static computeConvOutputShape(inputDims, filterDims, strides, dilations, kernelShape, pads, autoPad) {
        if (inputDims.length <= 0 || filterDims.length <= 0) {
            throw new Error('invalid input tensor dims or invalid filter tensor dims');
        }
        // Add batch size and number of channels of output
        const outputDims = [inputDims[0], filterDims[0]];
        PoolConvUtil.computeShapeHelper(false, inputDims, outputDims, strides, dilations, kernelShape, pads, autoPad);
        return outputDims;
    }
/**
     * Calculate the output shape for Conv op based on input attributes. (Should be used only for Conv op)
     * @param inputDims The input tensor dimension. (inputs[0].dims)
     * @param filterDims The filter tensor dimension. (inputs[1].dims)
     * @param strides Stride along each axis.
     * @param kernelShape The size of the kernel along each axis.
     * @param pads Padding for the beginning and ending along each axis.
     * @param autoPad DEPRECATED attribute supported for legacy models. Specifies how to implicitly calculate pads in each
     *     dimension. Can take values NOTSET, SAME_UPPER, SAME_LOWER, or VALID.
     */
Calculate the output shape for Conv op based on input attributes. (Should be used only for Conv op)
@param inputDims The input tensor dimension. (inputs[0].dims)
@param filterDims The filter tensor dimension. (inputs[1].dims)
@param strides Stride along each axis.
@param kernelShape The size of the kernel along each axis.
@param pads Padding for the beginning and ending along each axis.
@param autoPad DEPRECATED attribute supported for legacy models. Specifies how to implicitly calculate pads in each
dimension. Can take values NOTSET, SAME_UPPER, SAME_LOWER, or VALID.
Calculate the output shape for Conv op based on input attributes . ( Should be used only for Conv op ) @param inputDims The input tensor dimension . ( inputs [ 0 ] . dims ) @param filterDims The filter tensor dimension . ( inputs [ 1 ] . dims ) @param strides Stride along each axis . @param kernelShape The size of the kernel along each axis . @param pads Padding for the beginning and ending along each axis . @param autoPad DEPRECATED attribute supported for legacy models . Specifies how to implicitly calculate pads in each dimension . Can take values NOTSET SAME_UPPER SAME_LOWER or VALID .
static computeConvOutputShape(inputDims, filterDims, strides, dilations, kernelShape, pads, autoPad) {
        if (inputDims.length <= 0 || filterDims.length <= 0) {
            throw new Error('invalid input tensor dims or invalid filter tensor dims');
        }
        const outputDims = [inputDims[0], filterDims[0]];
        PoolConvUtil.computeShapeHelper(false, inputDims, outputDims, strides, dilations, kernelShape, pads, autoPad);
        return outputDims;
    }
static computeConvOutputShape ( inputDims , filterDims , strides , dilations , kernelShape , pads , autoPad ) { if ( inputDims . length <= 0 || filterDims . length <= 0 ) { throw new Error ( 'invalid input tensor dims or invalid filter tensor dims' ) ; } const outputDims = [ inputDims [ 0 ] , filterDims [ 0 ] ] ; PoolConvUtil . computeShapeHelper ( false , inputDims , outputDims , strides , dilations , kernelShape , pads , autoPad ) ; return outputDims ; }
Calculate the output shape for Conv op based on input attributes.
Calculate the output shape for Conv op based on input attributes .
// Add batch size and number of channels of output