[Cleanup][B-7] clean some to_variable for test

test/dygraph_to_static/test_for_enumerate.py

@@ -24,14 +24,13 @@
 )
 
 import paddle
-from paddle import base
 from paddle.static import InputSpec
 
 
 # 0. for in range var.numpy()[0]
 def for_in_range(x):
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x = base.dygraph.to_variable(x)
+    x = paddle.to_tensor(x)
     for i in range(x.numpy().item()):
         z = z + i
     return z
@@ -56,7 +55,7 @@ def for_enumerate_list(x_array):
 # 3. for iter var.numpy()
 def for_iter_var_numpy(x_array):
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for x in x_array.numpy():
         z = z + x
     return z
@@ -66,7 +65,7 @@ def for_iter_var_numpy(x_array):
 def for_enumerate_var_numpy(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy()):
         y = y + i
         z = z + x
@@ -77,7 +76,7 @@ def for_enumerate_var_numpy(x_array):
 def for_enumerate_var_numpy_with_start(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy(), 1):
         y = y + i
         z = z + x
@@ -87,7 +86,7 @@ def for_enumerate_var_numpy_with_start(x_array):
 # 6. for in range with break
 def for_in_range_with_break(x):
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x = base.dygraph.to_variable(x)
+    x = paddle.to_tensor(x)
     for i in range(x.numpy()[0]):
         z = z + i
         if i > 2:
@@ -99,7 +98,7 @@ def for_in_range_with_break(x):
 def for_enumerate_var_numpy_with_break(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy()):
         y = y + i
         z = z + x
@@ -112,7 +111,7 @@ def for_enumerate_var_numpy_with_break(x_array):
 def for_enumerate_var_numpy_with_continue(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy()):
         y = y + i
         if i > 2:
@@ -125,7 +124,7 @@ def for_enumerate_var_numpy_with_continue(x_array):
 def for_enumerate_var_numpy_with_start_break(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy(), 1):
         y = y + i
         z = z + x
@@ -138,7 +137,7 @@ def for_enumerate_var_numpy_with_start_break(x_array):
 def for_enumerate_var_numpy_with_start_continue(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array.numpy(), 1):
         y = y + i
         if i > 2:
@@ -150,7 +149,7 @@ def for_enumerate_var_numpy_with_start_continue(x_array):
 # 11. for iter var
 def for_iter_var(x_array):
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
 
     for x in x_array:
         z = z + x
@@ -161,7 +160,7 @@ def for_iter_var(x_array):
 def for_enumerate_var(x_array):
     y = paddle.tensor.fill_constant([1], 'int32', 0)
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, x in enumerate(x_array):
         y = y + i
         z = z + x
@@ -171,7 +170,7 @@ def for_enumerate_var(x_array):
 # 13. for iter list[var]
 def for_iter_var_list(x):
     # 1. prepare data, ref test_list.py
-    x = base.dygraph.to_variable(x)
+    x = paddle.to_tensor(x)
     iter_num = paddle.tensor.fill_constant(shape=[1], value=5, dtype="int32")
     a = []
     for i in range(iter_num):
@@ -186,7 +185,7 @@ def for_iter_var_list(x):
 # 14. for enumerate list[var]
 def for_enumerate_var_list(x):
     # 1. prepare data, ref test_list.py
-    x = base.dygraph.to_variable(x)
+    x = paddle.to_tensor(x)
     iter_num = paddle.tensor.fill_constant(shape=[1], value=5, dtype="int32")
     a = []
     for i in range(iter_num):
@@ -203,7 +202,7 @@ def for_enumerate_var_list(x):
 # 15. for enumerate list[var] with a nested for range
 def for_enumerate_var_with_nested_range(x_array):
     x = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
     for i, num in enumerate(x_array):
         for idx in range(num):
             x = x + num
@@ -213,7 +212,7 @@ def for_enumerate_var_with_nested_range(x_array):
 # 16. for iter var[idx]
 def for_iter_var_idx(x_array):
     z = paddle.tensor.fill_constant([1], 'int32', 0)
-    x_array = base.dygraph.to_variable(x_array)
+    x_array = paddle.to_tensor(x_array)
 
     for x in x_array[0:]:
         z = z + x

test/legacy_test/test_elementwise_pow_op.py

@@ -230,8 +230,8 @@ def test_grad(self):
             places.append(base.CUDAPlace(0))
         for place in places:
             with base.dygraph.guard(place):
-                x = base.dygraph.to_variable(self.x, zero_copy=False)
-                y = base.dygraph.to_variable(self.y, zero_copy=False)
+                x = paddle.to_tensor(self.x, zero_copy=False)
+                y = paddle.to_tensor(self.y, zero_copy=False)
                 x.stop_gradient = False
                 y.stop_gradient = False
                 res = x**y

test/legacy_test/test_elementwise_sub_op.py

@@ -930,8 +930,8 @@ def test_dygraph(self):
         with base.dygraph.guard():
             np_x = np.array([2, 3, 4]).astype('float64')
             np_y = np.array([1, 5, 2]).astype('float64')
-            x = base.dygraph.to_variable(np_x)
-            y = base.dygraph.to_variable(np_y)
+            x = paddle.to_tensor(np_x)
+            y = paddle.to_tensor(np_y)
             z = self._executed_api(x, y)
             np_z = z.numpy(False)
             z_expected = np.array([1.0, -2.0, 2.0])

test/legacy_test/test_erf_op.py

@@ -68,7 +68,7 @@ def _test_case(self, place):
         x = np.random.uniform(-1, 1, size=(11, 17)).astype(np.float64)
         y_ref = erf(x)
         with dg.guard(place) as g:
-            x_var = dg.to_variable(x)
+            x_var = paddle.to_tensor(x)
             y_var = paddle.erf(x_var)
             y_test = y_var.numpy()
         np.testing.assert_allclose(y_ref, y_test, rtol=1e-05)

test/legacy_test/test_exception.py

@@ -84,7 +84,7 @@ def test_exception_in_dynamic_mode(self):
         with base.dygraph.guard(place):
             x = numpy.random.random(size=(10, 2)).astype('float32')
             linear = paddle.nn.Linear(1, 10)
-            data = base.dygraph.to_variable(x)
+            data = paddle.to_tensor(x)
             with self.assertRaises(ValueError):
                 res = linear(data)
 

test/legacy_test/test_fill_constant_op.py

@@ -373,9 +373,9 @@ def test_api(self):
             data1 = np.array([1, 2]).astype('int32')
             data2 = np.array([1.1]).astype('float32')
             data3 = np.array([88]).astype('int32')
-            shape = base.dygraph.to_variable(data1)
-            val = base.dygraph.to_variable(data2)
-            value = base.dygraph.to_variable(data3)
+            shape = paddle.to_tensor(data1)
+            val = paddle.to_tensor(data2)
+            value = paddle.to_tensor(data3)
             res1 = paddle.tensor.fill_constant(
                 shape=[1, 2], dtype='float32', value=1.1
             )

test/legacy_test/test_fleet_base.py

@@ -161,7 +161,7 @@ def setUp(self):
     def test_dygraph_method(self):
         paddle.disable_static()
         value = np.arange(26).reshape(2, 13).astype("float32")
-        a = base.dygraph.to_variable(value)
+        a = paddle.to_tensor(value)
         layer = paddle.nn.Linear(13, 5)
         adam = paddle.optimizer.Adam(
             learning_rate=0.01, parameters=layer.parameters()

test/legacy_test/test_flip.py

@@ -58,7 +58,7 @@ def test_static_graph(self):
     def test_dygraph(self):
         img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
         with base.dygraph.guard():
-            inputs = base.dygraph.to_variable(img)
+            inputs = paddle.to_tensor(img)
             ret = paddle.flip(inputs, [0])
             ret = ret.flip(0)
             ret = paddle.flip(ret, 1)

test/legacy_test/test_functional_conv1d.py

@@ -35,12 +35,12 @@ def setUp(self):
 
     def dygraph_case(self):
         with dg.guard():
-            x = dg.to_variable(self.input, dtype=paddle.float32)
-            w = dg.to_variable(self.filter, dtype=paddle.float32)
+            x = paddle.to_tensor(self.input, dtype=paddle.float32)
+            w = paddle.to_tensor(self.filter, dtype=paddle.float32)
             b = (
                 None
                 if self.bias is None
-                else dg.to_variable(self.bias, dtype=paddle.float32)
+                else paddle.to_tensor(self.bias, dtype=paddle.float32)
             )
             y = F.conv1d(
                 x,

test/xpu/test_elementwise_add_op_xpu_kp.py

@@ -338,8 +338,8 @@ def test_dygraph(self):
         with base.dygraph.guard():
             np_x = np.array([2, 3, 4]).astype('float32')
             np_y = np.array([1, 5, 2]).astype('float32')
-            x = base.dygraph.to_variable(np_x)
-            y = base.dygraph.to_variable(np_y)
+            x = paddle.to_tensor(np_x)
+            y = paddle.to_tensor(np_y)
             z = paddle.add(x, y)
             np_z = z.numpy()
             z_expected = np.array([3.0, 8.0, 6.0])