code: def correlation_nchw(
      cfg,
      data1,
      data2,
      kernel_size,
      max_displacement,
      stride1,
      stride2,
      padding,
      is_multiply,
  ):
      """Correlation operator in NCHW layout.
  
      Parameters
      ----------
      data1 : tvm.te.Tensor
          4-D with shape [batch, channel, height, width]
  
      data2 : tvm.te.Tensor
          4-D with shape [batch, channel, height, width]
  
      kernel_size: int
          Kernel size for correlation, must be an odd number
  
      max_displacement: int
          Max displacement of Correlation
  
      stride1: int
          Stride for data1
  
      stride2: int
          Stride for data2 within the neightborhood centered around data1
  
      padding : int or a list/tuple of 2 or 4 ints
          Padding size, or
          [pad_height, pad_width] for 2 ints, or
          [pad_top, pad_left, pad_bottom, pad_right] for 4 ints
  
      is_multiply: bocorrelation
          operation type is either multiplication or substraction
  
      Returns
      -------
      Output : tvm.te.Tensor
          4-D with shape [batch, out_channel, out_height, out_width]
      """
      # pylint: disable=unused-argument
      return nn.correlation_nchw(
          data1,
          data2,
          kernel_size,
          max_displacement,
          stride1,
          stride2,
          padding,
          is_multiply,
      )
  
file_path: tvm/python/tvm/topi/cuda/correlation.py
imports: import tvm
  from tvm import te
  from tvm import autotvm
  from ..None import nn
  from ..utils import traverse_inline
label_desc: Use image node_id 1 for calling a global function with example usage: correlation_nchw(cfg, data1, data2, kernel_size, max_displacement, stride1, stride2, padding, is_multiply) and returns: nn