sjain58 opened a new pull request, #15806:
URL: https://github.com/apache/tvm/pull/15806

   In Mobilenet float32, we see this sequence of ops:
   
   %179 = squeeze(%178, axis=[2, 3]) /* ty=Tensor[(1, 1001), float16] 
span=MobilenetEdgeTPU/Logits/Squeeze:0:0 /;
   %180 = reshape(%179, newshape=[-1, 1001]) / ty=Tensor[(1, 1001), float16] 
span=MobilenetEdgeTPU/Predictions/
   Reshape:0:0 */;
   
   which later gets transformed to
   
   lv171 = R.call_tir(cls.primfunc_hmx_conv2d26_add20, (lv169, 
metadata["relax.expr.Constant"][116], metadata["relax.expr.Constant"][117]), 
out_sinfo=R.Tensor((1, 1001, 1, 1), dtype="float16"))
   lv172: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv171, R.shape([1, 
1001]))
   lv173: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv172, R.shape([1, 
1001]))
   
   We can eliminate the redundant reshape.
   
   lv171 = R.call_tir(cls.primfunc_hmx_conv2d26_add20, (lv169, 
metadata["relax.expr.Constant"][116], metadata["relax.expr.Constant"][117]), 
out_sinfo=R.Tensor((1, 1001, 1, 1), dtype="float16"))
   lv173: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv171, R.shape([1, 
1001]))


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