Remove Place in GraphWrapper

docs/source/quick_start/md/quick_start.md

@@ -53,7 +53,6 @@ place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
 # use GraphWrapper as a container for graph data to construct a graph neural network
 gw = pgl.graph_wrapper.GraphWrapper(name='graph',
-                        place = place,
                         node_feat=g.node_feat_info())
 ```
 

docs/source/quick_start/md/quick_start_for_heterGraph.md

@@ -77,7 +77,6 @@ place = fluid.CPUPlace()
 
 # create a GraphWrapper as a container for graph data
 gw = heter_graph_wrapper.HeterGraphWrapper(name='heter_graph', 
-                                    place = place, 
                                     edge_types = g.edge_types_info(),
                                     node_feat=g.node_feat_info(),
                                     edge_feat=g.edge_feat_info())

examples/GATNE/model.py

@@ -53,7 +53,6 @@ class GATNE(object):
 
         self.gw = heter_graph_wrapper.HeterGraphWrapper(
             name="heter_graph",
-            place=place,
             edge_types=self.graph.edge_types_info(),
             node_feat=self.graph.node_feat_info(),
             edge_feat=self.graph.edge_feat_info())

examples/dgi/train.py

@@ -65,7 +65,6 @@ def main(args):
     with fluid.program_guard(train_program, startup_program):
         gw = pgl.graph_wrapper.GraphWrapper(
             name="graph",
-            place=place,
             node_feat=dataset.graph.node_feat_info())
 
         output = pgl.layers.gcn(gw,

examples/distribute_graphsage/train.py

@@ -170,7 +170,7 @@ def main(args):
 
     with fluid.program_guard(train_program, startup_program):
         graph_wrapper = pgl.graph_wrapper.GraphWrapper(
-            "sub_graph", fluid.CPUPlace(), node_feat=[('feats', [None, 602], np.dtype('float32'))])
+            "sub_graph", node_feat=[('feats', [None, 602], np.dtype('float32'))])
         model_loss, model_acc = build_graph_model(
             graph_wrapper,
             num_class=data["num_class"],

examples/graphsage/train.py

@@ -204,8 +204,8 @@ def main(args):
 
         graph_wrapper = pgl.graph_wrapper.GraphWrapper(
             "sub_graph",
-            fluid.CPUPlace(),
             node_feat=data['graph'].node_feat_info())
+
         model_loss, model_acc = build_graph_model(
             graph_wrapper,
             num_class=data["num_class"],

examples/graphsage/train_multi.py

@@ -231,7 +231,6 @@ def main(args):
     with fluid.program_guard(train_program, startup_program):
         graph_wrapper = pgl.graph_wrapper.GraphWrapper(
             "sub_graph",
-            fluid.CPUPlace(),
             node_feat=data['graph'].node_feat_info())
 
         model_loss, model_acc = build_graph_model(

examples/graphsage/train_scale.py

@@ -227,7 +227,6 @@ def main(args):
     with fluid.program_guard(train_program, startup_program):
         graph_wrapper = pgl.graph_wrapper.GraphWrapper(
             "sub_graph",
-            fluid.CPUPlace(),
             node_feat=data['graph'].node_feat_info())
 
         model_loss, model_acc = build_graph_model(

examples/stgcn/main.py

@@ -49,7 +49,6 @@ def main(args):
     with fluid.program_guard(train_program, startup_program):
         gw = pgl.graph_wrapper.GraphWrapper(
             "gw",
-            place,
             node_feat=[('norm', [None, 1], "float32")],
             edge_feat=[('weights', [None, 1], "float32")])
 

examples/unsup_graphsage/train.py

@@ -88,7 +88,7 @@ def build_graph_model(args):
 
     graph_wrappers.append(
         pgl.graph_wrapper.GraphWrapper(
-            "layer_0", fluid.CPUPlace(), node_feat=node_feature_info))
+            "layer_0", node_feat=node_feature_info))
     #edge_feat=[("f", [None, 1], "float32")]))
 
     num_embed = args.num_nodes

ogb_examples/graphproppred/main_pgl.py

@@ -148,7 +148,6 @@ def main():
     with fluid.program_guard(train_program, startup_program):
         gw = pgl.graph_wrapper.GraphWrapper(
             "graph",
-            place=place,
             node_feat=graph_data.node_feat_info(),
             edge_feat=graph_data.edge_feat_info())
         pred = model.forward(gw)

ogb_examples/linkproppred/main_pgl.py

@@ -158,7 +158,6 @@ def main():
             num_layers=args.num_layers)
         gw = pgl.graph_wrapper.GraphWrapper(
             "graph",
-            place,
             node_feat=graph_data.node_feat_info(),
             edge_feat=graph_data.edge_feat_info())
         pred, prob, loss = model.forward(gw)

pgl/graph_wrapper.py

@@ -475,9 +475,6 @@ class GraphWrapper(BaseGraphWrapper):
     Args:
         name: The graph data prefix
 
-        place: fluid.CPUPlace or fluid.CUDAPlace(n) indicating the
-               device to hold the graph data.
-
         node_feat: A list of tuples that decribe the details of node
                    feature tenosr. Each tuple mush be (name, shape, dtype)
                    and the first dimension of the shape must be set unknown
@@ -516,7 +513,6 @@ class GraphWrapper(BaseGraphWrapper):
                         })
 
             graph_wrapper = GraphWrapper(name="graph",
-                        place=place,
                         node_feat=graph.node_feat_info(),
                         edge_feat=graph.edge_feat_info())
 
@@ -531,12 +527,11 @@ class GraphWrapper(BaseGraphWrapper):
                 ret = exe.run(fetch_list=[...], feed=feed_dict )
     """
 
-    def __init__(self, name, place, node_feat=[], edge_feat=[]):
+    def __init__(self, name, node_feat=[], edge_feat=[], **kwargs):
         super(GraphWrapper, self).__init__()
         # collect holders for PyReader
         self._data_name_prefix = name
         self._holder_list = []
-        self._place = place
         self.__create_graph_attr_holders()
         for node_feat_name, node_feat_shape, node_feat_dtype in node_feat:
             self.__create_graph_node_feat_holders(

pgl/heter_graph_wrapper.py

@@ -44,9 +44,6 @@ class HeterGraphWrapper(object):
     Args:
         name: The heterogeneous graph data prefix
 
-        place: fluid.CPUPlace or fluid.CUDAPlace(n) indicating the
-               device to hold the graph data.
-
         node_feat: A dict of list of tuples that decribe the details of node
                    feature tenosr. Each tuple mush be (name, shape, dtype)
                    and the first dimension of the shape must be set unknown
@@ -85,19 +82,15 @@ class HeterGraphWrapper(object):
                             node_feat=node_feat,
                             edge_feat=edges_feat)
            
-            place = fluid.CPUPlace()
-
             gw = heter_graph_wrapper.HeterGraphWrapper(
                                 name='heter_graph', 
-                                place = place, 
                                 edge_types = g.edge_types_info(),
                                 node_feat=g.node_feat_info(),
                                 edge_feat=g.edge_feat_info())
     """
 
-    def __init__(self, name, place, edge_types, node_feat={}, edge_feat={}):
+    def __init__(self, name, edge_types, node_feat={}, edge_feat={}, **kwargs):
         self.__data_name_prefix = name
-        self._place = place
         self._edge_types = edge_types
         self._multi_gw = {}
         for edge_type in self._edge_types:
@@ -114,7 +107,6 @@ class HeterGraphWrapper(object):
 
             self._multi_gw[edge_type] = GraphWrapper(
                 name=type_name,
-                place=self._place,
                 node_feat=n_feat,
                 edge_feat=e_feat)