[GitHub] [tvm] manupa-arm commented on a change in pull request #9164: Enable for qnn operations for const folding transformation

[GitBox <gi...@apache.org>]

manupa-arm commented on a change in pull request #9164:
URL: https://github.com/apache/tvm/pull/9164#discussion_r720008049



##########
File path: tests/python/relay/test_pass_fold_constant.py
##########
@@ -298,6 +298,31 @@ def before():
     assert tvm.ir.structural_equal(run_infer_type(before_mod["main"]), after_mod["main"])
 
 
+def test_fold_qnn_quantize():
+    t = relay.TensorType([1, 2, 3], "int8")
+
+    def before():
+        data = tvm.nd.array(np.array([1.0, 2.0, 3.0], dtype="float32"))
+        const_fp = relay.const(data, dtype="float32")
+        const_i8 = relay.qnn.op.quantize(const_fp, output_scale=relay.const(0.5), output_zero_point=relay.const(0))
+        x = relay.var("x", t)
+        add = relay.op.add(x, const_i8)
+        func = relay.Function([x], add)
+        return func
+
+    def expected():
+        data = tvm.nd.array(np.array([2, 4, 6], dtype="int8"))
+        const_i8 = relay.const(data, dtype="int8")
+        x = relay.var("x", t)
+        add = relay.op.add(x, const_i8)
+        func = relay.Function([x], add)
+        return func
+
+    zz = run_opt_pass(before(), transform.FoldConstant())

Review comment:
       How is it different from running Legalize followed by FoldConstant ?




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