[Cleanup][B-17]Replace to_variable (#61539)

Author: co63oc

test/legacy_test/test_smooth_l1_loss.py

@@ -84,8 +84,8 @@ def test_static():
         with base.dygraph.guard():
             smooth_l1_loss = paddle.nn.loss.SmoothL1Loss()
             dy_ret = smooth_l1_loss(
-                base.dygraph.to_variable(input_np),
-                base.dygraph.to_variable(label_np),
+                paddle.to_tensor(input_np),
+                paddle.to_tensor(label_np),
             )
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
@@ -132,8 +132,8 @@ def test_static():
         with base.dygraph.guard():
             smooth_l1_loss = paddle.nn.loss.SmoothL1Loss(reduction='sum')
             dy_ret = smooth_l1_loss(
-                base.dygraph.to_variable(input_np),
-                base.dygraph.to_variable(label_np),
+                paddle.to_tensor(input_np),
+                paddle.to_tensor(label_np),
             )
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
@@ -180,8 +180,8 @@ def test_static():
         with base.dygraph.guard():
             smooth_l1_loss = paddle.nn.loss.SmoothL1Loss(reduction='none')
             dy_ret = smooth_l1_loss(
-                base.dygraph.to_variable(input_np),
-                base.dygraph.to_variable(label_np),
+                paddle.to_tensor(input_np),
+                paddle.to_tensor(label_np),
             )
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)
@@ -229,8 +229,8 @@ def test_static():
         with base.dygraph.guard():
             smooth_l1_loss = paddle.nn.loss.SmoothL1Loss(delta=delta)
             dy_ret = smooth_l1_loss(
-                base.dygraph.to_variable(input_np),
-                base.dygraph.to_variable(label_np),
+                paddle.to_tensor(input_np),
+                paddle.to_tensor(label_np),
             )
             dy_ret_value = dy_ret.numpy()
             self.assertIsNotNone(dy_ret_value)

test/legacy_test/test_softmax_mask_fuse_op.py

@@ -142,8 +142,8 @@ def test_dygraph(self):
             mask = np.random.randint(0, 2, (1, 1, 8, 32)).astype("float32")
             mask_in_np = np.where(mask == 1, -10000.0, mask)
             rst_np = _get_softmax(x_in_np, mask_in_np, False)
-            input_x = base.dygraph.to_variable(x_in_np)
-            input_mask = base.dygraph.to_variable(mask_in_np)
+            input_x = paddle.to_tensor(x_in_np)
+            input_mask = paddle.to_tensor(mask_in_np)
 
             rst = incubate.softmax_mask_fuse(input_x, input_mask)
             np.testing.assert_allclose(rst, rst_np, rtol=1e-05)

test/legacy_test/test_softmax_mask_fuse_upper_triangle_op.py

@@ -122,7 +122,7 @@ def test_dygraph(self):
             with base.dygraph.guard(base.CUDAPlace(0)):
                 x_in_np = np.random.random((1, 4, 32, 32)).astype(dtype)
                 rst_np = _get_softmax_upper(x_in_np, dtype == 'float16')
-                input_x = base.dygraph.to_variable(x_in_np)
+                input_x = paddle.to_tensor(x_in_np)
 
                 rst = incubate.softmax_mask_fuse_upper_triangle(input_x)
                 np.testing.assert_allclose(rst, rst_np, rtol=1e-05)

test/legacy_test/test_solve_op.py

@@ -578,8 +578,8 @@ def test_dygraph(self):
             with base.dygraph.guard(place):
                 input_x_np = np.ones([4, 4]).astype(self.dtype)
                 input_y_np = np.ones([4, 4]).astype(self.dtype)
-                input_x = base.dygraph.to_variable(input_x_np)
-                input_y = base.dygraph.to_variable(input_y_np)
+                input_x = paddle.to_tensor(input_x_np)
+                input_y = paddle.to_tensor(input_y_np)
                 try:
                     result = paddle.linalg.solve(input_x, input_y)
                 except RuntimeError as ex:

test/legacy_test/test_stack_op.py

@@ -318,16 +318,16 @@ def test_out(self):
         data2 = np.array([[3.0, 4.0]])
         data3 = np.array([[5.0, 6.0]])
         with base.dygraph.guard():
-            x1 = base.dygraph.to_variable(data1)
-            x2 = base.dygraph.to_variable(data2)
-            x3 = base.dygraph.to_variable(data3)
+            x1 = paddle.to_tensor(data1)
+            x2 = paddle.to_tensor(data2)
+            x3 = paddle.to_tensor(data3)
             result = paddle.stack([x1, x2, x3])
             result_np = result.numpy()
         expected_result = np.stack([data1, data2, data3])
         np.testing.assert_allclose(expected_result, result_np, rtol=1e-05)
 
         with base.dygraph.guard():
-            y1 = base.dygraph.to_variable(data1)
+            y1 = paddle.to_tensor(data1)
             result = paddle.stack([y1], axis=0)
             result_np_2 = result.numpy()
         expected_result_2 = np.stack([data1], axis=0)

test/legacy_test/test_traced_layer_err_msg.py

@@ -63,7 +63,7 @@ def test_trace_err(self):
         if base.framework.in_dygraph_mode():
             return
         with base.dygraph.guard():
-            in_x = base.dygraph.to_variable(
+            in_x = paddle.to_tensor(
                 np.random.random((self.batch_size, self.feature_size)).astype(
                     'float32'
                 )
@@ -108,7 +108,7 @@ def test_set_strategy_err(self):
         if base.framework.in_dygraph_mode():
             return
         with base.dygraph.guard():
-            in_x = base.dygraph.to_variable(
+            in_x = paddle.to_tensor(
                 np.random.random((self.batch_size, self.feature_size)).astype(
                     'float32'
                 )
@@ -145,7 +145,7 @@ def test_save_inference_model_err(self):
         if base.framework.in_dygraph_mode():
             return
         with base.dygraph.guard():
-            in_x = base.dygraph.to_variable(
+            in_x = paddle.to_tensor(
                 np.random.random((self.batch_size, self.feature_size)).astype(
                     'float32'
                 )
@@ -216,7 +216,7 @@ def _train_simple_net(self):
             )
 
             for i in range(5):
-                in_x = base.dygraph.to_variable(
+                in_x = paddle.to_tensor(
                     np.random.random(
                         (self.batch_size, self.feature_size)
                     ).astype('float32')

test/legacy_test/test_transpose_op.py

@@ -619,23 +619,23 @@ def test_static_out(self):
     def test_dygraph_out(self):
         with base.dygraph.guard():
             np_x = np.random.random([10]).astype("float64")
-            data = base.dygraph.to_variable(np_x)
+            data = paddle.to_tensor(np_x)
             z = paddle.t(data)
             np_z = z.numpy()
             z_expected = np.array(np.transpose(np_x))
         self.assertEqual((np_z == z_expected).all(), True)
 
         with base.dygraph.guard():
             np_x = np.random.random([10, 5]).astype("float64")
-            data = base.dygraph.to_variable(np_x)
+            data = paddle.to_tensor(np_x)
             z = paddle.t(data)
             np_z = z.numpy()
             z_expected = np.array(np.transpose(np_x))
         self.assertEqual((np_z == z_expected).all(), True)
 
         with base.dygraph.guard():
             np_x = np.random.random([1, 5]).astype("float64")
-            data = base.dygraph.to_variable(np_x)
+            data = paddle.to_tensor(np_x)
             z = paddle.t(data)
             np_z = z.numpy()
             z_expected = np.array(np.transpose(np_x))

test/legacy_test/test_tril_triu_op.py

@@ -287,7 +287,7 @@ def test_api_with_dygraph(self):
                         np.random.uniform(-1, 1, [1, 9, 9, 4])
                         + 1j * np.random.uniform(-1, 1, [1, 9, 9, 4])
                     ).astype(dtype)
-                x = base.dygraph.to_variable(data)
+                x = paddle.to_tensor(data)
                 tril_out, triu_out = (
                     tensor.tril(x).numpy(),
                     tensor.triu(x).numpy(),

test/legacy_test/test_unfold_op.py

@@ -221,7 +221,7 @@ def setUp(self):
     def test_dygraph(self):
         for place in self.places:
             with base.dygraph.guard(place):
-                input = base.dygraph.to_variable(self.inputs['X'])
+                input = paddle.to_tensor(self.inputs['X'])
                 m = paddle.nn.Unfold(**self.attrs)
                 m.eval()
                 result = m(input)

test/xpu/test_unfold_op_xpu.py

@@ -159,7 +159,7 @@ def setUp(self):
         def test_dygraph(self):
             for place in self.places:
                 with base.dygraph.guard(place):
-                    input = base.dygraph.to_variable(self.inputs['X'])
+                    input = paddle.to_tensor(self.inputs['X'])
                     m = paddle.nn.Unfold(**self.attrs)
                     m.eval()
                     result = m(input)