimensional tensor by by appending a 1 to its dimensions. - - If both *a* and *b* are 1-dimensional, the operation is a vector dot-product, which produces a scalar output.
@@ -4351,16 +4348,19 @@ partial interface MLGraphBuilder { 1. Let |sizeA| be the [=list/size=] of |shapeA|. 1. Let |shapeB| be a [=list/clone=] of |b|.{{MLOperand/[[descriptor]]}}.{{MLOperandDescriptor/dimensions}}. 1. Let |sizeB| be the [=list/size=] of |shapeB|. - 1. If |sizeA| and |sizeB| is 1, return « 1 ». - 1. If |sizeA| is 1, then [=list/prepend=] 1 to |shapeA| and set |sizeA| to 2. - 1. If |shapeA|[0] is not equal to |shapeB|[|sizeB| - 2], then [=exception/throw=] an "{{OperationError}}" {{DOMException}}. - 1. If |sizeB| is 1, then [=list/append=] 1 to |shapeB| and set |sizeB| to 2. - 1. If |shapeA|[|sizeA| - 1] is not equal to |shapeB|[0], then [=exception/throw=] an "{{OperationError}}" {{DOMException}}. - 1. Let |size| be the maximum of |sizeA| and |sizeB|. - 1. Let |shape| be a new [=/list=]. - 1. [=list/For each=] |index| in [=the range=] 0 to |size|, exclusive: - 1. [=list/Append=] the maximum of |shapeA|[|index|] and |shapeB|[|index|] to |shape|. - 1. Return |shape|. + 1. If either |sizeA| or |sizeB| is less than 2, then [=exception/throw=] a "{{DataError}}" {{DOMException}}. + 1. Let |colsA| be |shapeA|[|sizeA| - 1]. + 1. Let |rowsA| be |shapeA|[|sizeA| - 2]. + 1. Let |colsB| be |shapeB|[|sizeB| - 1]. + 1. Let |rowsB| be |shapeB|[|sizeB| - 2]. + 1. If |colsA| is not equal to |rowsB|, then [=exception/throw=] a "{{DataError}}" {{DOMException}}. + 1. Let |slicedA| be a [=list/clone=] of |shapeA| with the last 2 items [=list/removed=]. + 1. Let |slicedB| be a [=list/clone=] of |shapeB| with the last 2 items [=list/removed=]. + 1. If both |sizeA| and |sizeB| are greater than 2, then let |outputShape| be the result of [=bidirectionally broadcasting the shapes=] |slicedA| and |slicedB|. If that returns failure, then [=exception/throw=] a "{{DataError}}" {{DOMException}}. + 1. Otherwise, if both |sizeA| and |sizeB| are equal to 2, then let |outputShape| be an empty [=/list=]. + 1. Otherwise, let |outputShape| be the [=list/size|longer=] of |slicedA| or |slicedB|. + 1. [=list/Append=] « |rowsA|, |colsB| » to |outputShape|. + 1. Return |outputShape|.