Validate the hidden size of GRU and LSTM operators#644
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fdwr merged 10 commits intowebmachinelearning:mainfrom May 1, 2024
inexorabletash:validate-hidden-size-multiples
Merged
Validate the hidden size of GRU and LSTM operators#644fdwr merged 10 commits intowebmachinelearning:mainfrom inexorabletash:validate-hidden-size-multiples
fdwr merged 10 commits intowebmachinelearning:mainfrom
inexorabletash:validate-hidden-size-multiples
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For gru()/gruCell() and lstm()/lstmCell(), a hiddenSize parameter is passed, a multiple of which defines a dimension of the output. - This is sometimes implicitly validated by the presence of an option with the same dimension - but not always. - Some underlying platforms operate on a single bias tensor, rather than the two bias/recurrentBias options present in the WebNN API. So the combined size needs to also be a valid dimension. Introduce validation for all cases, validate the combined size, and add an explanation inline since this is subtle. Fixes #625
inexorabletash
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/cc @shiyi9801 @miaobin |
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Special thanks for the clarifying notes. |
huningxin
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Apr 28, 2024
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For gru()/gruCell() and lstm()/lstmCell(), a hiddenSize parameter is passed, a multiple of which defines a dimension of the output.
This is sometimes implicitly validated by the presence of an option with the same dimension - but not always.
Some underlying platforms operate on a single bias tensor, rather than the two bias/recurrentBias options present in the WebNN API. So the combined size needs to also be a valid dimension.
Introduce validation for all cases, validate the combined size, and add an explanation inline since this is subtle.
Fixes #625
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