[Fix] Fixed compat.nn.functional import

Author: Enigmatisms

python/paddle/tensor/compat_softmax.py

@@ -30,7 +30,7 @@
 @ForbidKeywordsIgnoreOneParamDecorator(
     illegal_keys={"x", "axis", "name"},
     ignore_param=('_stacklevel', 2, int),
-    func_name="paddle.compat.softmax",
+    func_name="paddle.compat.nn.functional.softmax",
     correct_name="paddle.nn.functional.softmax",
 )
 def softmax(
@@ -41,7 +41,7 @@ def softmax(
     out: Tensor | None = None,
 ) -> Tensor:
     r"""
-    This operator implements the compat.softmax. The calculation process is as follows:
+    This operator implements PyTorch compatible softmax. The calculation process is as follows:
 
     1. The dimension :attr:`dim` of ``input`` will be permuted to the last.
 
@@ -139,8 +139,8 @@ def softmax(
             ...                       [[1.0, 2.0, 3.0, 4.0],
             ...                        [5.0, 6.0, 7.0, 8.0],
             ...                        [6.0, 7.0, 8.0, 9.0]]],dtype='float32')
-            >>> out1 = paddle.compat.softmax(x, -1)
-            >>> out2 = paddle.compat.softmax(x, -1, dtype='float64')
+            >>> out1 = paddle.compat.nn.functional.softmax(x, -1)
+            >>> out2 = paddle.compat.nn.functional.softmax(x, -1, dtype='float64')
             >>> #out1's data type is float32; out2's data type is float64
             >>> #out1 and out2's value is as follows:
             >>> print(out1)

test/legacy_test/test_softmax_op.py

@@ -804,7 +804,7 @@ def setUp(self):
     def test_static_check(self):
         with static_guard():
             for x_np, out_ref in zip(self.x_np_list, self.out_ref_list):
-                func = compat.softmax
+                func = compat.nn.functional.softmax
                 with paddle.static.program_guard(paddle.static.Program()):
                     x = paddle.static.data('X', x_np.shape, 'float32')
                     out1 = func(input=x, dim=None, _stacklevel=3)
@@ -854,7 +854,7 @@ def test_static_check(self):
     def test_dygraph_check(self):
         paddle.disable_static(self.place)
         for x_np, out_ref in zip(self.x_np_list, self.out_ref_list):
-            func = compat.softmax
+            func = compat.nn.functional.softmax
             x = paddle.to_tensor(x_np)
             out1 = func(input=x, dim=None, _stacklevel=3)
             x = paddle.to_tensor(x_np)
@@ -964,12 +964,18 @@ def test_forbid_keywords(self):
             paddle.static.program_guard(paddle.static.Program()),
         ):
             x = paddle.static.data('X', [2, 3], 'float32')
-            self.assertRaises(TypeError, compat.softmax, x=x, axis=-1)
-            self.assertRaises(TypeError, compat.softmax, x=x, dim=-1)
-            self.assertRaises(TypeError, compat.softmax, input=x, axis=-1)
+            self.assertRaises(
+                TypeError, compat.nn.functional.softmax, x=x, axis=-1
+            )
+            self.assertRaises(
+                TypeError, compat.nn.functional.softmax, x=x, dim=-1
+            )
+            self.assertRaises(
+                TypeError, compat.nn.functional.softmax, input=x, axis=-1
+            )
 
             if core.is_compiled_with_cuda() or is_custom_device():
-                compat.softmax(input=x, dim=-1)
+                compat.nn.functional.softmax(input=x, dim=-1)
 
 
 if __name__ == "__main__":