【BugFix】fix err of api `to_tensor`, which caused by numpy version update (#53534)

* fix

* update code

* pre-commit

* remove scale check (0-D tensor is usable)

* fix data dtype err

* fix numpy default dtype diff

* fix data dtype

* fix data dtype

* update

* fix coverage

python/paddle/tensor/creation.py

@@ -646,8 +646,10 @@ def _to_tensor_non_static(data, dtype=None, place=None, stop_gradient=True):
 
 def _to_tensor_static(data, dtype=None, stop_gradient=None):
 
-    if isinstance(data, Variable) and (dtype is None or dtype == data.dtype):
+    if isinstance(data, Variable):
         output = data
+        if dtype is not None and dtype != data.dtype:
+            output = paddle.cast(output, dtype)
     else:
         if isinstance(data, np.number):  # Special case for numpy scalars
             data = np.array(data)
@@ -656,17 +658,37 @@ def _to_tensor_static(data, dtype=None, stop_gradient=None):
             if np.isscalar(data) and not isinstance(data, str):
                 data = np.array(data)
             elif isinstance(data, (list, tuple)):
-                data = np.array(data)
+                try:
+                    '''
+                    In numpy version >= 1.24.0, case like:
+                        np.array([Variable, 1, 2])
+                    is not supported, it will raise error (numpy returns an numpy array with dtype='object' in version <= 1.23.5)
+
+                    Thus, process nested structure in except block
+                    '''
+                    data = np.array(data)
+
+                    # for numpy version <= 1.23.5
+                    if data.dtype == 'object':
+                        raise RuntimeError("Numpy get dtype `object`.")
+
+                except:
+                    to_stack_list = [None] * len(data)
+                    for idx, d in enumerate(data):
+                        to_stack_list[idx] = _to_tensor_static(
+                            d, dtype, stop_gradient
+                        )
+                    data = paddle.stack(to_stack_list)
+                    data = paddle.squeeze(data, -1)
 
-            if (
-                isinstance(data, np.ndarray)
-                and not dtype
-                and data.dtype != 'object'
-            ):
-                if data.dtype in ['float16', 'float32', 'float64']:
-                    data = data.astype(paddle.get_default_dtype())
-                elif data.dtype in ['int32']:
-                    data = data.astype('int64')
+            else:
+                raise RuntimeError(
+                    f"Do not support transform type `{type(data)}` to tensor"
+                )
+
+            # fix numpy default dtype
+            if data.dtype in ['float16', 'float32', 'float64']:
+                data = data.astype(paddle.get_default_dtype())
 
         if dtype:
             target_dtype = dtype
@@ -674,24 +696,10 @@ def _to_tensor_static(data, dtype=None, stop_gradient=None):
             target_dtype = data.dtype
         else:
             target_dtype = paddle.get_default_dtype()
-
         target_dtype = convert_dtype(target_dtype)
 
-        if (
-            isinstance(data, np.ndarray)
-            and len(data.shape) > 0
-            and any(isinstance(x, Variable) for x in data)
-        ):
-            to_stack_list = [None] * data.shape[0]
-            for idx, d in enumerate(data):
-                to_stack_list[idx] = _to_tensor_static(d, dtype, stop_gradient)
-            data = paddle.stack(to_stack_list)
-            data = paddle.squeeze(data, -1)
-
-        if not isinstance(data, Variable):
-            output = assign(data)
-        else:
-            output = data
+        output = assign(data)
+
         if convert_dtype(output.dtype) != target_dtype:
             output = paddle.cast(output, target_dtype)
 

test/dygraph_to_static/test_to_tensor.py

@@ -90,6 +90,11 @@ def case7(x):
     return a
 
 
+def case8(x):
+    a = paddle.to_tensor({1: 1})
+    return a
+
+
 class TestToTensorReturnVal(unittest.TestCase):
     def test_to_tensor_badreturn(self):
         paddle.disable_static()
@@ -143,6 +148,17 @@ class TestToTensorReturnVal(unittest.TestCase):
         self.assertTrue(a.stop_gradient == b.stop_gradient)
         self.assertTrue(a.place._equals(b.place))
 
+    def test_to_tensor_err_log(self):
+        paddle.disable_static()
+        x = paddle.to_tensor([3])
+        try:
+            a = paddle.jit.to_static(case8)(x)
+        except Exception as e:
+            self.assertTrue(
+                "Do not support transform type `<class 'dict'>` to tensor"
+                in str(e)
+            )
+
 
 class TestStatic(unittest.TestCase):
     def test_static(self):