test=develop, add random to testfile

paddle/fluid/API.spec

@@ -221,7 +221,7 @@ paddle.fluid.layers.psroi_pool (ArgSpec(args=['input', 'rois', 'output_channels'
 paddle.fluid.layers.teacher_student_sigmoid_loss (ArgSpec(args=['input', 'label', 'soft_max_up_bound', 'soft_max_lower_bound'], varargs=None, keywords=None, defaults=(15.0, -15.0)), ('document', '2f6ff96864054a31aa4bb659c6722c99'))
 paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '431a4301c35032166ec029f7432c80a7'))
 paddle.fluid.layers.tree_conv (ArgSpec(args=['nodes_vector', 'edge_set', 'output_size', 'num_filters', 'max_depth', 'act', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 2, 'tanh', None, None, None)), ('document', '34ea12ac9f10a65dccbc50100d12e607'))
-paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', 'cb0c35513643d9911e95c3194d6933c4'))
+paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', '7d010db0a2404dfbecb9ba5804788a16'))
 paddle.fluid.layers.data (ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)), ('document', '33bbd42027d872b3818b3d64ec52e139'))
 paddle.fluid.layers.open_files (ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None)), ('document', 'b1ae2e1cc0750e58726374061ea90ecc'))
 paddle.fluid.layers.read_file (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', 'b0a1c2fc51c27a106da28f3308c41f5e'))

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

@@ -86,8 +86,9 @@ class TestNpairLossOp(unittest.TestCase):
             shape=[num_data, feat_dim],
             dtype=self.dtype,
             append_batch_size=False)
+        rname = 'labels' + str(np.random.rand()).split('.')[1]
         labels_tensor = fluid.layers.data(
-            name='labels',
+            name=rname,
             shape=[num_data],
             dtype=self.dtype,
             append_batch_size=False)
@@ -100,7 +101,7 @@ class TestNpairLossOp(unittest.TestCase):
         out_tensor = exe.run(feed={
             'anchor': embeddings_anchor,
             'positive': embeddings_positive,
-            'labels': labels
+            rname: labels
         },
                              fetch_list=[npair_loss_op.name])