diff --git a/test/dygraph_to_static/test_for_enumerate.py b/test/dygraph_to_static/test_for_enumerate.py index d72e5a41742c94..46cfc80ebe7cd4 100644 --- a/test/dygraph_to_static/test_for_enumerate.py +++ b/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 diff --git a/test/legacy_test/test_elementwise_pow_op.py b/test/legacy_test/test_elementwise_pow_op.py index 82d4f889b28a15..79adfa8544cde0 100644 --- a/test/legacy_test/test_elementwise_pow_op.py +++ b/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) + y = paddle.to_tensor(self.y) x.stop_gradient = False y.stop_gradient = False res = x**y diff --git a/test/legacy_test/test_elementwise_sub_op.py b/test/legacy_test/test_elementwise_sub_op.py index 29185c1844bf4d..0fb79ff54fbf6c 100644 --- a/test/legacy_test/test_elementwise_sub_op.py +++ b/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]) diff --git a/test/legacy_test/test_erf_op.py b/test/legacy_test/test_erf_op.py index d66cdc3ce11793..a0e10986f1c938 100644 --- a/test/legacy_test/test_erf_op.py +++ b/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) diff --git a/test/legacy_test/test_exception.py b/test/legacy_test/test_exception.py index d8e998bf7f9eb6..5d1f04efca9f5f 100644 --- a/test/legacy_test/test_exception.py +++ b/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) diff --git a/test/legacy_test/test_fill_constant_op.py b/test/legacy_test/test_fill_constant_op.py index bac12927202a23..d09b694db96f4b 100644 --- a/test/legacy_test/test_fill_constant_op.py +++ b/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 ) diff --git a/test/legacy_test/test_fleet_base.py b/test/legacy_test/test_fleet_base.py index 6a20b425f9d456..2ffd8a747c72d4 100644 --- a/test/legacy_test/test_fleet_base.py +++ b/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() diff --git a/test/legacy_test/test_flip.py b/test/legacy_test/test_flip.py index 9557b51df0ab3b..b058bdd94d0d98 100644 --- a/test/legacy_test/test_flip.py +++ b/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) diff --git a/test/legacy_test/test_functional_conv1d.py b/test/legacy_test/test_functional_conv1d.py index 5100385497b50b..751b35b255497d 100644 --- a/test/legacy_test/test_functional_conv1d.py +++ b/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, diff --git a/test/xpu/test_elementwise_add_op_xpu_kp.py b/test/xpu/test_elementwise_add_op_xpu_kp.py index c551a538ce147e..a5a0eb7437acc1 100644 --- a/test/xpu/test_elementwise_add_op_xpu_kp.py +++ b/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])