[Dy2St] Fix NameloadJstTransformer missing transform call kwargs

python/paddle/base/dygraph/math_op_patch.py

@@ -167,9 +167,7 @@ def _size_(var):
     def _T_(var):
         if len(var.shape) == 1:
             return var
-        perm = []
-        for i in range(len(var.shape)):
-            perm.insert(0, i)
+        perm = list(reversed(range(len(var.shape))))
         out = _C_ops.transpose(var, perm)
         return out
 

python/paddle/jit/dy2static/transformers/basic_api_transformer.py

@@ -152,6 +152,8 @@ def visit_Call(self, node):
         Can't convert name of function call, bacause this will affect CallTransformer.
         """
         node.args = [self.visit(arg) for arg in node.args]
+        for keyword in node.keywords:
+            keyword.value = self.visit(keyword.value)
         node.func = self.visit(node.func)
         return node
 

python/paddle/pir/math_op_patch.py

@@ -405,6 +405,35 @@ def _size_(self):
         """
         return paddle.numel(self)
 
+    @property
+    def _T_(self):
+        """
+
+        Permute current Value with its dimensions reversed.
+
+        If `n` is the dimensions of `x` , `x.T` is equivalent to `x.transpose([n-1, n-2, ..., 0])`.
+
+        Examples:
+            .. code-block:: python
+
+                >>> import paddle
+                >>> paddle.enable_static()
+
+                >>> x = paddle.ones(shape=[2, 3, 5])
+                >>> x_T = x.T
+
+                >>> exe = paddle.static.Executor()
+                >>> x_T_np = exe.run(paddle.static.default_main_program(), fetch_list=[x_T])[0]
+                >>> print(x_T_np.shape)
+                (5, 3, 2)
+
+        """
+        if len(self.shape) == 1:
+            return self
+        perm = list(reversed(range(len(self.shape))))
+
+        return _C_ops.transpose(self, perm)
+
     def clone(self):
         """
         Returns a new static Value, which is the clone of the original static
@@ -511,6 +540,7 @@ def value_hash(self):
         ('ndim', _ndim),
         ('astype', astype),
         ('size', _size_),
+        ('T', _T_),
         ('clone', clone),
         ('clear_gradient', clear_gradient),
         ('append', append),

test/dygraph_to_static/test_load_transformer.py

@@ -71,5 +71,27 @@ def func(x):
         np.testing.assert_allclose(output_dy.numpy(), output_st.numpy())
 
 
+class LoadInCallKwargsNet(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.extra_inputs = []
+
+    def forward(self, x):
+        for i in range(len(self.extra_inputs)):
+            x = paddle.nn.functional.linear(weight=self.extra_inputs[i].T, x=x)
+        return x
+
+
+class TestLoadInCallKwargs(Dy2StTestBase):
+    @test_legacy_and_pt_and_pir
+    def test_name_load_nograd(self):
+        net = LoadInCallKwargsNet()
+        x = paddle.rand([10, 10])
+        net.extra_inputs.append(paddle.rand([10, 10]))
+        output_st = paddle.jit.to_static(net)(x)
+        output_dy = net(x)
+        np.testing.assert_allclose(output_dy.numpy(), output_st.numpy())
+
+
 if __name__ == "__main__":
     unittest.main()

test/legacy_test/test_math_op_patch_pir.py

@@ -450,6 +450,20 @@ def test_size(self):
                 (output_x,) = exe.run(main_program, fetch_list=[x.size])
                 self.assertEqual(output_x, 24)
 
+    def test_T(self):
+        with paddle.pir_utils.IrGuard():
+            for ndim in range(5):
+                # shape is [], [1], [1, 2], [1, 2, 3], [1, 2, 3, 4]
+                shape = list(range(1, ndim + 1))
+                out_shape = list(reversed(shape))
+                main_program, exe, program_guard = new_program()
+                with program_guard:
+                    x = paddle.rand(shape, dtype="float32")
+                    x_T = x.T
+                    self.assertEqual(x_T.shape, out_shape)
+                    (output_x,) = exe.run(main_program, fetch_list=[x_T])
+                    self.assertEqual(output_x.shape, tuple(out_shape))
+
     def test_hash_error(self):
         with paddle.pir_utils.IrGuard():
             _, _, program_guard = new_program()