fix bug of paddle.to_tensor and paddle.moveaxis (#39662)

* fix bug of paddle.to_tensor and paddle.moveaxis

* fix CI

Author: zhwesky2010

python/paddle/fluid/tests/unittests/test_transpose_op.py

@@ -423,6 +423,14 @@ def test_moveaxis2(self):
         self.assertEqual(np.array_equal(out.numpy(), expected), True)
         paddle.enable_static()
 
+    def test_moveaxis3(self):
+        paddle.disable_static()
+        x = paddle.to_tensor(
+            [[1 + 1j, -1 - 1j], [1 + 1j, -1 - 1j], [1 + 1j, -1 - 1j]])
+        out = x.moveaxis(0, 1)
+        self.assertEqual(out.shape, [2, 3])
+        paddle.enable_static()
+
     def test_error(self):
         x = paddle.randn([2, 3, 4, 5])
         # src must have the same number with dst

python/paddle/fluid/tests/unittests/test_var_base.py

@@ -51,6 +51,10 @@ def _test_place(place):
                     np.array_equal(x.numpy(), np.array([1.2], 'float16')))
                 self.assertEqual(x.dtype, core.VarDesc.VarType.FP16)
 
+                # set_default_dtype take effect on int
+                x = paddle.to_tensor(1, place=place)
+                self.assertTrue(x.dtype, core.VarDesc.VarType.INT64)
+
                 # set_default_dtype take effect on float
                 x = paddle.to_tensor(1.2, place=place, stop_gradient=False)
                 self.assertTrue(

python/paddle/tensor/creation.py

@@ -110,12 +110,6 @@ def to_tensor(data, dtype=None, place=None, stop_gradient=True):
             "'place' must be any of paddle.Place, paddle.CPUPlace, paddle.CUDAPinnedPlace, paddle.CUDAPlace, paddle.NPUPlace, paddle.XPUPlace, paddle.CustomPlace"
         )
 
-    #Todo(zhouwei): Support allocate tensor on any other specified card
-    if isinstance(place, core.CUDAPlace) and isinstance(
-            _current_expected_place(), core.CUDAPlace) and place._get_device_id(
-            ) != _current_expected_place()._get_device_id():
-        place = _current_expected_place()
-
     if not isinstance(data, np.ndarray):
 
         def _handle_dtype(data, dtype):
@@ -139,7 +133,7 @@ def _handle_dtype(data, dtype):
             data.stop_gradient = stop_gradient
             return data
         elif isinstance(data, (core.LoDTensor, core.Tensor)):
-            # Note(zhouwei25): should't expose it to users, just for internal use.
+            # should't expose it to users, just for internal use.
             # convert core.Tensor/core.LoDTensor to VarBase first
             # Currenly, there is no copy when places are same
             data = paddle.Tensor(data)
@@ -152,15 +146,20 @@ def _handle_dtype(data, dtype):
             raise TypeError(
                 "Can't constructs a 'paddle.Tensor' with data type {}, data type must be scalar|list|tuple|numpy.ndarray|paddle.Tensor".
                 format(type(data)))
-        if not dtype and data.dtype in [
-                'float16', 'float32', 'float64', 'complex64', 'complex128'
-        ]:
-            default_type = paddle.get_default_dtype()
-            if np.iscomplexobj(data):
-                default_type = 'complex64' if default_type in [
-                    'float16', 'float32'
-                ] else 'complex128'
-            data = data.astype(default_type)
+        if not dtype:
+            if data.dtype in [
+                    'float16', 'float32', 'float64', 'complex64', 'complex128'
+            ]:
+                default_type = paddle.get_default_dtype()
+                if np.iscomplexobj(data):
+                    default_type = 'complex64' if default_type in [
+                        'float16', 'float32'
+                    ] else 'complex128'
+                data = data.astype(default_type)
+            # Windows default type is 'int32', while Linux/Mac is 'int64'. Unify they.
+            if data.dtype in ['int32']:
+                default_type = "int64"
+                data = data.astype(default_type)
 
     if dtype and convert_dtype(dtype) != data.dtype:
         data = data.astype(convert_dtype(dtype))

python/paddle/tensor/manipulation.py

@@ -2737,9 +2737,10 @@ def moveaxis(x, source, destination, name=None):
         out, _ = _C_ops.transpose2(x, 'axis', perm)
         return out
 
-    check_variable_and_dtype(
-        x, 'x', ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'],
-        'moveaxis')
+    check_variable_and_dtype(x, 'x', [
+        'bool', 'float16', 'float32', 'float64', 'int32', 'int64', 'complex64',
+        'complex128'
+    ], 'moveaxis')
 
     helper = LayerHelper('moveaxis', **locals())
     out = helper.create_variable_for_type_inference(x.dtype)