Fix unittests after hide APIs

python/paddle/fluid/tests/unittests/test_batch_norm_op.py

@@ -129,7 +129,6 @@ def create_or_get_tensor(scope, var_name, var, place):
     if var is not None:
         assert isinstance(var, np.ndarray)
         tensor.set_recursive_sequence_lengths([])
-        tensor.set_dims(var.shape)
         tensor.set(var, place)
     return tensor
 

python/paddle/fluid/tests/unittests/test_dynrnn_static_input.py

@@ -65,10 +65,10 @@ class TestDyRnnStaticInput(unittest.TestCase):
         return self._lodtensor_to_ndarray(fetch_outs[0])
 
     def _lodtensor_to_ndarray(self, lod_tensor):
-        dims = lod_tensor.get_dims()
+        dims = lod_tensor.shape()
         ndarray = np.zeros(shape=dims).astype('float32')
         for i in xrange(np.product(dims)):
-            ndarray.ravel()[i] = lod_tensor.get_float_element(i)
+            ndarray.ravel()[i] = lod_tensor._get_float_element(i)
         return ndarray, lod_tensor.recursive_sequence_lengths()
 
     def build_graph(self, only_forward=False):
@@ -185,19 +185,19 @@ class TestDyRnnStaticInput(unittest.TestCase):
 
         actual_gradients, actual_lod = self.fetch_value(static_input_grad)
 
-        static_input_shape = self.static_input_tensor.get_dims()
+        static_input_shape = self.static_input_tensor.shape()
         numeric_gradients = np.zeros(shape=static_input_shape).astype('float32')
         # calculate numeric gradients
         tensor_size = np.product(static_input_shape)
         for i in xrange(tensor_size):
-            origin = self.static_input_tensor.get_float_element(i)
+            origin = self.static_input_tensor._get_float_element(i)
             x_pos = origin + self._delta
-            self.static_input_tensor.set_float_element(i, x_pos)
+            self.static_input_tensor._set_float_element(i, x_pos)
             y_pos = self.fetch_value(loss)[0][0]
             x_neg = origin - self._delta
-            self.static_input_tensor.set_float_element(i, x_neg)
+            self.static_input_tensor._set_float_element(i, x_neg)
             y_neg = self.fetch_value(loss)[0][0]
-            self.static_input_tensor.set_float_element(i, origin)
+            self.static_input_tensor._set_float_element(i, origin)
             numeric_gradients.ravel()[i] = (y_pos - y_neg) / self._delta / 2
         self.assertTrue(np.allclose(actual_gradients, numeric_gradients, 0.001))
         self.assertTrue(

python/paddle/fluid/tests/unittests/test_selected_rows.py

@@ -40,12 +40,12 @@ class TestSelectedRows(unittest.TestCase):
 
         # compare tensor
         self.assertAlmostEqual(2.0,
-                               selected_rows.get_tensor().get_float_element(0))
+                               selected_rows.get_tensor()._get_float_element(0))
         self.assertAlmostEqual(1.0,
-                               selected_rows.get_tensor().get_float_element(1))
+                               selected_rows.get_tensor()._get_float_element(1))
         self.assertAlmostEqual(
             4.0,
-            selected_rows.get_tensor().get_float_element(2 * row_numel + 8))
+            selected_rows.get_tensor()._get_float_element(2 * row_numel + 8))
 
 
 if __name__ == "__main__":

python/paddle/fluid/tests/unittests/test_shrink_rnn_memory.py

@@ -45,8 +45,8 @@ class TestShrinkRNNMemoryBase(unittest.TestCase):
 
     def sum_lodtensor(self, tensor):
         sum_res = 0.0
-        for i in xrange(np.product(tensor.get_dims())):
-            sum_res += tensor.get_float_element(i)
+        for i in xrange(np.product(tensor.shape())):
+            sum_res += tensor._get_float_element(i)
         return sum_res
 
 

python/paddle/fluid/tests/unittests/test_tensor.py

@@ -25,7 +25,7 @@ class TestTensor(unittest.TestCase):
 
         tensor = var.get_tensor()
 
-        tensor.set_dims([1000, 784])
+        tensor._set_dims([1000, 784])
         tensor._alloc_int(place)
         tensor_array = numpy.array(tensor)
         self.assertEqual((1000, 784), tensor_array.shape)
@@ -44,7 +44,7 @@ class TestTensor(unittest.TestCase):
 
         tensor = var.get_tensor()
 
-        tensor.set_dims([1000, 784])
+        tensor._set_dims([1000, 784])
         tensor._alloc_float(place)
 
         tensor_array = numpy.array(tensor)
@@ -63,7 +63,7 @@ class TestTensor(unittest.TestCase):
         var_lod = scope.var("test_lod_tensor")
         lod_tensor = var_lod.get_tensor()
 
-        lod_tensor.set_dims([4, 4, 6])
+        lod_tensor._set_dims([4, 4, 6])
         lod_tensor._alloc_int(place)
         array = numpy.array(lod_tensor)
         array[0, 0, 0] = 3
@@ -84,7 +84,7 @@ class TestTensor(unittest.TestCase):
         var_lod = scope.var("test_lod_tensor")
 
         lod_tensor = var_lod.get_tensor()
-        lod_tensor.set_dims([5, 2, 3, 4])
+        lod_tensor._set_dims([5, 2, 3, 4])
         lod_tensor._alloc_float(place)
 
         tensor_array = numpy.array(lod_tensor)
@@ -108,7 +108,7 @@ class TestTensor(unittest.TestCase):
         lod_py = [[2, 1], [1, 2, 2]]
         lod_tensor = core.LoDTensor()
 
-        lod_tensor.set_dims([5, 2, 3, 4])
+        lod_tensor._set_dims([5, 2, 3, 4])
         lod_tensor.set_recursive_sequence_lengths(lod_py)
         lod_tensor._alloc_float(place)
         tensor_array = numpy.array(lod_tensor)
@@ -128,7 +128,7 @@ class TestTensor(unittest.TestCase):
         lod_py = [[2, 1], [1, 2, 2]]
         lod_tensor = core.LoDTensor()
 
-        lod_tensor.set_dims([5, 2, 3, 4])
+        lod_tensor._set_dims([5, 2, 3, 4])
         lod_tensor.set_recursive_sequence_lengths(lod_py)
         lod_tensor._alloc_float(place)
         tensor_array = numpy.array(lod_tensor)
@@ -148,7 +148,7 @@ class TestTensor(unittest.TestCase):
 
         tensor = var.get_tensor()
 
-        tensor.set_dims([0, 1])
+        tensor._set_dims([0, 1])
         tensor._alloc_float(place)
 
         tensor_array = numpy.array(tensor)