[Hetero] New syntax (#824)

* WIP. remove graph arg in NodeBatch and EdgeBatch

* refactor: use graph adapter for scheduler

* WIP: recv

* draft impl

* stuck at bipartite

* bipartite->unitgraph; support dsttype == srctype

* pass test_query

* pass test_query

* pass test_view

* test apply

* pass udf message passing tests

* pass quan's test using builtins

* WIP: wildcard slicing

* new construct methods

* broken

* good

* add stack cross reducer

* fix bug; fix mx

* fix bug in csrmm2 when the CSR is not square

* lint

* removed FlattenedHeteroGraph class

* WIP

* prop nodes, prop edges, filter nodes/edges

* add DGLGraph tests to heterograph. Fix several bugs

* finish nx<->hetero graph conversion

* create bipartite from nx

* more spec on hetero/homo conversion

* silly fixes

* check node and edge types

* repr

* to api

* adj APIs

* inc

* fix some lints and bugs

* fix some lints

* hetero/homo conversion

* fix flatten test

* more spec in hetero_from_homo and test

* flatten using concat names

* WIP: creators

* rewrite hetero_from_homo in a more efficient way

* remove useless variables

* fix lint

* subgraphs and typed subgraphs

* lint & removed heterosubgraph class

* lint x2

* disable heterograph mutation test

* docstring update

* add edge id for nx graph test

* fix mx unittests

* fix bug

* try fix

* fix unittest when cross_reducer is stack

* fix ci

* fix nx bipartite bug; docstring

* fix scipy creation bug

* lint

* fix bug when converting heterograph from homograph

* fix bug in hetero_from_homo about ntype order

* trailing white

* docstring fixes for add_foo and data views

* docstring for relation slice

* to_hetero and to_homo with feature support

* lint

* lint

* DGLGraph compatibility

* incidence matrix & docstring fixes

* example string fixes

* feature in hetero_from_relations

* deduplication of edge types in to_hetero

* fix lint

* fix

include/dgl/base_heterograph.h

@@ -21,7 +21,9 @@ namespace dgl {
 
 // Forward declaration
 class BaseHeteroGraph;
+class FlattenedHeteroGraph;
 typedef std::shared_ptr<BaseHeteroGraph> HeteroGraphPtr;
+typedef std::shared_ptr<FlattenedHeteroGraph> FlattenedHeteroGraphPtr;
 struct HeteroSubgraph;
 
 /*!
@@ -46,10 +48,14 @@ class BaseHeteroGraph : public runtime::Object {
   ////////////////////////// query/operations on meta graph ////////////////////////
 
   /*! \return the number of vertex types */
-  virtual uint64_t NumVertexTypes() const = 0;
+  virtual uint64_t NumVertexTypes() const {
+    return meta_graph_->NumVertices();
+  }
 
   /*! \return the number of edge types */
-  virtual uint64_t NumEdgeTypes() const = 0;
+  virtual uint64_t NumEdgeTypes() const {
+    return meta_graph_->NumEdges();
+  }
 
   /*! \return the meta graph */
   virtual GraphPtr meta_graph() const {
@@ -351,6 +357,17 @@ class BaseHeteroGraph : public runtime::Object {
   virtual HeteroSubgraph EdgeSubgraph(
       const std::vector<IdArray>& eids, bool preserve_nodes = false) const = 0;
 
+  /*!
+   * \brief Convert the list of requested unitgraph graphs into a single unitgraph graph.
+   *
+   * \param etypes The list of edge type IDs.
+   * \return The flattened graph, with induced source/edge/destination types/IDs.
+   */
+  virtual FlattenedHeteroGraphPtr Flatten(const std::vector<dgl_type_t>& etypes) const {
+    LOG(FATAL) << "Flatten operation unsupported";
+    return nullptr;
+  }
+
   static constexpr const char* _type_key = "graph.HeteroGraph";
   DGL_DECLARE_OBJECT_TYPE_INFO(BaseHeteroGraph, runtime::Object);
 
@@ -381,6 +398,62 @@ struct HeteroSubgraph : public runtime::Object {
   DGL_DECLARE_OBJECT_TYPE_INFO(HeteroSubgraph, runtime::Object);
 };
 
+/*! \brief The flattened heterograph */
+struct FlattenedHeteroGraph : public runtime::Object {
+  /*! \brief The graph */
+  HeteroGraphRef graph;
+  /*!
+   * \brief Mapping from source node ID to node type in parent graph
+   * \note The induced type array guarantees that the same type always appear contiguously.
+   */
+  IdArray induced_srctype;
+  /*!
+   * \brief The set of node types in parent graph appearing in source nodes.
+   */
+  IdArray induced_srctype_set;
+  /*! \brief Mapping from source node ID to local node ID in parent graph */
+  IdArray induced_srcid;
+  /*!
+   * \brief Mapping from edge ID to edge type in parent graph
+   * \note The induced type array guarantees that the same type always appear contiguously.
+   */
+  IdArray induced_etype;
+  /*!
+   * \brief The set of edge types in parent graph appearing in edges.
+   */
+  IdArray induced_etype_set;
+  /*! \brief Mapping from edge ID to local edge ID in parent graph */
+  IdArray induced_eid;
+  /*!
+   * \brief Mapping from destination node ID to node type in parent graph
+   * \note The induced type array guarantees that the same type always appear contiguously.
+   */
+  IdArray induced_dsttype;
+  /*!
+   * \brief The set of node types in parent graph appearing in destination nodes.
+   */
+  IdArray induced_dsttype_set;
+  /*! \brief Mapping from destination node ID to local node ID in parent graph */
+  IdArray induced_dstid;
+
+  void VisitAttrs(runtime::AttrVisitor *v) final {
+    v->Visit("graph", &graph);
+    v->Visit("induced_srctype", &induced_srctype);
+    v->Visit("induced_srctype_set", &induced_srctype_set);
+    v->Visit("induced_srcid", &induced_srcid);
+    v->Visit("induced_etype", &induced_etype);
+    v->Visit("induced_etype_set", &induced_etype_set);
+    v->Visit("induced_eid", &induced_eid);
+    v->Visit("induced_dsttype", &induced_dsttype);
+    v->Visit("induced_dsttype_set", &induced_dsttype_set);
+    v->Visit("induced_dstid", &induced_dstid);
+  }
+
+  static constexpr const char* _type_key = "graph.FlattenedHeteroGraph";
+  DGL_DECLARE_OBJECT_TYPE_INFO(FlattenedHeteroGraph, runtime::Object);
+};
+DGL_DEFINE_OBJECT_REF(FlattenedHeteroGraphRef, FlattenedHeteroGraph);
+
 // Define HeteroSubgraphRef
 DGL_DEFINE_OBJECT_REF(HeteroSubgraphRef, HeteroSubgraph);
 

include/dgl/runtime/object.h

@@ -18,6 +18,7 @@ namespace runtime {
 // forward declaration
 class Object;
 class ObjectRef;
+class NDArray;
 
 /*!
  * \brief Visitor class to each object attribute.
@@ -33,6 +34,7 @@ class AttrVisitor {
   virtual void Visit(const char* key, bool* value) = 0;
   virtual void Visit(const char* key, std::string* value) = 0;
   virtual void Visit(const char* key, ObjectRef* value) = 0;
+  virtual void Visit(const char* key, NDArray* value) = 0;
   template<typename ENum,
            typename = typename std::enable_if<std::is_enum<ENum>::value>::type>
   void Visit(const char* key, ENum* ptr) {

python/dgl/__init__.py

@@ -13,9 +13,10 @@ from ._ffi.runtime_ctypes import TypeCode
 from ._ffi.function import register_func, get_global_func, list_global_func_names, extract_ext_funcs
 from ._ffi.base import DGLError, __version__
 
-from .base import ALL
+from .base import ALL, NTYPE, NID, ETYPE, EID
 from .backend import load_backend
 from .batched_graph import *
+from .convert import *
 from .graph import DGLGraph
 from .heterograph import DGLHeteroGraph
 from .nodeflow import *

python/dgl/base.py

@@ -8,6 +8,13 @@ from ._ffi.function import _init_internal_api
 
 # A special symbol for selecting all nodes or edges.
 ALL = "__ALL__"
+# An alias for [:]
+SLICE_FULL = slice(None, None, None)
+# Reserved column names for storing parent node/edge types and IDs in flattened heterographs
+NTYPE = '_TYPE'
+NID = '_ID'
+ETYPE = '_TYPE'
+EID = '_ID'
 
 def is_all(arg):
     """Return true if the argument is a special symbol for all nodes or edges."""

python/dgl/frame.py

@@ -186,8 +186,8 @@ class Frame(MutableMapping):
         update on one will not reflect to the other. The inplace update will
         be seen by both. This follows the semantic of python's container.
     num_rows : int, optional [default=0]
-        The number of rows in this frame. If ``data`` is provided, ``num_rows``
-        will be ignored and inferred from the given data.
+        The number of rows in this frame. If ``data`` is provided and is not empty,
+        ``num_rows`` will be ignored and inferred from the given data.
     """
     def __init__(self, data=None, num_rows=0):
         if data is None:
@@ -202,7 +202,7 @@ class Frame(MutableMapping):
             elif len(self._columns) != 0:
                 self._num_rows = len(next(iter(self._columns.values())))
             else:
-                self._num_rows = 0
+                self._num_rows = num_rows
             # sanity check
             for name, col in self._columns.items():
                 if len(col) != self._num_rows:
@@ -880,23 +880,23 @@ class FrameRef(MutableMapping):
         """
         return self._index.get_items(query)
 
-def frame_like(other, num_rows):
-    """Create a new frame that has the same scheme as the given one.
+def frame_like(other, num_rows=None):
+    """Create an empty frame that has the same initializer as the given one.
 
     Parameters
     ----------
     other : Frame
         The given frame.
     num_rows : int
-        The number of rows of the new one.
+        The number of rows of the new one. If None, use other.num_rows
+        (Default: None)
 
     Returns
     -------
     Frame
         The new frame.
     """
-    # TODO(minjie): scheme is not inherited at the moment. Fix this
-    #   when moving per-col initializer to column scheme.
+    num_rows = other.num_rows if num_rows is None else num_rows
     newf = Frame(num_rows=num_rows)
     # set global initializr
     if other.get_initializer() is None:

python/dgl/graph.py

@@ -11,7 +11,7 @@ from . import backend as F
 from . import init
 from .frame import FrameRef, Frame, Scheme, sync_frame_initializer
 from . import graph_index
-from .runtime import ir, scheduler, Runtime
+from .runtime import ir, scheduler, Runtime, GraphAdapter
 from . import utils
 from .view import NodeView, EdgeView
 from .udf import NodeBatch, EdgeBatch
@@ -49,14 +49,6 @@ class DGLBaseGraph(object):
         """
         return self._graph.number_of_nodes()
 
-    def _number_of_src_nodes(self):
-        """Return number of source nodes (only used in scheduler)"""
-        return self.number_of_nodes()
-
-    def _number_of_dst_nodes(self):
-        """Return number of destination nodes (only used in scheduler)"""
-        return self.number_of_nodes()
-
     def __len__(self):
         """Return the number of nodes in the graph."""
         return self.number_of_nodes()
@@ -73,10 +65,6 @@ class DGLBaseGraph(object):
         """
         return self._graph.is_readonly()
 
-    def _number_of_edges(self):
-        """Return number of edges in the current view (only used for scheduler)"""
-        return self.number_of_edges()
-
     def number_of_edges(self):
         """Return the number of edges in the graph.
 
@@ -951,14 +939,6 @@ class DGLGraph(DGLBaseGraph):
     def _set_msg_index(self, index):
         self._msg_index = index
 
-    @property
-    def _src_frame(self):
-        return self._node_frame
-
-    @property
-    def _dst_frame(self):
-        return self._node_frame
-
     def add_nodes(self, num, data=None):
         """Add multiple new nodes.
 
@@ -2089,9 +2069,9 @@ class DGLGraph(DGLBaseGraph):
         else:
             v = utils.toindex(v)
         with ir.prog() as prog:
-            scheduler.schedule_apply_nodes(graph=self,
-                                           v=v,
+            scheduler.schedule_apply_nodes(v=v,
                                            apply_func=func,
+                                           node_frame=self._node_frame,
                                            inplace=inplace)
             Runtime.run(prog)
 
@@ -2159,12 +2139,7 @@ class DGLGraph(DGLBaseGraph):
             u, v, _ = self._graph.find_edges(eid)
 
         with ir.prog() as prog:
-            scheduler.schedule_apply_edges(graph=self,
-                                           u=u,
-                                           v=v,
-                                           eid=eid,
-                                           apply_func=func,
-                                           inplace=inplace)
+            scheduler.schedule_apply_edges(AdaptedDGLGraph(self), u, v, eid, func, inplace)
             Runtime.run(prog)
 
     def group_apply_edges(self, group_by, func, edges=ALL, inplace=False):
@@ -2241,10 +2216,8 @@ class DGLGraph(DGLBaseGraph):
             u, v, _ = self._graph.find_edges(eid)
 
         with ir.prog() as prog:
-            scheduler.schedule_group_apply_edge(graph=self,
-                                                u=u,
-                                                v=v,
-                                                eid=eid,
+            scheduler.schedule_group_apply_edge(graph=AdaptedDGLGraph(self),
+                                                u=u, v=v, eid=eid,
                                                 apply_func=func,
                                                 group_by=group_by,
                                                 inplace=inplace)
@@ -2308,7 +2281,7 @@ class DGLGraph(DGLBaseGraph):
             return
 
         with ir.prog() as prog:
-            scheduler.schedule_send(graph=self, u=u, v=v, eid=eid,
+            scheduler.schedule_send(graph=AdaptedDGLGraph(self), u=u, v=v, eid=eid,
                                     message_func=message_func)
             Runtime.run(prog)
 
@@ -2407,7 +2380,7 @@ class DGLGraph(DGLBaseGraph):
             return
 
         with ir.prog() as prog:
-            scheduler.schedule_recv(graph=self,
+            scheduler.schedule_recv(graph=AdaptedDGLGraph(self),
                                     recv_nodes=v,
                                     reduce_func=reduce_func,
                                     apply_func=apply_node_func,
@@ -2515,7 +2488,7 @@ class DGLGraph(DGLBaseGraph):
             return
 
         with ir.prog() as prog:
-            scheduler.schedule_snr(graph=self,
+            scheduler.schedule_snr(graph=AdaptedDGLGraph(self),
                                    edge_tuples=(u, v, eid),
                                    message_func=message_func,
                                    reduce_func=reduce_func,
@@ -2618,7 +2591,7 @@ class DGLGraph(DGLBaseGraph):
         if len(v) == 0:
             return
         with ir.prog() as prog:
-            scheduler.schedule_pull(graph=self,
+            scheduler.schedule_pull(graph=AdaptedDGLGraph(self),
                                     pull_nodes=v,
                                     message_func=message_func,
                                     reduce_func=reduce_func,
@@ -2715,7 +2688,7 @@ class DGLGraph(DGLBaseGraph):
         if len(u) == 0:
             return
         with ir.prog() as prog:
-            scheduler.schedule_push(graph=self,
+            scheduler.schedule_push(graph=AdaptedDGLGraph(self),
                                     u=u,
                                     message_func=message_func,
                                     reduce_func=reduce_func,
@@ -2762,7 +2735,7 @@ class DGLGraph(DGLBaseGraph):
         assert reduce_func is not None
 
         with ir.prog() as prog:
-            scheduler.schedule_update_all(graph=self,
+            scheduler.schedule_update_all(graph=AdaptedDGLGraph(self),
                                           message_func=message_func,
                                           reduce_func=reduce_func,
                                           apply_func=apply_node_func)
@@ -3219,7 +3192,7 @@ class DGLGraph(DGLBaseGraph):
             v = utils.toindex(nodes)
 
         n_repr = self.get_n_repr(v)
-        nbatch = NodeBatch(self, v, n_repr)
+        nbatch = NodeBatch(v, n_repr)
         n_mask = F.copy_to(predicate(nbatch), F.cpu())
 
         if is_all(nodes):
@@ -3277,8 +3250,8 @@ class DGLGraph(DGLBaseGraph):
         filter_nodes
         """
         if is_all(edges):
-            eid = ALL
             u, v, _ = self._graph.edges('eid')
+            eid = utils.toindex(slice(0, self.number_of_edges()))
         elif isinstance(edges, tuple):
             u, v = edges
             u = utils.toindex(u)
@@ -3292,7 +3265,7 @@ class DGLGraph(DGLBaseGraph):
         src_data = self.get_n_repr(u)
         edge_data = self.get_e_repr(eid)
         dst_data = self.get_n_repr(v)
-        ebatch = EdgeBatch(self, (u, v, eid), src_data, edge_data, dst_data)
+        ebatch = EdgeBatch((u, v, eid), src_data, edge_data, dst_data)
         e_mask = F.copy_to(predicate(ebatch), F.cpu())
 
         if is_all(edges):
@@ -3492,3 +3465,79 @@ class DGLGraph(DGLBaseGraph):
         yield
         self._node_frame = old_nframe
         self._edge_frame = old_eframe
+
+############################################################
+# Internal APIs
+############################################################
+
+class AdaptedDGLGraph(GraphAdapter):
+    """Adapt DGLGraph to interface required by scheduler.
+
+    Parameters
+    ----------
+    graph : DGLGraph
+        Graph
+    """
+    def __init__(self, graph):
+        self.graph = graph
+
+    @property
+    def gidx(self):
+        return self.graph._graph
+
+    def num_src(self):
+        """Number of source nodes."""
+        return self.graph.number_of_nodes()
+
+    def num_dst(self):
+        """Number of destination nodes."""
+        return self.graph.number_of_nodes()
+
+    def num_edges(self):
+        """Number of edges."""
+        return self.graph.number_of_edges()
+
+    @property
+    def srcframe(self):
+        """Frame to store source node features."""
+        return self.graph._node_frame
+
+    @property
+    def dstframe(self):
+        """Frame to store source node features."""
+        return self.graph._node_frame
+
+    @property
+    def edgeframe(self):
+        """Frame to store edge features."""
+        return self.graph._edge_frame
+
+    @property
+    def msgframe(self):
+        """Frame to store messages."""
+        return self.graph._msg_frame
+
+    @property
+    def msgindicator(self):
+        """Message indicator tensor."""
+        return self.graph._get_msg_index()
+
+    @msgindicator.setter
+    def msgindicator(self, val):
+        """Set new message indicator tensor."""
+        self.graph._set_msg_index(val)
+
+    def in_edges(self, nodes):
+        return self.graph._graph.in_edges(nodes)
+
+    def out_edges(self, nodes):
+        return self.graph._graph.out_edges(nodes)
+
+    def edges(self, form):
+        return self.graph._graph.edges(form)
+
+    def get_immutable_gidx(self, ctx):
+        return self.graph._graph.get_immutable_gidx(ctx)
+
+    def bits_needed(self):
+        return self.graph._graph.bits_needed()

python/dgl/graph_index.py

@@ -1129,9 +1129,12 @@ def from_edge_list(elist, is_multigraph, readonly):
 
     Parameters
     ---------
-    elist : list
-        List of (u, v) edge tuple.
+    elist : list, tuple
+        List of (u, v) edge tuple, or a tuple of src/dst lists
     """
+    if isinstance(elist, tuple):
+        src, dst = elist
+    else:
         src, dst = zip(*elist)
     src = np.array(src)
     dst = np.array(dst)

python/dgl/heterograph_index.py

 """Module for heterogeneous graph index class definition."""
 from __future__ import absolute_import
 
+import numpy as np
+import scipy
+
 from ._ffi.object import register_object, ObjectBase
 from ._ffi.function import _init_api
 from .base import DGLError
@@ -48,7 +51,7 @@ class HeteroGraphIndex(ObjectBase):
         return self.metagraph.number_of_edges()
 
     def get_relation_graph(self, etype):
-        """Get the bipartite graph of the given edge/relation type.
+        """Get the unitgraph graph of the given edge/relation type.
 
         Parameters
         ----------
@@ -58,10 +61,26 @@ class HeteroGraphIndex(ObjectBase):
         Returns
         -------
         HeteroGraphIndex
-            The bipartite graph.
+            The unitgraph graph.
         """
         return _CAPI_DGLHeteroGetRelationGraph(self, int(etype))
 
+    def flatten_relations(self, etypes):
+        """Convert the list of requested unitgraph graphs into a single unitgraph
+        graph.
+
+        Parameters
+        ----------
+        etypes : list[int]
+            The edge/relation types.
+
+        Returns
+        -------
+        HeteroGraphIndex
+            The unitgraph graph.
+        """
+        return _CAPI_DGLHeteroGetFlattenedGraph(self, etypes)
+
     def add_nodes(self, ntype, num):
         """Add nodes.
 
@@ -131,7 +150,7 @@ class HeteroGraphIndex(ObjectBase):
         return _CAPI_DGLHeteroNumBits(self)
 
     def bits_needed(self, etype):
-        """Return the number of integer bits needed to represent the bipartite graph.
+        """Return the number of integer bits needed to represent the unitgraph graph.
 
         Parameters
         ----------
@@ -658,6 +677,146 @@ class HeteroGraphIndex(ObjectBase):
         else:
             raise Exception("unknown format")
 
+    def adjacency_matrix_scipy(self, etype, transpose, fmt, return_edge_ids=None):
+        """Return the scipy adjacency matrix representation of this graph.
+
+        By default, a row of returned adjacency matrix represents the destination
+        of an edge and the column represents the source.
+
+        When transpose is True, a row represents the source and a column represents
+        a destination.
+
+        Parameters
+        ----------
+        etype : int
+            Edge type
+        transpose : bool
+            A flag to transpose the returned adjacency matrix.
+        fmt : str
+            Indicates the format of returned adjacency matrix.
+        return_edge_ids : bool
+            Indicates whether to return edge IDs or 1 as elements.
+
+        Returns
+        -------
+        scipy.sparse.spmatrix
+            The scipy representation of adjacency matrix.
+        """
+        if not isinstance(transpose, bool):
+            raise DGLError('Expect bool value for "transpose" arg,'
+                           ' but got %s.' % (type(transpose)))
+
+        if return_edge_ids is None:
+            dgl_warning(
+                "Adjacency matrix by default currently returns edge IDs."
+                "  As a result there is one 0 entry which is not eliminated."
+                "  In the next release it will return 1s by default,"
+                " and 0 will be eliminated otherwise.",
+                FutureWarning)
+            return_edge_ids = True
+
+        rst = _CAPI_DGLHeteroGetAdj(self, int(etype), transpose, fmt)
+        srctype, dsttype = self.metagraph.find_edge(etype)
+        nrows = self.number_of_nodes(srctype) if transpose else self.number_of_nodes(dsttype)
+        ncols = self.number_of_nodes(dsttype) if transpose else self.number_of_nodes(srctype)
+        nnz = self.number_of_edges(etype)
+        if fmt == "csr":
+            indptr = utils.toindex(rst(0)).tonumpy()
+            indices = utils.toindex(rst(1)).tonumpy()
+            data = utils.toindex(rst(2)).tonumpy() if return_edge_ids else np.ones_like(indices)
+            return scipy.sparse.csr_matrix((data, indices, indptr), shape=(nrows, ncols))
+        elif fmt == 'coo':
+            idx = utils.toindex(rst(0)).tonumpy()
+            row, col = np.reshape(idx, (2, nnz))
+            data = np.arange(0, nnz) if return_edge_ids else np.ones_like(row)
+            return scipy.sparse.coo_matrix((data, (row, col)), shape=(nrows, ncols))
+        else:
+            raise Exception("unknown format")
+
+    def incidence_matrix(self, etype, typestr, ctx):
+        """Return the incidence matrix representation of this graph.
+
+        An incidence matrix is an n x m sparse matrix, where n is
+        the number of nodes and m is the number of edges. Each nnz
+        value indicating whether the edge is incident to the node
+        or not.
+
+        There are three types of an incidence matrix `I`:
+        * "in":
+          - I[v, e] = 1 if e is the in-edge of v (or v is the dst node of e);
+          - I[v, e] = 0 otherwise.
+        * "out":
+          - I[v, e] = 1 if e is the out-edge of v (or v is the src node of e);
+          - I[v, e] = 0 otherwise.
+        * "both":
+          - I[v, e] = 1 if e is the in-edge of v;
+          - I[v, e] = -1 if e is the out-edge of v;
+          - I[v, e] = 0 otherwise (including self-loop).
+
+        Parameters
+        ----------
+        etype : int
+            Edge type
+        typestr : str
+            Can be either "in", "out" or "both"
+        ctx : context
+            The context of returned incidence matrix.
+
+        Returns
+        -------
+        SparseTensor
+            The incidence matrix.
+        utils.Index
+            A index for data shuffling due to sparse format change. Return None
+            if shuffle is not required.
+        """
+        src, dst, eid = self.edges(etype)
+        src = src.tousertensor(ctx)  # the index of the ctx will be cached
+        dst = dst.tousertensor(ctx)  # the index of the ctx will be cached
+        eid = eid.tousertensor(ctx)  # the index of the ctx will be cached
+        srctype, dsttype = self.metagraph.find_edge(etype)
+
+        m = self.number_of_edges(etype)
+        if typestr == 'in':
+            n = self.number_of_nodes(dsttype)
+            row = F.unsqueeze(dst, 0)
+            col = F.unsqueeze(eid, 0)
+            idx = F.cat([row, col], dim=0)
+            # FIXME(minjie): data type
+            dat = F.ones((m,), dtype=F.float32, ctx=ctx)
+            inc, shuffle_idx = F.sparse_matrix(dat, ('coo', idx), (n, m))
+        elif typestr == 'out':
+            n = self.number_of_nodes(srctype)
+            row = F.unsqueeze(src, 0)
+            col = F.unsqueeze(eid, 0)
+            idx = F.cat([row, col], dim=0)
+            # FIXME(minjie): data type
+            dat = F.ones((m,), dtype=F.float32, ctx=ctx)
+            inc, shuffle_idx = F.sparse_matrix(dat, ('coo', idx), (n, m))
+        elif typestr == 'both':
+            assert srctype == dsttype, \
+                    "'both' is supported only if source and destination type are the same"
+            n = self.number_of_nodes(srctype)
+            # first remove entries for self loops
+            mask = F.logical_not(F.equal(src, dst))
+            src = F.boolean_mask(src, mask)
+            dst = F.boolean_mask(dst, mask)
+            eid = F.boolean_mask(eid, mask)
+            n_entries = F.shape(src)[0]
+            # create index
+            row = F.unsqueeze(F.cat([src, dst], dim=0), 0)
+            col = F.unsqueeze(F.cat([eid, eid], dim=0), 0)
+            idx = F.cat([row, col], dim=0)
+            # FIXME(minjie): data type
+            x = -F.ones((n_entries,), dtype=F.float32, ctx=ctx)
+            y = F.ones((n_entries,), dtype=F.float32, ctx=ctx)
+            dat = F.cat([x, y], dim=0)
+            inc, shuffle_idx = F.sparse_matrix(dat, ('coo', idx), (n, m))
+        else:
+            raise DGLError('Invalid incidence matrix type: %s' % str(typestr))
+        shuffle_idx = utils.toindex(shuffle_idx) if shuffle_idx is not None else None
+        return inc, shuffle_idx
+
     def node_subgraph(self, induced_nodes):
         """Return the induced node subgraph.
 
@@ -696,16 +855,16 @@ class HeteroGraphIndex(ObjectBase):
         eids = [edges.todgltensor() for edges in induced_edges]
         return _CAPI_DGLHeteroEdgeSubgraph(self, eids, preserve_nodes)
 
-    @utils.cached_member(cache='_cache', prefix='bipartite')
-    def get_bipartite(self, etype, ctx):
-        """Create a bipartite graph from given edge type and copy to the given device
+    @utils.cached_member(cache='_cache', prefix='unitgraph')
+    def get_unitgraph(self, etype, ctx):
+        """Create a unitgraph graph from given edge type and copy to the given device
         context.
 
         Note: this internal function is for DGL scheduler use only
 
         Parameters
         ----------
-        etype : int, or None
+        etype : int
             If the graph index is a Bipartite graph index, this argument must be None.
             Otherwise, it represents the edge type.
         ctx : DGLContext
@@ -715,7 +874,7 @@ class HeteroGraphIndex(ObjectBase):
         -------
         HeteroGraphIndex
         """
-        g = self.get_relation_graph(etype) if etype is not None else self
+        g = self.get_relation_graph(etype)
         return g.asbits(self.bits_needed(etype or 0)).copy_to(ctx)
 
     def get_csr_shuffle_order(self, etype):
@@ -778,11 +937,17 @@ class HeteroSubgraphIndex(ObjectBase):
         ret = _CAPI_DGLHeteroSubgraphGetInducedEdges(self)
         return [utils.toindex(v.data) for v in ret]
 
-def create_bipartite_from_coo(num_src, num_dst, row, col):
-    """Create a bipartite graph index from COO format
+#################################################################
+# Creators
+#################################################################
+
+def create_unitgraph_from_coo(num_ntypes, num_src, num_dst, row, col):
+    """Create a unitgraph graph index from COO format
 
     Parameters
     ----------
+    num_ntypes : int
+        Number of node types (must be 1 or 2).
     num_src : int
         Number of nodes in the src type.
     num_dst : int
@@ -796,14 +961,16 @@ def create_bipartite_from_coo(num_src, num_dst, row, col):
     -------
     HeteroGraphIndex
     """
-    return _CAPI_DGLHeteroCreateBipartiteFromCOO(
-        int(num_src), int(num_dst), row.todgltensor(), col.todgltensor())
+    return _CAPI_DGLHeteroCreateUnitGraphFromCOO(
+        int(num_ntypes), int(num_src), int(num_dst), row.todgltensor(), col.todgltensor())
 
-def create_bipartite_from_csr(num_src, num_dst, indptr, indices, edge_ids):
-    """Create a bipartite graph index from CSR format
+def create_unitgraph_from_csr(num_ntypes, num_src, num_dst, indptr, indices, edge_ids):
+    """Create a unitgraph graph index from CSR format
 
     Parameters
     ----------
+    num_ntypes : int
+        Number of node types (must be 1 or 2).
     num_src : int
         Number of nodes in the src type.
     num_dst : int
@@ -819,11 +986,11 @@ def create_bipartite_from_csr(num_src, num_dst, indptr, indices, edge_ids):
     -------
     HeteroGraphIndex
     """
-    return _CAPI_DGLHeteroCreateBipartiteFromCSR(
-        int(num_src), int(num_dst),
+    return _CAPI_DGLHeteroCreateUnitGraphFromCSR(
+        int(num_ntypes), int(num_src), int(num_dst),
         indptr.todgltensor(), indices.todgltensor(), edge_ids.todgltensor())
 
-def create_heterograph(metagraph, rel_graphs):
+def create_heterograph_from_relations(metagraph, rel_graphs):
     """Create a heterograph from metagraph and graphs of every relation.
 
     Parameters

python/dgl/runtime/__init__.py

@@ -3,3 +3,4 @@ from __future__ import absolute_import
 
 from . import scheduler
 from .runtime import Runtime
+from .adapter import GraphAdapter

python/dgl/runtime/adapter.py

+"""Temporary adapter to unify DGLGraph and HeteroGraph for scheduler.
+NOTE(minjie): remove once all scheduler codes are migrated to heterograph
+"""
+from __future__ import absolute_import
+
+from abc import ABC, abstractmethod
+
+class GraphAdapter(ABC):
+    """Temporary adapter class to unify DGLGraph and DGLHeteroGraph for schedulers."""
+    @property
+    @abstractmethod
+    def gidx(self):
+        """Get graph index object."""
+
+    @abstractmethod
+    def num_src(self):
+        """Number of source nodes."""
+
+    @abstractmethod
+    def num_dst(self):
+        """Number of destination nodes."""
+
+    @abstractmethod
+    def num_edges(self):
+        """Number of edges."""
+
+    @property
+    @abstractmethod
+    def srcframe(self):
+        """Frame to store source node features."""
+
+    @property
+    @abstractmethod
+    def dstframe(self):
+        """Frame to store source node features."""
+
+    @property
+    @abstractmethod
+    def edgeframe(self):
+        """Frame to store edge features."""
+
+    @property
+    @abstractmethod
+    def msgframe(self):
+        """Frame to store messages."""
+
+
+    @property
+    @abstractmethod
+    def msgindicator(self):
+        """Message indicator tensor."""
+
+    @msgindicator.setter
+    @abstractmethod
+    def msgindicator(self, val):
+        """Set new message indicator tensor."""
+
+    @abstractmethod
+    def in_edges(self, nodes):
+        """Get in edges
+
+        Parameters
+        ----------
+        nodes : utils.Index
+            Nodes
+
+        Returns
+        -------
+        tuple of utils.Index
+            (src, dst, eid)
+        """
+
+    @abstractmethod
+    def out_edges(self, nodes):
+        """Get out edges
+
+        Parameters
+        ----------
+        nodes : utils.Index
+            Nodes
+
+        Returns
+        -------
+        tuple of utils.Index
+            (src, dst, eid)
+        """
+
+    @abstractmethod
+    def edges(self, form):
+        """Get all edges
+
+        Parameters
+        ----------
+        form : str
+            "eid", "uv", etc.
+
+        Returns
+        -------
+        tuple of utils.Index
+            (src, dst, eid)
+        """
+
+    @abstractmethod
+    def get_immutable_gidx(self, ctx):
+        """Get immutable graph index for kernel computation.
+
+        Parameters
+        ----------
+        ctx : DGLContext
+            The context of the returned graph.
+
+        Returns
+        -------
+        GraphIndex
+
+        """
+
+    @abstractmethod
+    def bits_needed(self):
+        """Return the number of integer bits needed to represent the graph
+
+        Returns
+        -------
+        int
+            The number of bits needed
+        """

python/dgl/runtime/degree_bucketing.py

@@ -10,7 +10,6 @@ from . import ir
 from .ir import var
 
 def gen_degree_bucketing_schedule(
-        graph,
         reduce_udf,
         message_ids,
         dst_nodes,
@@ -28,8 +27,6 @@ def gen_degree_bucketing_schedule(
 
     Parameters
     ----------
-    graph : DGLGraph
-        DGLGraph to use
     reduce_udf : callable
         The UDF to reduce messages.
     message_ids : utils.Index
@@ -56,7 +53,7 @@ def gen_degree_bucketing_schedule(
     fd_list = []
     for deg, vbkt, mid in zip(degs, buckets, msg_ids):
         # create per-bkt rfunc
-        rfunc = _create_per_bkt_rfunc(graph, reduce_udf, deg, vbkt)
+        rfunc = _create_per_bkt_rfunc(reduce_udf, deg, vbkt)
         # vars
         vbkt = var.IDX(vbkt)
         mid = var.IDX(mid)
@@ -144,7 +141,7 @@ def _process_node_buckets(buckets):
 
     return v, degs, dsts, msg_ids, zero_deg_nodes
 
-def _create_per_bkt_rfunc(graph, reduce_udf, deg, vbkt):
+def _create_per_bkt_rfunc(reduce_udf, deg, vbkt):
     """Internal function to generate the per degree bucket node UDF."""
     def _rfunc_wrapper(node_data, mail_data):
         def _reshaped_getter(key):
@@ -152,12 +149,11 @@ def _create_per_bkt_rfunc(graph, reduce_udf, deg, vbkt):
             new_shape = (len(vbkt), deg) + F.shape(msg)[1:]
             return F.reshape(msg, new_shape)
         reshaped_mail_data = utils.LazyDict(_reshaped_getter, mail_data.keys())
-        nbatch = NodeBatch(graph, vbkt, node_data, reshaped_mail_data)
+        nbatch = NodeBatch(vbkt, node_data, reshaped_mail_data)
         return reduce_udf(nbatch)
     return _rfunc_wrapper
 
 def gen_group_apply_edge_schedule(
-        graph,
         apply_func,
         u, v, eid,
         group_by,
@@ -175,8 +171,6 @@ def gen_group_apply_edge_schedule(
 
     Parameters
     ----------
-    graph : DGLGraph
-        DGLGraph to use
     apply_func: callable
         The edge_apply_func UDF
     u: utils.Index
@@ -209,7 +203,7 @@ def gen_group_apply_edge_schedule(
     fd_list = []
     for deg, u_bkt, v_bkt, eid_bkt in zip(degs, uids, vids, eids):
         # create per-bkt efunc
-        _efunc = var.FUNC(_create_per_bkt_efunc(graph, apply_func, deg,
+        _efunc = var.FUNC(_create_per_bkt_efunc(apply_func, deg,
                                                 u_bkt, v_bkt, eid_bkt))
         # vars
         var_u = var.IDX(u_bkt)
@@ -280,7 +274,7 @@ def _process_edge_buckets(buckets):
     eids = split(eids)
     return degs, uids, vids, eids
 
-def _create_per_bkt_efunc(graph, apply_func, deg, u, v, eid):
+def _create_per_bkt_efunc(apply_func, deg, u, v, eid):
     """Internal function to generate the per degree bucket edge UDF."""
     batch_size = len(u) // deg
     def _efunc_wrapper(src_data, edge_data, dst_data):
@@ -302,7 +296,7 @@ def _create_per_bkt_efunc(graph, apply_func, deg, u, v, eid):
                                             edge_data.keys())
         reshaped_dst_data = utils.LazyDict(_reshape_func(dst_data),
                                            dst_data.keys())
-        ebatch = EdgeBatch(graph, (u, v, eid), reshaped_src_data,
+        ebatch = EdgeBatch((u, v, eid), reshaped_src_data,
                            reshaped_edge_data, reshaped_dst_data)
         return {k: _reshape_back(v) for k, v in apply_func(ebatch).items()}
     return _efunc_wrapper

python/dgl/runtime/spmv.py

@@ -6,8 +6,7 @@ from ..base import DGLError
 from .. import backend as F
 from .. import utils
 from .. import ndarray as nd
-from ..graph_index import GraphIndex
-from ..heterograph_index import HeteroGraphIndex, create_bipartite_from_coo
+from ..heterograph_index import create_unitgraph_from_coo
 
 from . import ir
 from .ir import var
@@ -129,8 +128,8 @@ def build_gidx_and_mapping_graph(graph):
 
     Parameters
     ----------
-    graph : DGLGraph or DGLHeteroGraph
-        The homogeneous graph, or a bipartite view of the heterogeneous graph.
+    graph : GraphAdapter
+        Graph
 
     Returns
     -------
@@ -142,30 +141,21 @@ def build_gidx_and_mapping_graph(graph):
     nbits : int
         Number of ints needed to represent the graph
     """
-    gidx = graph._graph
-    if isinstance(gidx, GraphIndex):
-        return gidx.get_immutable_gidx, None, gidx.bits_needed()
-    elif isinstance(gidx, HeteroGraphIndex):
-        return (partial(gidx.get_bipartite, graph._current_etype_idx),
-                None,
-                gidx.bits_needed(graph._current_etype_idx))
-    else:
-        raise TypeError('unknown graph index type %s' % type(gidx))
-
+    return graph.get_immutable_gidx, None, graph.bits_needed()
 
 def build_gidx_and_mapping_uv(edge_tuples, num_src, num_dst):
     """Build immutable graph index and mapping using the given (u, v) edges
 
-    The matrix is of shape (len(reduce_nodes), n), where n is the number of
-    nodes in the graph. Therefore, when doing SPMV, the src node data should be
-    all the node features.
+    The matrix is of shape (num_src, num_dst).
 
     Parameters
     ---------
     edge_tuples : tuple of three utils.Index
         A tuple of (u, v, eid)
-    num_src, num_dst : int
-        The number of source and destination nodes.
+    num_src : int
+        Number of source nodes.
+    num_dst : int
+        Number of destination nodes.
 
     Returns
     -------
@@ -178,7 +168,7 @@ def build_gidx_and_mapping_uv(edge_tuples, num_src, num_dst):
         Number of ints needed to represent the graph
     """
     u, v, eid = edge_tuples
-    gidx = create_bipartite_from_coo(num_src, num_dst, u, v)
+    gidx = create_unitgraph_from_coo(2, num_src, num_dst, u, v)
     forward, backward = gidx.get_csr_shuffle_order(0)
     eid = eid.tousertensor()
     nbits = gidx.bits_needed(0)
@@ -189,8 +179,7 @@ def build_gidx_and_mapping_uv(edge_tuples, num_src, num_dst):
     edge_map = utils.CtxCachedObject(
         lambda ctx: (nd.array(forward_map, ctx=ctx),
                      nd.array(backward_map, ctx=ctx)))
-    return partial(gidx.get_bipartite, None), edge_map, nbits
-
+    return partial(gidx.get_unitgraph, 0), edge_map, nbits
 
 def build_gidx_and_mapping_block(graph, block_id, edge_tuples=None):
     """Build immutable graph index and mapping for node flow

python/dgl/udf.py

 """User-defined function related data structures."""
 from __future__ import absolute_import
 
-from .base import is_all
-from . import backend as F
-from . import utils
-
 class EdgeBatch(object):
     """The class that can represent a batch of edges.
 
     Parameters
     ----------
-    g : DGLGraph
-        The graph object.
     edges : tuple of utils.Index
         The edge tuple (u, v, eid). eid can be ALL
     src_data : dict
@@ -24,8 +18,7 @@ class EdgeBatch(object):
         The dst node features, in the form of ``dict``
         with ``str`` keys and ``tensor`` values
     """
-    def __init__(self, g, edges, src_data, edge_data, dst_data):
-        self._g = g
+    def __init__(self, edges, src_data, edge_data, dst_data):
         self._edges = edges
         self._src_data = src_data
         self._edge_data = edge_data
@@ -75,9 +68,6 @@ class EdgeBatch(object):
             destination node and the edge id for the ith edge
             in the batch.
         """
-        if is_all(self._edges[2]):
-            self._edges = self._edges[:2] + (utils.toindex(F.arange(
-                0, self._g.number_of_edges())),)
         u, v, eid = self._edges
         return (u.tousertensor(), v.tousertensor(), eid.tousertensor())
 
@@ -104,9 +94,7 @@ class NodeBatch(object):
 
     Parameters
     ----------
-    g : DGLGraph
-        The graph object.
-    nodes : utils.Index or ALL
+    nodes : utils.Index
         The node ids.
     data : dict
         The node features, in the form of ``dict``
@@ -115,8 +103,7 @@ class NodeBatch(object):
         The messages, , in the form of ``dict``
         with ``str`` keys and ``tensor`` values
     """
-    def __init__(self, g, nodes, data, msgs=None):
-        self._g = g
+    def __init__(self, nodes, data, msgs=None):
         self._nodes = nodes
         self._data = data
         self._msgs = msgs
@@ -154,9 +141,6 @@ class NodeBatch(object):
         tensor
             The nodes.
         """
-        if is_all(self._nodes):
-            self._nodes = utils.toindex(F.arange(
-                0, self._g.number_of_nodes()))
         return self._nodes.tousertensor()
 
     def batch_size(self):
@@ -166,9 +150,6 @@ class NodeBatch(object):
         -------
         int
         """
-        if is_all(self._nodes):
-            return self._g.number_of_nodes()
-        else:
         return len(self._nodes)
 
     def __len__(self):

python/dgl/utils.py

@@ -505,3 +505,14 @@ def to_nbits_int(tensor, nbits):
         return F.astype(tensor, F.int32)
     else:
         return F.astype(tensor, F.int64)
+
+def make_invmap(array, use_numpy=True):
+    """Find the unique elements of the array and return another array with indices
+    to the array of unique elements."""
+    if use_numpy:
+        uniques = np.unique(array)
+    else:
+        uniques = list(set(array))
+    invmap = {x: i for i, x in enumerate(uniques)}
+    remapped = np.array([invmap[x] for x in array])
+    return uniques, invmap, remapped

python/dgl/view.py

@@ -10,6 +10,7 @@ from .base import ALL, is_all, DGLError
 from . import backend as F
 
 NodeSpace = namedtuple('NodeSpace', ['data'])
+EdgeSpace = namedtuple('EdgeSpace', ['data'])
 
 class NodeView(object):
     """A NodeView class to act as G.nodes for a DGLGraph.
@@ -79,8 +80,6 @@ class NodeDataView(MutableMapping):
         data = self._graph.get_n_repr(self._nodes)
         return repr({key : data[key] for key in self._graph._node_frame})
 
-EdgeSpace = namedtuple('EdgeSpace', ['data'])
-
 class EdgeView(object):
     """A EdgeView class to act as G.edges for a DGLGraph.
 
@@ -256,111 +255,57 @@ class HeteroNodeView(object):
     def __init__(self, graph):
         self._graph = graph
 
-    def __getitem__(self, ntype):
-        return HeteroNodeTypeView(self._graph, ntype)
-
-class HeteroNodeTypeView(object):
-    """A NodeView class to act as G.nodes[ntype] for a DGLHeteroGraph.
-
-    See Also
-    --------
-    dgl.DGLGraph.nodes
-    """
-    __slots__ = ['_graph', '_ntype']
-
-    def __init__(self, graph, ntype):
-        self._graph = graph
-        self._ntype = ntype
-
-    def __len__(self):
-        return self._graph.number_of_nodes(self._graph._ntypes_invmap[self._ntype])
-
-    def __getitem__(self, nodes):
-        if isinstance(nodes, slice):
+    def __getitem__(self, key):
+        if isinstance(key, slice):
             # slice
-            if not (nodes.start is None and nodes.stop is None
-                    and nodes.step is None):
+            if not (key.start is None and key.stop is None
+                    and key.step is None):
                 raise DGLError('Currently only full slice ":" is supported')
-            return NodeSpace(data=HeteroNodeTypeDataView(self._graph, self._ntype, ALL))
+            nodes = ALL
+            ntype = None
+        elif isinstance(key, tuple):
+            nodes, ntype = key
+        elif isinstance(key, str):
+            nodes = ALL
+            ntype = key
         else:
-            return NodeSpace(data=HeteroNodeTypeDataView(self._graph, self._ntype, nodes))
+            nodes = key
+            ntype = None
+        return NodeSpace(data=HeteroNodeDataView(self._graph, ntype, nodes))
 
-    def __call__(self):
+    def __call__(self, ntype=None):
         """Return the nodes."""
-        return F.arange(0, len(self))
-
-class HeteroNodeTypeDataView(MutableMapping):
-    """The data view class when G.nodes[ntype][...].data is called.
+        return F.arange(0, self._graph.number_of_nodes(ntype))
 
-    See Also
-    --------
-    dgl.DGLGraph.nodes
-    """
-    __slots__ = ['_graph', '_ntype', '_nodes']
+class HeteroNodeDataView(MutableMapping):
+    """The data view class when G.ndata[ntype] is called."""
+    __slots__ = ['_graph', '_ntype', '_ntid', '_nodes']
 
     def __init__(self, graph, ntype, nodes):
         self._graph = graph
         self._ntype = ntype
+        self._ntid = self._graph.get_ntype_id(ntype)
         self._nodes = nodes
 
     def __getitem__(self, key):
-        return self._graph.get_n_repr(self._ntype, self._nodes)[key]
-
-    def __setitem__(self, key, val):
-        self._graph.set_n_repr(self._ntype, {key : val}, self._nodes)
-
-    def __delitem__(self, key):
-        raise DGLError('Delete feature data is not supported on only a subset'
-                       ' of nodes. Please use `del G.ndata[key]` instead.')
-
-    def __len__(self):
-        return len(self._graph._node_frames[self._graph._ntypes_invmap[self._ntype]])
-
-    def __iter__(self):
-        return iter(self._graph.get_n_repr(self._ntype, self._nodes))
-
-    def __repr__(self):
-        data = self._graph.get_n_repr(self._ntype, self._nodes)
-        return repr({key : data[key]
-                     for key in self._graph._node_frames[self._graph._ntypes_invmap[self._ntype]]})
-
-class HeteroNodeDataView(object):
-    """The data view class when G.ndata is called."""
-    __slots__ = ['_graph']
-
-    def __init__(self, graph):
-        self._graph = graph
-
-    def __getitem__(self, key):
-        return HeteroNodeDataTypeView(self._graph, key)
-
-class HeteroNodeDataTypeView(MutableMapping):
-    """The data view class when G.ndata[ntype] is called."""
-    __slots__ = ['_graph', '_ntype']
-
-    def __init__(self, graph, ntype):
-        self._graph = graph
-        self._ntype = ntype
-
-    def __getitem__(self, key):
-        return self._graph.get_n_repr(self._ntype)[key]
+        return self._graph._get_n_repr(self._ntid, self._nodes)[key]
 
     def __setitem__(self, key, val):
-        self._graph.set_n_repr(self._ntype, {key : val})
+        self._graph._set_n_repr(self._ntid, self._nodes, {key : val})
 
     def __delitem__(self, key):
-        self._graph.pop_n_repr(self._ntype, key)
+        self._graph._pop_n_repr(self._ntid, key)
 
     def __len__(self):
-        return len(self._graph._node_frames[self._graph._ntypes_invmap[self._ntype]])
+        return len(self._graph._node_frames[self._ntid])
 
     def __iter__(self):
-        return iter(self._graph._node_frames[self._graph._ntypes_invmap[self._ntype]])
+        return iter(self._graph._node_frames[self._ntid])
 
     def __repr__(self):
-        data = self._graph.get_n_repr(self._ntype)
+        data = self._graph._get_n_repr(self._ntid, self._nodes)
         return repr({key : data[key]
-                     for key in self._graph._node_frames[self._graph._ntypes_invmap[self._ntype]]})
+                     for key in self._graph._node_frames[self._ntid]})
 
 class HeteroEdgeView(object):
     """A EdgeView class to act as G.edges for a DGLHeteroGraph."""
@@ -369,108 +314,59 @@ class HeteroEdgeView(object):
     def __init__(self, graph):
         self._graph = graph
 
-    def __getitem__(self, etype):
-        return HeteroEdgeTypeView(self._graph, etype)
-
-class HeteroEdgeTypeView(object):
-    """A EdgeView class to act as G.edges[etype] for a DGLHeteroGraph.
-
-    See Also
-    --------
-    dgl.DGLGraph.edges
-    """
-    __slots__ = ['_graph', '_etype']
-
-    def __init__(self, graph, etype):
-        self._graph = graph
-        self._etype = etype
-
-    def __len__(self):
-        return self._graph.number_of_edges(self._graph._etypes_invmap[self._etype])
-
-    def __getitem__(self, edges):
-        if isinstance(edges, slice):
+    def __getitem__(self, key):
+        if isinstance(key, slice):
             # slice
-            if not (edges.start is None and edges.stop is None
-                    and edges.step is None):
+            if not (key.start is None and key.stop is None
+                    and key.step is None):
                 raise DGLError('Currently only full slice ":" is supported')
-            return EdgeSpace(data=HeteroEdgeTypeDataView(self._graph, self._etype, ALL))
+            edges = ALL
+            etype = None
+        elif isinstance(key, tuple):
+            if len(key) == 3:
+                edges = ALL
+                etype = key
             else:
-            return EdgeSpace(data=HeteroEdgeTypeDataView(self._graph, self._etype, edges))
-
-    def __call__(self):
-        """Return the edges."""
-        return F.arange(0, len(self))
+                edges = key
+                etype = None
+        elif isinstance(key, (str, tuple)):
+            edges = ALL
+            etype = key
+        else:
+            edges = key
+            etype = None
+        return EdgeSpace(data=HeteroEdgeDataView(self._graph, etype, edges))
 
-class HeteroEdgeTypeDataView(MutableMapping):
-    """The data view class when G.edges[etype][...].data is called.
+    def __call__(self, *args, **kwargs):
+        """Return all the edges."""
+        return self._graph.all_edges(*args, **kwargs)
 
-    See Also
-    --------
-    dgl.DGLGraph.edges
-    """
-    __slots__ = ['_graph', '_etype', '_edges']
+class HeteroEdgeDataView(MutableMapping):
+    """The data view class when G.ndata[etype] is called."""
+    __slots__ = ['_graph', '_etype', '_etid', '_edges']
 
     def __init__(self, graph, etype, edges):
         self._graph = graph
         self._etype = etype
+        self._etid = self._graph.get_etype_id(etype)
         self._edges = edges
 
     def __getitem__(self, key):
-        return self._graph.get_e_repr(self._etype, self._edges)[key]
-
-    def __setitem__(self, key, val):
-        self._graph.set_e_repr(self._etype, {key : val}, self._edges)
-
-    def __delitem__(self, key):
-        raise DGLError('Delete feature data is not supported on only a subset'
-                       ' of edges. Please use `del G.edata[key]` instead.')
-
-    def __len__(self):
-        return len(self._graph._edge_frames[self._graph._etypes_invmap[self._etype]])
-
-    def __iter__(self):
-        return iter(self._graph.get_e_repr(self._etype, self._edges))
-
-    def __repr__(self):
-        data = self._graph.get_e_repr(self._etype, self._edges)
-        return repr({key : data[key]
-                     for key in self._graph._edge_frames[self._graph._etypes_invmap[self._etype]]})
-
-class HeteroEdgeDataView(object):
-    """The data view class when G.edata is called."""
-    __slots__ = ['_graph']
-
-    def __init__(self, graph):
-        self._graph = graph
-
-    def __getitem__(self, key):
-        return HeteroEdgeDataTypeView(self._graph, key)
-
-class HeteroEdgeDataTypeView(MutableMapping):
-    """The data view class when G.edata[etype] is called."""
-    __slots__ = ['_graph', '_etype']
-
-    def __init__(self, graph, etype):
-        self._graph = graph
-        self._etype = etype
-
-    def __getitem__(self, key):
-        return self._graph.get_e_repr(self._etype)[key]
+        return self._graph._get_e_repr(self._etid, self._edges)[key]
 
     def __setitem__(self, key, val):
-        self._graph.set_e_repr(self._etype, {key : val})
+        self._graph._set_e_repr(self._etid, self._edges, {key : val})
 
     def __delitem__(self, key):
-        self._graph.pop_e_repr(self._etype, key)
+        self._graph._pop_e_repr(self._etid, key)
 
     def __len__(self):
-        return len(self._graph._edge_frames[self._graph._etypes_invmap[self._etype]])
+        return len(self._graph._edge_frames[self._etid])
 
     def __iter__(self):
-        return iter(self._graph._edge_frames[self._graph._etypes_invmap[self._etype]])
+        return iter(self._graph._edge_frames[self._etid])
 
     def __repr__(self):
-        data = self._graph.get_e_repr(self._etype)
+        data = self._graph._get_e_repr(self._etid, self._edges)
         return repr({key : data[key]
-                     for key in self._graph._edge_frames[self._graph._etypes_invmap[self._etype]]})
+                     for key in self._graph._edge_frames[self._etid]})

src/graph/heterograph.cc

@@ -4,10 +4,11 @@
  * \brief Heterograph implementation
  */
 #include "./heterograph.h"
+#include <dgl/array.h>
 #include <dgl/packed_func_ext.h>
 #include <dgl/runtime/container.h>
 #include "../c_api_common.h"
-#include "./bipartite.h"
+#include "./unit_graph.h"
 
 using namespace dgl::runtime;
 
@@ -50,7 +51,7 @@ HeteroSubgraph EdgeSubgraphNoPreserveNodes(
   // following heterograph:
   //
   // Meta graph: A -> B -> C
-  // Bipartite graphs:
+  // UnitGraph graphs:
   // * A -> B: (0, 0), (0, 1)
   // * B -> C: (1, 0), (1, 1)
   //
@@ -91,7 +92,8 @@ HeteroSubgraph EdgeSubgraphNoPreserveNodes(
     auto pair = hg->meta_graph()->FindEdge(etype);
     const dgl_type_t src_vtype = pair.first;
     const dgl_type_t dst_vtype = pair.second;
-    subrels[etype] = Bipartite::CreateFromCOO(
+    subrels[etype] = UnitGraph::CreateFromCOO(
+      (src_vtype == dst_vtype)? 1 : 2,
       ret.induced_vertices[src_vtype]->shape[0],
       ret.induced_vertices[dst_vtype]->shape[0],
       subedges[etype].src,
@@ -108,10 +110,9 @@ HeteroGraph::HeteroGraph(GraphPtr meta_graph, const std::vector<HeteroGraphPtr>&
   // Sanity check
   CHECK_EQ(meta_graph->NumEdges(), rel_graphs.size());
   CHECK(!rel_graphs.empty()) << "Empty heterograph is not allowed.";
-  // all relation graph must be bipartite graphs
+  // all relation graphs must have only one edge type
   for (const auto rg : rel_graphs) {
-    CHECK_EQ(rg->NumVertexTypes(), 2) << "Each relation graph must be a bipartite graph.";
-    CHECK_EQ(rg->NumEdgeTypes(), 1) << "Each relation graph must be a bipartite graph.";
+    CHECK_EQ(rg->NumEdgeTypes(), 1) << "Each relation graph must have only one edge type.";
   }
   // create num verts per type
   num_verts_per_type_.resize(meta_graph->NumVertices(), -1);
@@ -125,17 +126,20 @@ HeteroGraph::HeteroGraph(GraphPtr meta_graph, const std::vector<HeteroGraphPtr>&
     dgl_type_t srctype = srctypes[i];
     dgl_type_t dsttype = dsttypes[i];
     dgl_type_t etype = etypes[i];
+    const auto& rg = rel_graphs[etype];
+    const auto sty = 0;
+    const auto dty = rg->NumVertexTypes() == 1? 0 : 1;
     size_t nv;
 
     // # nodes of source type
-    nv = rel_graphs[etype]->NumVertices(Bipartite::kSrcVType);
+    nv = rg->NumVertices(sty);
     if (num_verts_per_type_[srctype] < 0)
       num_verts_per_type_[srctype] = nv;
     else
       CHECK_EQ(num_verts_per_type_[srctype], nv)
         << "Mismatch number of vertices for vertex type " << srctype;
     // # nodes of destination type
-    nv = rel_graphs[etype]->NumVertices(Bipartite::kDstVType);
+    nv = rg->NumVertices(dty);
     if (num_verts_per_type_[dsttype] < 0)
       num_verts_per_type_[dsttype] = nv;
     else
@@ -171,8 +175,10 @@ HeteroSubgraph HeteroGraph::VertexSubgraph(const std::vector<IdArray>& vids) con
     auto pair = meta_graph_->FindEdge(etype);
     const dgl_type_t src_vtype = pair.first;
     const dgl_type_t dst_vtype = pair.second;
-    const auto& rel_vsg = GetRelationGraph(etype)->VertexSubgraph(
-        {vids[src_vtype], vids[dst_vtype]});
+    const std::vector<IdArray> rel_vids = (src_vtype == dst_vtype) ?
+      std::vector<IdArray>({vids[src_vtype]}) :
+      std::vector<IdArray>({vids[src_vtype], vids[dst_vtype]});
+    const auto& rel_vsg = GetRelationGraph(etype)->VertexSubgraph(rel_vids);
     subrels[etype] = rel_vsg.graph;
     ret.induced_edges[etype] = rel_vsg.induced_edges[0];
   }
@@ -189,18 +195,106 @@ HeteroSubgraph HeteroGraph::EdgeSubgraph(
   }
 }
 
-// creator implementation
-HeteroGraphPtr CreateBipartiteFromCOO(
-    int64_t num_src, int64_t num_dst, IdArray row, IdArray col) {
-  return Bipartite::CreateFromCOO(num_src, num_dst, row, col);
-}
+FlattenedHeteroGraphPtr HeteroGraph::Flatten(const std::vector<dgl_type_t>& etypes) const {
+  std::unordered_map<dgl_type_t, size_t> srctype_offsets, dsttype_offsets;
+  size_t src_nodes = 0, dst_nodes = 0;
+  std::vector<dgl_id_t> result_src, result_dst;
+  std::vector<dgl_type_t> induced_srctype, induced_etype, induced_dsttype;
+  std::vector<dgl_id_t> induced_srcid, induced_eid, induced_dstid;
+  std::vector<dgl_type_t> srctype_set, dsttype_set;
+
+  // XXXtype_offsets contain the mapping from node type and number of nodes after this
+  // loop.
+  for (dgl_type_t etype : etypes) {
+    auto src_dsttype = meta_graph_->FindEdge(etype);
+    dgl_type_t srctype = src_dsttype.first;
+    dgl_type_t dsttype = src_dsttype.second;
+    size_t num_srctype_nodes = NumVertices(srctype);
+    size_t num_dsttype_nodes = NumVertices(dsttype);
+
+    if (srctype_offsets.count(srctype) == 0) {
+      srctype_offsets[srctype] = num_srctype_nodes;
+      srctype_set.push_back(srctype);
+    }
+    if (dsttype_offsets.count(dsttype) == 0) {
+      dsttype_offsets[dsttype] = num_dsttype_nodes;
+      dsttype_set.push_back(dsttype);
+    }
+  }
 
-HeteroGraphPtr CreateBipartiteFromCSR(
-    int64_t num_src, int64_t num_dst,
-    IdArray indptr, IdArray indices, IdArray edge_ids) {
-  return Bipartite::CreateFromCSR(num_src, num_dst, indptr, indices, edge_ids);
+  // Sort the node types so that we can compare the sets and decide whether a homograph
+  // should be returned.
+  std::sort(srctype_set.begin(), srctype_set.end());
+  std::sort(dsttype_set.begin(), dsttype_set.end());
+  bool homograph = (srctype_set.size() == dsttype_set.size()) &&
+    std::equal(srctype_set.begin(), srctype_set.end(), dsttype_set.begin());
+
+  // XXXtype_offsets contain the mapping from node type to node ID offsets after these
+  // two loops.
+  for (size_t i = 0; i < srctype_set.size(); ++i) {
+    dgl_type_t ntype = srctype_set[i];
+    size_t num_nodes = srctype_offsets[ntype];
+    srctype_offsets[ntype] = src_nodes;
+    src_nodes += num_nodes;
+    for (size_t j = 0; j < num_nodes; ++j) {
+      induced_srctype.push_back(ntype);
+      induced_srcid.push_back(j);
+    }
+  }
+  for (size_t i = 0; i < dsttype_set.size(); ++i) {
+    dgl_type_t ntype = dsttype_set[i];
+    size_t num_nodes = dsttype_offsets[ntype];
+    dsttype_offsets[ntype] = dst_nodes;
+    dst_nodes += num_nodes;
+    for (size_t j = 0; j < num_nodes; ++j) {
+      induced_dsttype.push_back(ntype);
+      induced_dstid.push_back(j);
+    }
+  }
+
+  for (dgl_type_t etype : etypes) {
+    auto src_dsttype = meta_graph_->FindEdge(etype);
+    dgl_type_t srctype = src_dsttype.first;
+    dgl_type_t dsttype = src_dsttype.second;
+    size_t srctype_offset = srctype_offsets[srctype];
+    size_t dsttype_offset = dsttype_offsets[dsttype];
+
+    EdgeArray edges = Edges(etype);
+    size_t num_edges = NumEdges(etype);
+    const dgl_id_t* edges_src_data = static_cast<const dgl_id_t*>(edges.src->data);
+    const dgl_id_t* edges_dst_data = static_cast<const dgl_id_t*>(edges.dst->data);
+    const dgl_id_t* edges_eid_data = static_cast<const dgl_id_t*>(edges.id->data);
+    // TODO(gq) Use concat?
+    for (size_t i = 0; i < num_edges; ++i) {
+      result_src.push_back(edges_src_data[i] + srctype_offset);
+      result_dst.push_back(edges_dst_data[i] + dsttype_offset);
+      induced_etype.push_back(etype);
+      induced_eid.push_back(edges_eid_data[i]);
+    }
+  }
+
+  HeteroGraphPtr gptr = UnitGraph::CreateFromCOO(
+      homograph ? 1 : 2,
+      src_nodes,
+      dst_nodes,
+      aten::VecToIdArray(result_src),
+      aten::VecToIdArray(result_dst));
+
+  FlattenedHeteroGraph* result = new FlattenedHeteroGraph;
+  result->graph = HeteroGraphRef(gptr);
+  result->induced_srctype = aten::VecToIdArray(induced_srctype);
+  result->induced_srctype_set = aten::VecToIdArray(srctype_set);
+  result->induced_srcid = aten::VecToIdArray(induced_srcid);
+  result->induced_etype = aten::VecToIdArray(induced_etype);
+  result->induced_etype_set = aten::VecToIdArray(etypes);
+  result->induced_eid = aten::VecToIdArray(induced_eid);
+  result->induced_dsttype = aten::VecToIdArray(induced_dsttype);
+  result->induced_dsttype_set = aten::VecToIdArray(dsttype_set);
+  result->induced_dstid = aten::VecToIdArray(induced_dstid);
+  return FlattenedHeteroGraphPtr(result);
 }
 
+// creator implementation
 HeteroGraphPtr CreateHeteroGraph(
     GraphPtr meta_graph, const std::vector<HeteroGraphPtr>& rel_graphs) {
   return HeteroGraphPtr(new HeteroGraph(meta_graph, rel_graphs));
@@ -208,24 +302,27 @@ HeteroGraphPtr CreateHeteroGraph(
 
 ///////////////////////// C APIs /////////////////////////
 
-DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroCreateBipartiteFromCOO")
+DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroCreateUnitGraphFromCOO")
 .set_body([] (DGLArgs args, DGLRetValue* rv) {
-    int64_t num_src = args[0];
-    int64_t num_dst = args[1];
-    IdArray row = args[2];
-    IdArray col = args[3];
-    auto hgptr = CreateBipartiteFromCOO(num_src, num_dst, row, col);
+    int64_t nvtypes = args[0];
+    int64_t num_src = args[1];
+    int64_t num_dst = args[2];
+    IdArray row = args[3];
+    IdArray col = args[4];
+    auto hgptr = UnitGraph::CreateFromCOO(nvtypes, num_src, num_dst, row, col);
     *rv = HeteroGraphRef(hgptr);
   });
 
-DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroCreateBipartiteFromCSR")
+DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroCreateUnitGraphFromCSR")
 .set_body([] (DGLArgs args, DGLRetValue* rv) {
-    int64_t num_src = args[0];
-    int64_t num_dst = args[1];
-    IdArray indptr = args[2];
-    IdArray indices = args[3];
-    IdArray edge_ids = args[4];
-    auto hgptr = CreateBipartiteFromCSR(num_src, num_dst, indptr, indices, edge_ids);
+    int64_t nvtypes = args[0];
+    int64_t num_src = args[1];
+    int64_t num_dst = args[2];
+    IdArray indptr = args[3];
+    IdArray indices = args[4];
+    IdArray edge_ids = args[5];
+    auto hgptr = UnitGraph::CreateFromCSR(
+        nvtypes, num_src, num_dst, indptr, indices, edge_ids);
     *rv = HeteroGraphRef(hgptr);
   });
 
@@ -252,7 +349,23 @@ DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroGetRelationGraph")
 .set_body([] (DGLArgs args, DGLRetValue* rv) {
     HeteroGraphRef hg = args[0];
     dgl_type_t etype = args[1];
+    if (hg->NumEdgeTypes() == 1) {
+      CHECK_EQ(etype, 0);
+      *rv = hg;
+    } else {
       *rv = HeteroGraphRef(hg->GetRelationGraph(etype));
+    }
+  });
+
+DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroGetFlattenedGraph")
+.set_body([] (DGLArgs args, DGLRetValue* rv) {
+    HeteroGraphRef hg = args[0];
+    List<Value> etypes = args[1];
+    std::vector<dgl_id_t> etypes_vec;
+    for (Value val : etypes)
+      etypes_vec.push_back(val->data);
+
+    *rv = FlattenedHeteroGraphRef(hg->Flatten(etypes_vec));
   });
 
 DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroAddVertices")
@@ -551,7 +664,7 @@ DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroAsNumBits")
 .set_body([] (DGLArgs args, DGLRetValue* rv) {
     HeteroGraphRef hg = args[0];
     int bits = args[1];
-    HeteroGraphPtr hg_new = Bipartite::AsNumBits(hg.sptr(), bits);
+    HeteroGraphPtr hg_new = UnitGraph::AsNumBits(hg.sptr(), bits);
     *rv = HeteroGraphRef(hg_new);
   });
 
@@ -563,7 +676,7 @@ DGL_REGISTER_GLOBAL("heterograph_index._CAPI_DGLHeteroCopyTo")
     DLContext ctx;
     ctx.device_type = static_cast<DLDeviceType>(device_type);
     ctx.device_id = device_id;
-    HeteroGraphPtr hg_new = Bipartite::CopyTo(hg.sptr(), ctx);
+    HeteroGraphPtr hg_new = UnitGraph::CopyTo(hg.sptr(), ctx);
     *rv = HeteroGraphRef(hg_new);
   });
 

src/graph/heterograph.h

@@ -20,14 +20,6 @@ class HeteroGraph : public BaseHeteroGraph {
  public:
   HeteroGraph(GraphPtr meta_graph, const std::vector<HeteroGraphPtr>& rel_graphs);
 
-  uint64_t NumVertexTypes() const override {
-    return meta_graph_->NumVertices();
-  }
-
-  uint64_t NumEdgeTypes() const override {
-    return meta_graph_->NumEdges();
-  }
-
   HeteroGraphPtr GetRelationGraph(dgl_type_t etype) const override {
     CHECK_LT(etype, meta_graph_->NumEdges()) << "Invalid edge type: " << etype;
     return relation_graphs_[etype];
@@ -172,8 +164,10 @@ class HeteroGraph : public BaseHeteroGraph {
   HeteroSubgraph EdgeSubgraph(
       const std::vector<IdArray>& eids, bool preserve_nodes = false) const override;
 
+  FlattenedHeteroGraphPtr Flatten(const std::vector<dgl_type_t>& etypes) const override;
+
  private:
-  /*! \brief A map from edge type to bipartite graph */
+  /*! \brief A map from edge type to unit graph */
   std::vector<HeteroGraphPtr> relation_graphs_;
 
   /*! \brief A map from vert type to the number of verts in the type */