code: def dilation2d(
      data,
      weight,
      strides=(1, 1),
      padding=(0, 0),
      dilations=(1, 1),
      data_layout="NCHW",
      kernel_layout="IHW",
      out_dtype="",
  ):
      r"""Morphological Dilation 2D.
      This operator takes the weight as the dilation kernel and dilates it with
      data to produce an output. In the default case, where the data_layout is `NCHW`
      and kernel_layout is `OIHW`, dilation2d takes in a data Tensor with shape
      `(batch_size, in_channels, height, width)`, and a weight Tensor with shape
      `(channels, kernel_height, kernel_width)` to produce an output Tensor
      with the following rule:
  
      .. math::
          \mbox{out}[b, c, y, x] = \max_{dy, dx}
             \mbox{data}[b, c, \mbox{strides}[0] * y  + dy, \mbox{strides}[1] * x + dx] +
             \mbox{weight}[c, dy, dx]
  
      Padding and dilation are applied to data and weight respectively before the computation.
      This operator accepts data layout specification. Semantically, the operator
      will convert the layout to the canonical layout
      (`NCHW` for data and `IHW` for weight) and perform the computation.
  
      weight : tvm.relay.Expr
          The weight expressions.
  
      strides : Optional[Tuple[int]]
          The strides of convolution.
  
      padding : Optional[Tuple[int]]
          The padding of convolution on both sides of inputs before convolution.
  
      dilations : Optional[Tuple[int]]
          Specifies the dilation rate to be used for dilated convolution.
  
      data_layout : Optional[str]
          Layout of the input.
  
      kernel_layout : Optional[str]
          Layout of the weight.
  
      out_dtype : Optional[str]
          Specifies the output data type.
  
      Returns
      -------
      result : tvm.relay.Expr
          The computed result.
      """
  
      return _make.dilation2d(
          data,
          weight,
          strides,
          padding,
          dilations,
          data_layout,
          kernel_layout,
          out_dtype,
      )
  
file_path: tvm/python/tvm/relay/op/image/image.py
imports: from .None import _make
  from ..dyn.image import _make
  from ...expr import Expr, Constant, const
label_desc: Use image node_id 5 for calling a global function with example usage: dilation2d(data, weight, strides, padding, dilations, data_layout, kernel_layout, out_dtype) and returns: _make