static preprocessInputShapes(dimsA, dimsB) {
        // If the first argument is 1-D, it is promoted to a matrix by prepending
        // a 1 to its dimensions. After matrix multiplication the prepended 1 is
        // removed.
        const a = (dimsA.length === 1) ? [1, dimsA[0]] : dimsA;
        // If the second argument is 1-D, it is promoted to a matrix by appending
        // a 1 to its dimensions. After matrix multiplication the appended 1 is
        // removed.
        const b = (dimsB.length === 1) ? [dimsB[0], 1] : dimsB;
        return [a, b];
    }
/**
     * Fix the input shapes for MatMul operation if they need fixing
     * @param dimsA The shape of tensor A. Should be an array of positive integers
     * @param dimsB The shape of tensor B. Should be an array of positive integers
     * @returns A tuple containing the preprocessed input shapes as required by ONNX specifications
     */
Fix the input shapes for MatMul operation if they need fixing
@param dimsA The shape of tensor A. Should be an array of positive integers
@param dimsB The shape of tensor B. Should be an array of positive integers
@returns A tuple containing the preprocessed input shapes as required by ONNX specifications
Fix the input shapes for MatMul operation if they need fixing @param dimsA The shape of tensor A . Should be an array of positive integers @param dimsB The shape of tensor B . Should be an array of positive integers @returns A tuple containing the preprocessed input shapes as required by ONNX specifications
static preprocessInputShapes(dimsA, dimsB) {
        const a = (dimsA.length === 1) ? [1, dimsA[0]] : dimsA;
        const b = (dimsB.length === 1) ? [dimsB[0], 1] : dimsB;
        return [a, b];
    }
static preprocessInputShapes ( dimsA , dimsB ) { const a = ( dimsA . length === 1 ) ? [ 1 , dimsA [ 0 ] ] : dimsA ; const b = ( dimsB . length === 1 ) ? [ dimsB [ 0 ] , 1 ] : dimsB ; return [ a , b ] ; }
Fix the input shapes for MatMul operation if they need fixing
 @param dimsA The shape of tensor A.
Fix the input shapes for MatMul operation if they need fixing @param dimsA The shape of tensor A .
// If the first argument is 1-D, it is promoted to a matrix by prepending // a 1 to its dimensions. After matrix multiplication the prepended 1 is // removed. // If the second argument is 1-D, it is promoted to a matrix by appending // a 1 to its dimensions. After matrix multiplication the appended 1 is // removed.