fix: some bugs..

Author: aztice

test/legacy_test/test_gather_op.py

@@ -101,29 +101,6 @@ def config_dtype(self):
         self.x_type = "float16"
 
 
-@unittest.skipIf(
-    not (core.is_compiled_with_cuda() or is_custom_device()),
-    "only support compiled with CUDA.",
-)
-class TestGatherGPUCPUConsistency(unittest.TestCase):
-    def test_gpu_cpu_consistency(self):
-        with paddle.base.dygraph.guard():
-            np.random.seed(42)
-            x = np.random.rand(1000, 128).astype("float32")
-            index = np.random.randint(0, 1000, size=(100,))
-            cpu_out = paddle.gather(
-                paddle.to_tensor(x, place=paddle.CPUPlace()),
-                paddle.to_tensor(index),
-            )
-            gpu_out = paddle.gather(
-                paddle.to_tensor(x, place=paddle.CUDAPlace(0)),
-                paddle.to_tensor(index),
-            )
-            np.testing.assert_allclose(
-                cpu_out.numpy(), gpu_out.numpy(), rtol=1e-6
-            )
-
-
 @unittest.skipIf(
     not (core.is_compiled_with_cuda() or is_custom_device())
     or core.cudnn_version() < 8100
@@ -770,38 +747,65 @@ def test_out2(self):
         np.testing.assert_allclose(result, expected_output, rtol=1e-05)
 
 
+@unittest.skipIf(
+    not (core.is_compiled_with_cuda() or is_custom_device()),
+    "only support compiled with CUDA.",
+)
+class TestGatherGPUCPUConsistency(unittest.TestCase):
+    def test_gpu_cpu_consistency(self):
+        paddle.disable_static()
+        np.random.seed(42)
+        x = np.random.rand(1000, 128).astype("float32")
+        index = np.random.randint(0, 1000, size=(100,))
+        cpu_out = paddle.gather(
+            paddle.to_tensor(x, place=paddle.CPUPlace()),
+            paddle.to_tensor(index),
+        )
+        gpu_out = paddle.gather(
+            paddle.to_tensor(x, place=paddle.CUDAPlace(0)),
+            paddle.to_tensor(index),
+        )
+        np.testing.assert_allclose(
+            cpu_out.numpy(), gpu_out.numpy(), rtol=1e-6
+        )
+        paddle.enable_static()
+
+
 class API_TestDygraphGather(unittest.TestCase):
     def test_out1(self):
-        with paddle.base.dygraph.guard():
-            input_1 = np.array([[1, 2], [3, 4], [5, 6]])
-            index_1 = np.array([1, 2])
-            input = paddle.to_tensor(input_1)
-            index = paddle.to_tensor(index_1)
-            output = paddle.gather(input, index)
-            output_np = output.numpy()
-            expected_output = np.array([[3, 4], [5, 6]])
-            np.testing.assert_allclose(output_np, expected_output, rtol=1e-05)
+        paddle.disable_static()
+        input_1 = np.array([[1, 2], [3, 4], [5, 6]])
+        index_1 = np.array([1, 2])
+        input = paddle.to_tensor(input_1)
+        index = paddle.to_tensor(index_1)
+        output = paddle.gather(input, index)
+        output_np = output.numpy()
+        expected_output = np.array([[3, 4], [5, 6]])
+        np.testing.assert_allclose(output_np, expected_output, rtol=1e-05)
+        paddle.enable_static()
 
     def test_out12(self):
-        with paddle.base.dygraph.guard():
-            input_1 = np.array([[1, 2], [3, 4], [5, 6]])
-            index_1 = np.array([1, 2])
-            x = paddle.to_tensor(input_1)
-            index = paddle.to_tensor(index_1)
-            output = paddle.gather(x, index, axis=0)
-            output_np = output.numpy()
-            expected_output = gather_numpy(input_1, index_1, axis=0)
-            np.testing.assert_allclose(output_np, expected_output, rtol=1e-05)
+        paddle.disable_static()
+        input_1 = np.array([[1, 2], [3, 4], [5, 6]])
+        index_1 = np.array([1, 2])
+        x = paddle.to_tensor(input_1)
+        index = paddle.to_tensor(index_1)
+        output = paddle.gather(x, index, axis=0)
+        output_np = output.numpy()
+        expected_output = gather_numpy(input_1, index_1, axis=0)
+        np.testing.assert_allclose(output_np, expected_output, rtol=1e-05)
+        paddle.enable_static()
 
     def test_zero_index(self):
-        with paddle.base.dygraph.guard():
-            x = paddle.to_tensor([[1, 2], [3, 4]])
-            index = paddle.to_tensor(np.array([]).astype('int64'))
-            for axis in range(len(x.shape)):
-                out = paddle.gather(x, index, axis)
-                expected_shape = list(x.shape)
-                expected_shape[axis] = 0
-                self.assertEqual(list(out.shape), expected_shape)
+        paddle.disable_static()
+        x = paddle.to_tensor([[1, 2], [3, 4]])
+        index = paddle.to_tensor(np.array([]).astype('int64'))
+        for axis in range(len(x.shape)):
+            out = paddle.gather(x, index, axis)
+            expected_shape = list(x.shape)
+            expected_shape[axis] = 0
+            self.assertEqual(list(out.shape), expected_shape)
+        paddle.enable_static()
 
     def test_large_data(self):
         if not (paddle.is_compiled_with_cuda() or is_custom_device()):