function computeDilation2DInfo(inputShape, filterShape, strides, pad, dataFormat, dilations) {
	  if (dataFormat === void 0) {
	    dataFormat = 'NHWC';
	  }

	  // `computerConv2DInfo` require filterShape to be in the dimension of:
	  // `[filterHeight, filterWidth, depth, outDepth]`, dilation2d doesn't have
	  // outDepth, it should have the same depth as the input.
	  // Input shape: [batch, height, width, inChannels]
	  var inputChannels = inputShape[3];
	  var $filterShape = [].concat(filterShape, [inputChannels]);
	  var $dataFormat = convertConv2DDataFormat(dataFormat);
	  return computeConv2DInfo(inputShape, $filterShape, strides, dilations, pad, null
	  /* roundingMode */
	  , null
	  /* depthWise */
	  , $dataFormat);
	}
@param inputShape Input tensor shape is of the following dimensions:
    `[batch, height, width, inChannels]`.
@param filterShape The filter shape is of the following dimensions:
    `[filterHeight, filterWidth, depth]`.
@param strides The strides of the sliding window for each dimension of the
    input tensor: `[strideHeight, strideWidth]`.
    If `strides` is a single number,
    then `strideHeight == strideWidth`.
@param pad The type of padding algorithm.
   - `same` and stride 1: output will be of same size as input,
      regardless of filter size.
   - `valid`: output will be smaller than input if filter is larger
      than 1*1x1.
   - For more info, see this guide:
    [https://www.tensorflow.org/api_guides/python/nn#Convolution](
         https://www.tensorflow.org/api_guides/python/nn#Convolution)
@param dataFormat The data format of the input and output data.
    Defaults to 'NHWC'.
@param dilations The dilation rates: `[dilationHeight, dilationWidth]`.
    Defaults to `[1, 1]`. If `dilations` is a single number, then
    `dilationHeight == dilationWidth`.