【SCU】【Paddle Tensor No.5】新增 Tensor.__rand__，复用已有接口Tensor.__and__

python/paddle/tensor/__init__.py

@@ -104,6 +104,7 @@
     transpose_,
 )
 from .logic import (  # noqa: F401
+    __rand__,
     allclose,
     bitwise_and,
     bitwise_and_,
@@ -862,6 +863,7 @@
 # this list used in math_op_patch.py for magic_method bind
 magic_method_func = [
     ('__and__', 'bitwise_and'),
+    ('__rand__', '__rand__'),
     ('__or__', 'bitwise_or'),
     ('__xor__', 'bitwise_xor'),
     ('__invert__', 'bitwise_not'),

python/paddle/tensor/logic.py

@@ -1231,6 +1231,16 @@ def bitwise_and(
     )
 
 
+def __rand__(x: Tensor, y: int | bool):
+    if isinstance(y, (int, bool)):
+        y_tensor = paddle.to_tensor(y, dtype=x.dtype)
+        return bitwise_and(y_tensor, x, None, None)
+    else:
+        raise TypeError(
+            f"unsupported operand type(s) for |: '{type(y).__name__}' and 'Tensor'"
+        )
+
+
 @inplace_apis_in_dygraph_only
 def bitwise_and_(x: Tensor, y: Tensor, name: str | None = None) -> Tensor:
     r"""

python/paddle/tensor/tensor.prototype.pyi

@@ -181,6 +181,7 @@ class AbstractTensor:
     def __rpow__(self, y: _typing.TensorLike) -> Tensor: ...  # type: ignore
     def __rdiv__(self, y: _typing.TensorLike) -> Tensor: ...  # type: ignore
     def __rfloordiv__(self, y: _typing.TensorLike) -> Tensor: ...  # type: ignore
+    def __rand__(self, y: _typing.TensorLike) -> Tensor: ...  # type: ignore
 
     # type cast
     def __bool__(self) -> bool: ...

test/legacy_test/test_math_op_patch.py

@@ -299,21 +299,23 @@ def test_astype(self):
         np.testing.assert_allclose(a_np.astype('float32'), b_np, rtol=1e-05)
 
     def test_bitwise_and(self):
+        temp = 2
         x_np = np.random.randint(-100, 100, [2, 3, 5]).astype("int32")
         y_np = np.random.randint(-100, 100, [2, 3, 5]).astype("int32")
         out_np = x_np & y_np
-
+        e_np = temp & x_np
         x = paddle.static.data(name="x", shape=[2, 3, 5], dtype="int32")
         y = paddle.static.data(name="y", shape=[2, 3, 5], dtype="int32")
         z = x & y
-
+        e = temp & x
         exe = base.Executor()
-        out = exe.run(
+        (out, e_out) = exe.run(
             base.default_main_program(),
             feed={"x": x_np, "y": y_np},
-            fetch_list=[z],
+            fetch_list=[z, e],
         )
-        np.testing.assert_array_equal(out[0], out_np)
+        np.testing.assert_array_equal(out, out_np)
+        np.testing.assert_array_equal(e_out, e_np)
 
     @prog_scope()
     def test_bitwise_or(self):

test/legacy_test/test_math_op_patch_pir.py

@@ -260,6 +260,8 @@ def test_bitwise_and(self):
             paddle.to_tensor(x_np), paddle.to_tensor(y_np)
         )
         res_np_d = x_np.__and__(y_np)
+        temp = 2
+        res_np_e = temp & y_np
         paddle.enable_static()
         with paddle.pir_utils.IrGuard():
             main_program, exe, program_guard = new_program()
@@ -269,14 +271,16 @@ def test_bitwise_and(self):
                 b = x & y
                 c = x.bitwise_and(y)
                 d = x.__and__(y)
-                (b_np, c_np, d_np) = exe.run(
+                e = temp & y
+                (b_np, c_np, d_np, e_np) = exe.run(
                     main_program,
                     feed={"x": x_np, "y": y_np},
-                    fetch_list=[b, c, d],
+                    fetch_list=[b, c, d, e],
                 )
                 np.testing.assert_array_equal(res_np_b, b_np)
                 np.testing.assert_array_equal(res_np_c, c_np)
                 np.testing.assert_array_equal(res_np_d, d_np)
+                np.testing.assert_array_equal(res_np_e, e_np)
 
     def test_positive(self):
         paddle.disable_static()