[QNN] Change default rouning to UPWARD. (#4131)

include/tvm/relay/qnn/attrs.h

@@ -49,7 +49,7 @@ struct RequantizeAttrs : public tvm::AttrsNode<RequantizeAttrs> {
         .describe("The scale of the output tensor.");
     TVM_ATTR_FIELD(output_zero_point)
         .describe("The zero point of the output tensor.");
-    TVM_ATTR_FIELD(rounding).set_default("TONEAREST")
+    TVM_ATTR_FIELD(rounding).set_default("UPWARD")
         .describe("Defines the rounding direction when the value is midway between"
                   "two representable values. There are two supported modes - UPWARD"
                   "or TONEAREST. Both modes behave exactly same except at the"

python/tvm/relay/qnn/op/qnn.py

@@ -27,7 +27,7 @@ def requantize(data,
                input_zero_point,
                output_scale,
                output_zero_point,
-               rounding="TONEAREST",
+               rounding="UPWARD",
                out_dtype="int8"):
     r"""Requantized operator.
 

src/relay/qnn/util.h

@@ -76,7 +76,7 @@ Expr RequantizeLower(const Expr& input_tensor, const RequantizeAttrs* param,
 static inline Expr Requantize(const Expr& data, const Array<IndexExpr>& input_shape,
                               double input_scale, int32_t input_zero_point, double output_scale,
                               int32_t output_zero_point, const DataType& out_dtype,
-                              const std::string& rounding = "TONEAREST") {
+                              const std::string& rounding = "UPWARD") {
   auto attrs = make_node<RequantizeAttrs>();
   attrs->input_scale = std::move(input_scale);
   attrs->input_zero_point = std::move(input_zero_point);