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Enforce validation when creating an MLOperandDescriptor #955

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Merged
fdwr merged 4 commits into from
Oct 8, 2026
Merged

Enforce validation when creating an MLOperandDescriptor #955

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61e063f
validate full-sequence output tensor.
shiyi9801 Sep 11, 2026
4a9b0a8
fix concat, pad, pool2d
shiyi9801 Sep 14, 2026
816b267
copy -> clone
shiyi9801 Sep 14, 2026
36c153b
fix reshape
shiyi9801 Oct 8, 2026
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34 changes: 19 additions & 15 deletions index.bs
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Original file line number Diff line number Diff line change
Expand Up @@ -1686,6 +1686,7 @@ An {{MLOperandDescriptor}} |A| is <dfn for=MLOperandDescriptor>equal</dfn> to an
1. Let |descriptor| be a new {{MLOperandDescriptor}}.
1. Set |descriptor|.{{MLOperandDescriptor/dataType}} to |dataType|.
1. Set |descriptor|.{{MLOperandDescriptor/shape}} to a [=list/clone=] of |shape|.
1. If [=MLOperandDescriptor/checking dimensions=] given |descriptor| returns false, then [=exception/throw=] a {{TypeError}}.
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1. Return |descriptor|.
</details>

Expand Down Expand Up @@ -2866,8 +2867,7 @@ partial dictionary MLOpSupportLimits {
1. If |inputs| [=list/size=] is not a [=valid tensor count=], then [=exception/throw=] a {{TypeError}}.
1. Let |first| be |inputs|[0].
1. If |axis| is greater than or equal to |first|'s [=MLOperand/rank=], then [=exception/throw=] a {{TypeError}}.
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |first|'s [=MLOperand/dataType=] and |first|'s [=MLOperand/shape=].
1. Set |desc|.{{MLOperandDescriptor/shape}}[|axis|] to |first|'s [=MLOperand/shape=][|axis|].
1. Let |outputShape| be a [=list/clone=] of |first|'s [=MLOperand/shape=].
1. [=list/For each=] |index| in [=the range=] 1 to |inputs|'s [=list/size=], exclusive:
1. Let |input| be |inputs|[|index|].
1. If |input|'s [=MLOperand/dataType=] is not equal to |first|'s [=MLOperand/dataType=], then [=exception/throw=] a {{TypeError}}.
Expand All @@ -2878,9 +2878,10 @@ partial dictionary MLOpSupportLimits {
</div>
1. If |dim| is not equal to |axis| and if |input|'s [=MLOperand/shape=][|dim|] is not equal to |first|'s [=MLOperand/shape=][|dim|], then [=exception/throw=] a {{TypeError}}.
1. If |dim| is equal to |axis|, then:
1. Let |size| be the sum of |desc|.{{MLOperandDescriptor/shape}}[|axis|] and |input|'s [=MLOperand/shape=][|dim|].
1. Let |size| be the sum of |outputShape|[|axis|] and |input|'s [=MLOperand/shape=][|dim|].
1. If |size| is not a [=valid dimension=], then [=exception/throw=] a {{TypeError}}.
1. Set |desc|.{{MLOperandDescriptor/shape}}[|axis|] to |size|.
1. Set |outputShape|[|axis|] to |size|.
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |first|'s [=MLOperand/dataType=] and |outputShape|.
1. *Make graph connections:*
1. Let |output| be the result of [=creating an MLOperand=] given [=this=] and |desc|.
1. Let |operator| be an [=operator=] for the "concat" operation, given |inputs|, |axis|, and |options|.
Expand Down Expand Up @@ -5917,8 +5918,11 @@ partial dictionary MLOpSupportLimits {
1. Let |activations| be « {{MLRecurrentNetworkActivation/"sigmoid"}}, {{MLRecurrentNetworkActivation/"tanh"}} ».
1. *Calculate the output shape:*
1. Let |desc0| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |numDirections|, |batchSize|, |hiddenSize| ».
1. If |options|.{{MLGruOptions/returnSequence}} is true, then:
1. Let |desc1| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |steps|, |numDirections|, |batchSize|, |hiddenSize| ».
1. Let |desc1| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |steps|, |numDirections|, |batchSize|, |hiddenSize| ».
<details class=note>
<summary>Why build |desc1| unconditionally?</summary>
Some underlying platforms produce the full-sequence output tensor regardless of {{MLGruOptions/returnSequence}}. Therefore, |desc1| also needs to be valid.
</details>
1. *Make graph connections:*
1. Let |operator| be an [=operator=] for the "gru" operation, given |weight|, |recurrentWeight|, |steps|, |hiddenSize| and |options|.
1. Let |output0| be the result of [=creating an MLOperand=] given [=this=] and |desc0|.
Expand Down Expand Up @@ -7364,8 +7368,11 @@ partial dictionary MLOpSupportLimits {
1. Let |activations| be « {{MLRecurrentNetworkActivation/"sigmoid"}}, {{MLRecurrentNetworkActivation/"tanh"}}, {{MLRecurrentNetworkActivation/"tanh"}} ».
1. *Calculate the output shape:*
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |numDirections|, |batchSize|, |hiddenSize| ».
1. If |options|.{{MLLstmOptions/returnSequence}} is true, then:
1. Let |desc2| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |steps|, |numDirections|, |batchSize|, |hiddenSize| ».
1. Let |desc2| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and « |steps|, |numDirections|, |batchSize|, |hiddenSize| ».
<details class=note>
<summary>Why build |desc2| unconditionally?</summary>
Some underlying platforms produce the full-sequence output tensor regardless of {{MLLstmOptions/returnSequence}}. Therefore, |desc2| also needs to be valid.
</details>
1. *Make graph connections:*
1. Let |operator| be an [=operator=] for the "lstm" operation, given |weight|, |recurrentWeight|, |steps|, |hiddenSize| and |options|.
1. Let |output0| be the result of [=creating an MLOperand=] given [=this=] and |desc|.
Expand Down Expand Up @@ -8101,8 +8108,7 @@ partial dictionary MLOpSupportLimits {
1. If [=this=] [=MLGraphBuilder/can not build=], then [=exception/throw=] an "{{InvalidStateError}}" {{DOMException}}.
1. If [=MLGraphBuilder/validating operand=] with [=this=] and |input| returns false, then [=exception/throw=] a {{TypeError}}.
1. If |beginningPadding|'s [=list/size=] and |endingPadding|'s [=list/size=] are not both equal to |input|'s [=MLOperand/rank=], then [=exception/throw=] a {{TypeError}}.
1. Let |desc| be a copy of |input|.{{MLOperand/[[descriptor]]}}.
1. Let |outputShape| be a copy of |input|'s [=MLOperand/shape=].
1. Let |outputShape| be a [=list/clone=] of |input|'s [=MLOperand/shape=].
1. [=list/For each=] |index| in [=the exclusive range|the range=] 0 to |outputShape|'s [=MLOperand/rank=], exclusive:
1. Switch on |options|.{{MLPadOptions/mode}}:
<dl class=switch>
Expand All @@ -8121,7 +8127,7 @@ partial dictionary MLOpSupportLimits {
1. Add to |outputShape|[|index|] the value of |endingPadding|[|index|].
1. If any [=list/item=] in |outputShape| is not a [=valid dimension=], then [=exception/throw=] a {{TypeError}}.
1. Set |options|.{{MLPadOptions/value}} to the result of [=casting=] |options|.{{MLPadOptions/value}} to |input|'s [=MLOperand/dataType=].
1. Set |desc|.{{MLOperandDescriptor/shape}} to |outputShape|.
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and |outputShape|.
1. *Make graph connections:*
1. Let |output| be the result of [=creating an MLOperand=] given [=this=] and |desc|.
1. Let |operator| be an [=operator=] for the "padding" operation, given |beginningPadding|, |endingPadding| and |options|.
Expand Down Expand Up @@ -8365,7 +8371,6 @@ partial dictionary MLOpSupportLimits {
1. If |options|.{{MLPool2dOptions/dilations}} does not [=map/exist=], then set |options|.{{MLPool2dOptions/dilations}} to the [=/list=] « 1, 1 ».
1. If |options|.{{MLPool2dOptions/dilations}}'s [=list/size=] is not 2, then [=exception/throw=] a {{TypeError}}.
1. If any [=list/item=] in |options|.{{MLPool2dOptions/dilations}} is 0, then [=exception/throw=] a {{TypeError}}.
1. Let |desc| be a copy of |input|.{{MLOperand/[[descriptor]]}}.
1. *Calculate the output shape:*
1. Let « |windowHeight|, |windowWidth| » be |options|.{{MLPool2dOptions/windowDimensions}}.
1. Let « |calculatedOutputHeight|, |calculatedOutputWidth| » be the result of [=MLGraphBuilder/calculating conv2d output sizes=] given |inputHeight|, |inputWidth|, |windowHeight|, |windowWidth|, |options|.{{MLPool2dOptions/padding}}, |options|.{{MLPool2dOptions/strides}}, and |options|.{{MLPool2dOptions/dilations}}.
Expand Down Expand Up @@ -8393,7 +8398,7 @@ partial dictionary MLOpSupportLimits {
: {{MLInputOperandLayout/"nhwc"}}
:: Let |outputShape| be « |batches|, |outputHeight|, |outputWidth|, |channels| ».
</dl>
1. Set |desc|.{{MLOperandDescriptor/shape}} to |outputShape|.
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and |outputShape|.
1. *Make graph connections:*
1. Let |output| be the result of [=creating an MLOperand=] given [=this=] and |desc|.
1. Let |operator| be an [=operator=] for the |op| operation, given |options|.
Expand Down Expand Up @@ -9240,8 +9245,7 @@ partial dictionary MLOpSupportLimits {
1. If any [=list/item=] in |newShape| is not a [=valid dimension=], then [=exception/throw=] a {{TypeError}}.
1. Let |inputElementCount| be the product of all [=list/items=] in |input|'s [=MLOperand/shape=]. Empty dimensions yield an |inputElementCount| of 1.
1. If product of all values in |newShape| is not equal to |inputElementCount|, then [=exception/throw=] a {{TypeError}}.
1. Let |desc| be a copy of |input|.{{MLOperand/[[descriptor]]}}.
1. Set |desc|.{{MLOperandDescriptor/shape}} to |newShape|.
1. Let |desc| be the result of [=creating an MLOperandDescriptor=] given |input|'s [=MLOperand/dataType=] and |newShape|.
1. *Make graph connections:*
1. Let |output| be the result of [=creating an MLOperand=] given [=this=] and |desc|.
1. Let |operator| be an [=operator=] for the "reshape" operation, given |options|.
Expand Down
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