[Cleanup][B-14] Replace to_variable (#61574)

--------- Co-authored-by: Nyakku Shigure <sigure.qaq@gmail.com>
PaddlePaddle · Feb 5, 2024 · da76b51 · da76b51
1 parent ca68a91
commit da76b51
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Showing 10 changed files with 39 additions and 44 deletions.
diff --git a/test/dygraph_to_static/test_mnist.py b/test/dygraph_to_static/test_mnist.py
@@ -26,7 +26,6 @@
 
 import paddle
 from paddle import base
-from paddle.base.dygraph import to_variable
 from paddle.jit.translated_layer import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX
 from paddle.nn import Linear
 from paddle.optimizer import Adam
@@ -209,8 +208,8 @@ def train(self, to_static=False):
                     .reshape(-1, 1)
                 )
 
-                img = to_variable(dy_x_data)
-                label = to_variable(y_data)
+                img = paddle.to_tensor(dy_x_data)
+                label = paddle.to_tensor(y_data)
 
                 label.stop_gradient = True
                 prediction, acc, avg_loss = mnist(img, label=label)

diff --git a/test/dygraph_to_static/test_mobile_net.py b/test/dygraph_to_static/test_mobile_net.py
@@ -645,7 +645,7 @@ def predict_dygraph(args, data):
         model.set_dict(model_dict)
         model.eval()
 
-        pred_res = model(base.dygraph.to_variable(data))
+        pred_res = model(paddle.to_tensor(data))
 
         return pred_res.numpy()
 

diff --git a/test/legacy_test/test_mean_op.py b/test/legacy_test/test_mean_op.py
@@ -524,7 +524,7 @@ def test_base_api(self):
 
         with base.dygraph.guard():
             x_np = np.random.rand(10, 10).astype(np.float32)
-            x = base.dygraph.to_variable(x_np)
+            x = paddle.to_tensor(x_np)
             out = paddle.mean(x=x, axis=1)
         np.testing.assert_allclose(
             out.numpy(), np.mean(x_np, axis=1), rtol=1e-05

diff --git a/test/legacy_test/test_merged_adam_op.py b/test/legacy_test/test_merged_adam_op.py
@@ -47,16 +47,14 @@ def run_adam_op(
     paddle.disable_static()
     paddle.set_device(place)
 
-    param_vars = [paddle.base.dygraph.to_variable(p) for p in params]
-    grad_vars = [paddle.base.dygraph.to_variable(g) for g in grads]
-    lr_vars = [paddle.base.dygraph.to_variable(l) for l in lrs]
-    moment1_vars = [paddle.base.dygraph.to_variable(m) for m in moment1s]
-    moment2_vars = [paddle.base.dygraph.to_variable(m) for m in moment2s]
-    beta1_pow_vars = [paddle.base.dygraph.to_variable(b) for b in beta1_pows]
-    beta2_pow_vars = [paddle.base.dygraph.to_variable(b) for b in beta2_pows]
-    master_param_vars = [
-        paddle.base.dygraph.to_variable(m_p) for m_p in master_params
-    ]
+    param_vars = [paddle.to_tensor(p) for p in params]
+    grad_vars = [paddle.to_tensor(g) for g in grads]
+    lr_vars = [paddle.to_tensor(l) for l in lrs]
+    moment1_vars = [paddle.to_tensor(m) for m in moment1s]
+    moment2_vars = [paddle.to_tensor(m) for m in moment2s]
+    beta1_pow_vars = [paddle.to_tensor(b) for b in beta1_pows]
+    beta2_pow_vars = [paddle.to_tensor(b) for b in beta2_pows]
+    master_param_vars = [paddle.to_tensor(m_p) for m_p in master_params]
 
     if not use_merged:
         for i in range(len(param_vars)):

diff --git a/test/legacy_test/test_meshgrid_op.py b/test/legacy_test/test_meshgrid_op.py
@@ -269,8 +269,8 @@ def test_api_with_dygraph(self):
         ).astype('int32')
 
         with base.dygraph.guard():
-            tensor_3 = base.dygraph.to_variable(input_3)
-            tensor_4 = base.dygraph.to_variable(input_4)
+            tensor_3 = paddle.to_tensor(input_3)
+            tensor_4 = paddle.to_tensor(input_4)
             res_3, res_4 = paddle.tensor.meshgrid(tensor_3, tensor_4)
 
             np.testing.assert_array_equal(res_3.shape, [100, 200])
@@ -295,8 +295,8 @@ def test_api_with_dygraph_list_input(self):
         ).astype('int32')
 
         with base.dygraph.guard():
-            tensor_3 = base.dygraph.to_variable(input_3)
-            tensor_4 = base.dygraph.to_variable(input_4)
+            tensor_3 = paddle.to_tensor(input_3)
+            tensor_4 = paddle.to_tensor(input_4)
             res_3, res_4 = paddle.tensor.meshgrid([tensor_3, tensor_4])
 
             np.testing.assert_array_equal(res_3.shape, [100, 200])
@@ -321,8 +321,8 @@ def test_api_with_dygraph_tuple_input(self):
         ).astype('int32')
 
         with base.dygraph.guard():
-            tensor_3 = base.dygraph.to_variable(input_3)
-            tensor_4 = base.dygraph.to_variable(input_4)
+            tensor_3 = paddle.to_tensor(input_3)
+            tensor_4 = paddle.to_tensor(input_4)
             res_3, res_4 = paddle.tensor.meshgrid((tensor_3, tensor_4))
 
             np.testing.assert_array_equal(res_3.shape, [100, 200])
@@ -372,15 +372,15 @@ def test_dygraph_api(self):
         ).astype('int32')
 
         with base.dygraph.guard():
-            tensor_1 = base.dygraph.to_variable(input_1)
-            tensor_2 = base.dygraph.to_variable(input_2)
+            tensor_1 = paddle.to_tensor(input_1)
+            tensor_2 = paddle.to_tensor(input_2)
             tensor_1.stop_gradient = False
             tensor_2.stop_gradient = False
             res_1, res_2 = paddle.tensor.meshgrid((tensor_1, tensor_2))
             sum = paddle.add_n([res_1, res_2])
             sum.backward()
-            tensor_eager_1 = base.dygraph.to_variable(input_1)
-            tensor_eager_2 = base.dygraph.to_variable(input_2)
+            tensor_eager_1 = paddle.to_tensor(input_1)
+            tensor_eager_2 = paddle.to_tensor(input_2)
             tensor_eager_1.stop_gradient = False
             tensor_eager_2.stop_gradient = False
             res_eager_1, res_eager_2 = paddle.tensor.meshgrid(

diff --git a/test/legacy_test/test_mse_loss.py b/test/legacy_test/test_mse_loss.py
@@ -115,8 +115,8 @@ def test_NNMseLoss_mean(self):
             with base.dygraph.guard():
                 mse_loss = paddle.nn.loss.MSELoss()
                 dy_ret = mse_loss(
-                    base.dygraph.to_variable(input_np),
-                    base.dygraph.to_variable(label_np),
+                    paddle.to_tensor(input_np),
+                    paddle.to_tensor(label_np),
                 )
                 dy_result = dy_ret.numpy()
 
@@ -160,8 +160,8 @@ def test_NNMseLoss_sum(self):
             with base.dygraph.guard():
                 mse_loss = paddle.nn.loss.MSELoss(reduction='sum')
                 dy_ret = mse_loss(
-                    base.dygraph.to_variable(input_np),
-                    base.dygraph.to_variable(label_np),
+                    paddle.to_tensor(input_np),
+                    paddle.to_tensor(label_np),
                 )
                 dy_result = dy_ret.numpy()
 
@@ -205,8 +205,8 @@ def test_NNMseLoss_none(self):
             with base.dygraph.guard():
                 mse_loss = paddle.nn.loss.MSELoss(reduction='none')
                 dy_ret = mse_loss(
-                    base.dygraph.to_variable(input_np),
-                    base.dygraph.to_variable(label_np),
+                    paddle.to_tensor(input_np),
+                    paddle.to_tensor(label_np),
                 )
                 dy_result = dy_ret.numpy()
 

diff --git a/test/legacy_test/test_nansum_api.py b/test/legacy_test/test_nansum_api.py
@@ -136,7 +136,7 @@ def test_dygraph(self):
             [[float('nan'), 3, 5, 9], [1, 2, float('-nan'), 7]]
         ).astype(np.float32)
         with base.dygraph.guard():
-            inputs = base.dygraph.to_variable(x)
+            inputs = paddle.to_tensor(x)
             out = paddle.nansum(inputs)
             out_ref = np.array([27]).astype(np.float32)
 

diff --git a/test/legacy_test/test_nn_functional_hot_op.py b/test/legacy_test/test_nn_functional_hot_op.py
@@ -180,7 +180,7 @@ def test_api_with_dygraph(self):
         ).reshape([6, 1])
         with base.dygraph.guard():
             one_hot_label = functional.one_hot(
-                x=base.dygraph.to_variable(label), num_classes=num_classes
+                x=paddle.to_tensor(label), num_classes=num_classes
             )
 
 

diff --git a/test/legacy_test/test_nonzero_api.py b/test/legacy_test/test_nonzero_api.py
@@ -90,7 +90,7 @@ def test_nonzero_api(self):
     def test_dygraph_api(self):
         data_x = np.array([[True, False], [False, True]])
         with base.dygraph.guard():
-            x = base.dygraph.to_variable(data_x)
+            x = paddle.to_tensor(data_x)
             z = paddle.nonzero(x)
             np_z = z.numpy()
         expect_out = np.array([[0, 0], [1, 1]])

diff --git a/test/xpu/test_merged_adam_op_xpu.py b/test/xpu/test_merged_adam_op_xpu.py
@@ -55,16 +55,14 @@ def run_adam_op(
     paddle.disable_static()
     paddle.set_device(place)
 
-    param_vars = [paddle.base.dygraph.to_variable(p) for p in params]
-    grad_vars = [paddle.base.dygraph.to_variable(g) for g in grads]
-    lr_vars = [paddle.base.dygraph.to_variable(l) for l in lrs]
-    moment1_vars = [paddle.base.dygraph.to_variable(m) for m in moment1s]
-    moment2_vars = [paddle.base.dygraph.to_variable(m) for m in moment2s]
-    beta1_pow_vars = [paddle.base.dygraph.to_variable(b) for b in beta1_pows]
-    beta2_pow_vars = [paddle.base.dygraph.to_variable(b) for b in beta2_pows]
-    master_param_vars = [
-        paddle.base.dygraph.to_variable(m_p) for m_p in master_params
-    ]
+    param_vars = [paddle.to_tensor(p) for p in params]
+    grad_vars = [paddle.to_tensor(g) for g in grads]
+    lr_vars = [paddle.to_tensor(l) for l in lrs]
+    moment1_vars = [paddle.to_tensor(m) for m in moment1s]
+    moment2_vars = [paddle.to_tensor(m) for m in moment2s]
+    beta1_pow_vars = [paddle.to_tensor(b) for b in beta1_pows]
+    beta2_pow_vars = [paddle.to_tensor(b) for b in beta2_pows]
+    master_param_vars = [paddle.to_tensor(m_p) for m_p in master_params]
 
     if not use_merged:
         for i in range(len(param_vars)):