[UX][TVMScript] Overload __neg__ for relax expr (#434)

This PR overloads `__neg__` given that `relax.negative` is now supported and adds corresponding tests.

python/tvm/relax/expr.py

@@ -125,7 +125,7 @@ def astype(self, dtype: Union[str, DataType]) -> "ExprWithOp":
         return _op_ffi_api.astype(self, dtype)  # type: ignore
 
     def __neg__(self) -> "ExprWithOp":
-        raise ValueError("relax.negative is not supported yet.")
+        return _op_ffi_api.negative(self)  # type: ignore
 
     def __lt__(self, other: Expr) -> "ExprWithOp":
         return _binary_op_helper(self, other, _op_ffi_api.less)  # type: ignore

tests/python/relax/test_op.py

@@ -62,6 +62,7 @@ def _check_call(expr, op_name: str):
     _check_call(x <= y, "less_equal")
 
     # Arithmetic operators
+    _check_call(-x, "negative")
     _check_call(x + y, "add")
     _check_call(x - y, "subtract")
     _check_call(x * y, "multiply")

tests/python/relax/test_tvmscript_parser.py

@@ -883,11 +883,12 @@ def foo(x: R.Tensor(("m + 1", "m * 2"), "float32")):  # name 'm' is not defined
 def test_arith_operators():
     @R.function
     def foo(x: R.Tensor(("m", "n"), "float32"), y: R.Tensor(("m", "n"), "float32")):
-        a0 = x + y
-        a1 = x - y
-        a2 = x * y
-        a3 = x / y
-        a4 = x // y
+        a0 = -x
+        a1 = x + y
+        a2 = x - y
+        a3 = x * y
+        a4 = x / y
+        a5 = x // y
 
         c0 = x > y
         c1 = x < y
@@ -898,19 +899,20 @@ def foo(x: R.Tensor(("m", "n"), "float32"), y: R.Tensor(("m", "n"), "float32")):
         t0 = tuple_expr[0]
         t1 = tuple_expr[1]
         t2 = tuple_expr[0][0]  # <= Will normalize to two bindings
-        return a0, a1, a2, a3, a4, c0, c1, c2, c3, t0, t1, t2
+        return a0, a1, a2, a3, a4, a5, c0, c1, c2, c3, t0, t1, t2
 
     m = tir.Var("m", "int64")
     n = tir.Var("n", "int64")
     x = relax.Var("x", relax.TensorStructInfo([m, n], "float32"))
     y = relax.Var("y", relax.TensorStructInfo([m, n], "float32"))
     bb = relax.BlockBuilder()
     with bb.function("foo", (x, y)):
-        a0 = bb.emit(relax.op.add(x, y))
-        a1 = bb.emit(relax.op.subtract(x, y))
-        a2 = bb.emit(relax.op.multiply(x, y))
-        a3 = bb.emit(relax.op.divide(x, y))
-        a4 = bb.emit(relax.op.floor_divide(x, y))
+        a0 = bb.emit(relax.op.negative(x))
+        a1 = bb.emit(relax.op.add(x, y))
+        a2 = bb.emit(relax.op.subtract(x, y))
+        a3 = bb.emit(relax.op.multiply(x, y))
+        a4 = bb.emit(relax.op.divide(x, y))
+        a5 = bb.emit(relax.op.floor_divide(x, y))
 
         c0 = bb.emit(relax.op.greater(x, y))
         c1 = bb.emit(relax.op.less(x, y))
@@ -922,7 +924,7 @@ def foo(x: R.Tensor(("m", "n"), "float32"), y: R.Tensor(("m", "n"), "float32")):
         t1 = bb.emit(relax.TupleGetItem(tuple_expr, 1))
         tmp = bb.emit(relax.TupleGetItem(tuple_expr, 0))
         t2 = bb.emit(relax.TupleGetItem(tmp, 0))
-        bb.emit_func_output(relax.Tuple((a0, a1, a2, a3, a4, c0, c1, c2, c3, t0, t1, t2)))
+        bb.emit_func_output(relax.Tuple((a0, a1, a2, a3, a4, a5, c0, c1, c2, c3, t0, t1, t2)))
 
     _check(foo, bb.get()["foo"])