[API compatibility] paddle.nn.functional.one_hot (#74925)

* [API compatibility] one_hot

* fix

Author: DongBaiYue

python/paddle/nn/functional/input.py

@@ -30,9 +30,10 @@
 __all__ = []
 
 
+@param_one_alias(["x", "input"])
 def one_hot(
     x: Tensor,
-    num_classes: int,
+    num_classes: int = -1,
     name: str | None = None,
 ) -> Tensor:
     """
@@ -72,11 +73,17 @@ def one_hot(
             so it throws an exception.
 
 
+    .. note::
+        Alias Support: The parameter name ``input`` can be used as an alias for ``x``.
+        For example, ``one_hot(input=tensor_x, ...)`` is equivalent to ``one_hot(x=tensor_x, ...)``.
+
+
     Args:
         x(Tensor): Tensor with shape :math:`[N_1, N_2, ..., N_k]` ,
             which contains at least one dimension. The data type is int32 or int64.
+            alias: ``input``.
         num_classes(int): An integer defining the `num_classes` of the one hot dimension. If input `x`
-            is word id, `num_classes` is generally the dictionary size.
+            is word id, `num_classes` is generally the dictionary size. Default value: -1.
         name(str|None, optional): For detailed information, please refer
            to :ref:`api_guide_Name`. Usually name is no need to set and
            None by default.
@@ -103,7 +110,8 @@ def one_hot(
                     [1., 0., 0., 0.]])
 
     """
-
+    if not isinstance(num_classes, paddle.pir.Value) and num_classes == -1:
+        num_classes = x.max() + 1
     if in_dynamic_or_pir_mode():
         return _C_ops.one_hot(x, num_classes)
     else:

test/ir/pir/test_special_op_translator.py

@@ -264,48 +264,6 @@ def test_op(self):
             _ = pir.translate_to_pir(main_program.desc)
 
 
-class TestOneHotOpTranscriber(unittest.TestCase):
-    def test_mutable_attribute(self):
-        with paddle.pir_utils.OldIrGuard():
-            place = core.Place()
-            place.set_place(paddle.CPUPlace())
-            new_scope = paddle.static.Scope()
-            main_program = paddle.static.Program()
-            with (
-                paddle.static.scope_guard(new_scope),
-                paddle.static.program_guard(main_program),
-            ):
-                depth = paddle.assign(np.array([10], dtype=np.int32))
-                label = paddle.static.data(
-                    name="label", shape=[-1, 1], dtype="int64"
-                )
-                one_hot_label = paddle.nn.functional.one_hot(
-                    x=label, num_classes=depth
-                )
-
-            _ = pir.translate_to_pir(main_program.desc)
-
-    def test_normal_attribute(self):
-        with paddle.pir_utils.OldIrGuard():
-            place = core.Place()
-            place.set_place(paddle.CPUPlace())
-            new_scope = paddle.static.Scope()
-            main_program = paddle.static.Program()
-            with (
-                paddle.static.scope_guard(new_scope),
-                paddle.static.program_guard(main_program),
-            ):
-                depth = 10
-                label = paddle.static.data(
-                    name="label", shape=[-1, 1], dtype="int64"
-                )
-                one_hot_label = paddle.nn.functional.one_hot(
-                    x=label, num_classes=depth
-                )
-
-            _ = pir.translate_to_pir(main_program.desc)
-
-
 class TestReduceOpTranscriber(unittest.TestCase):
     def test_reduce_all(self):
         place = core.Place()

test/legacy_test/test_one_hot_v2_op.py

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from op_test import OpTest
+from op_test import OpTest, get_places
 
 import paddle
 from paddle import base
@@ -283,6 +283,70 @@ def test_check_output(self):
         self.check_output()
 
 
+class TestOneHotAPI_Compatibility(unittest.TestCase):
+    def setUp(self):
+        np.random.seed(123)
+        paddle.enable_static()
+        self.places = get_places()
+        self.shape = [5]
+        self.dtype = 'int32'
+        self.init_data()
+
+    def init_data(self):
+        self.np_input = np.random.randint(0, 8, self.shape).astype(self.dtype)
+        self.num_classes = self.np_input.max() + 1
+        self.np_out = np.eye(self.num_classes)[self.np_input]
+
+    def test_dygraph_Compatibility(self):
+        paddle.disable_static()
+        x = paddle.to_tensor(self.np_input)
+        paddle_dygraph_out = []
+        # Position args (args)
+        out1 = paddle.nn.functional.one_hot(x, self.num_classes)
+        paddle_dygraph_out.append(out1)
+        # Key words args (kwargs) for paddle
+        out2 = paddle.nn.functional.one_hot(x=x, num_classes=self.num_classes)
+        paddle_dygraph_out.append(out2)
+        # Key words args for torch
+        out3 = paddle.nn.functional.one_hot(
+            input=x, num_classes=self.num_classes
+        )
+        paddle_dygraph_out.append(out3)
+        # default args
+        out4 = paddle.nn.functional.one_hot(x, -1)
+        paddle_dygraph_out.append(out4)
+        # Check
+        for out in paddle_dygraph_out:
+            np.testing.assert_allclose(self.np_out, out.numpy())
+        paddle.enable_static()
+
+    def test_static_Compatibility(self):
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with base.program_guard(main, startup):
+            x = paddle.static.data(name="x", shape=self.shape, dtype=self.dtype)
+            # Position args (args)
+            out1 = paddle.nn.functional.one_hot(x, self.num_classes)
+            # Key words args (kwargs) for paddle
+            out2 = paddle.nn.functional.one_hot(
+                x=x, num_classes=self.num_classes
+            )
+            # Key words args for torch
+            out3 = paddle.nn.functional.one_hot(
+                input=x, num_classes=self.num_classes
+            )
+            # default args
+            out4 = paddle.nn.functional.one_hot(x, -1)
+            exe = base.Executor(paddle.CPUPlace())
+            fetches = exe.run(
+                main,
+                feed={"x": self.np_input},
+                fetch_list=[out1, out2, out3],
+            )
+            for out in fetches:
+                np.testing.assert_allclose(out, self.np_out)
+
+
 if __name__ == '__main__':
     paddle.enable_static()
     unittest.main()