48 bool canMatrixMul(uint32_t LHSRow, uint32_t LHSCol, uint32_t RHSRow, uint32_t RHSCol, bool adjX,  in canMatrixMul()  argument
53     if (adjX) {  in canMatrixMul()
64                                               const Shape& RHSTensorShape, bool adjX, bool adjY) {  in computeOutputDimensions()  argument
68             adjX ? LHSTensorShape.dimensions[numDims - 1] : LHSTensorShape.dimensions[numDims - 2];  in computeOutputDimensions()
117                         const Shape& inputRHSShape, const bool adjX, const bool adjY, T* outputData,  in batchMatMulGeneric()  argument
133     if (adjX) {  in batchMatMulGeneric()
141     Shape realInputLHSShape = adjX ? inputLHSShape : swapRowColumnDims(inputLHSShape);  in batchMatMulGeneric()
153                           const Shape& inputRHSShape, const bool adjX, const bool adjY,  in batchMatMulQuantized()  argument
161     if (adjX) {  in batchMatMulQuantized()
169     Shape realInputLHSShape = adjX ? inputLHSShape : swapRowColumnDims(inputLHSShape);  in batchMatMulQuantized()
214     const bool adjX = context->getInputValue<bool>(kInputLHSAdj);  in prepare()  local
220                               getSizeOfDimension(inputRHSTensorShape, numDims - 1), adjX, adjY))  in prepare()
225             computeOutputDimensions(inputLHSTensorShape, inputRHSTensorShape, adjX, adjY);  in prepare()