code: def compute_conv(data, weight):
      N, IC, H, W = data.shape
      OC, IC, KH, KW = weight.shape
      OH = H - KH + 1
      OW = W - KW + 1
  
      ic = te.reduce_axis((0, IC), name="ic")
      dh = te.reduce_axis((0, KH), name="dh")
      dw = te.reduce_axis((0, KW), name="dw")
  
      return te.compute(
          (N, OC, OH, OW),
          lambda i, oc, h, w: te.sum(
              data[i, ic, h + dh, w + dw] * weight[oc, ic, dh, dw],
              axis=[ic, dh, dw],
          ),
      )
  
file_path: tvm/tests/python/te/test_te_tag.py
imports: import json
  import tvm
  from tvm import te
  from tvm import te
label_desc: Use image node_id 1 for calling a global function with example usage: compute_conv(data, weight) and returns: te