[GraphBolt] Add functional name into docstring (#6739)

python/dgl/graphbolt/base.py

@@ -104,6 +104,8 @@ class CopyTo(IterDataPipe):
     """DataPipe that transfers each element yielded from the previous DataPipe
     to the given device.
 
+    Functional name: :obj:`copy_to`.
+
     This is equivalent to
 
     .. code:: python

python/dgl/graphbolt/feature_fetcher.py

@@ -16,17 +16,9 @@ __all__ = [
 
 @functional_datapipe("fetch_feature")
 class FeatureFetcher(MiniBatchTransformer):
-    """A feature fetcher used to fetch features for node/edge in graphbolt."""
+    """A feature fetcher used to fetch features for node/edge in graphbolt.
 
-    def __init__(
-        self,
-        datapipe,
-        feature_store,
-        node_feature_keys=None,
-        edge_feature_keys=None,
-    ):
-        """
-        Initlization for a feature fetcher.
+    Functional name: :obj:`fetch_feature`.
 
     Parameters
     ----------
@@ -48,6 +40,14 @@ class FeatureFetcher(MiniBatchTransformer):
         following the format 'str:str:str', and the values are lists of
         feature names.
     """
+
+    def __init__(
+        self,
+        datapipe,
+        feature_store,
+        node_feature_keys=None,
+        edge_feature_keys=None,
+    ):
         super().__init__(datapipe, self._read)
         self.feature_store = feature_store
         self.node_feature_keys = node_feature_keys

python/dgl/graphbolt/impl/in_subgraph_sampler.py

@@ -15,6 +15,8 @@ __all__ = ["InSubgraphSampler"]
 class InSubgraphSampler(SubgraphSampler):
     """Sample the subgraph induced on the inbound edges of the given nodes.
 
+    Functional name: :obj:`sample_in_subgraph`.
+
     In-subgraph sampler is responsible for sampling a subgraph from given data,
     returning an induced subgraph along with compacted information.
 

python/dgl/graphbolt/impl/neighbor_sampler.py

@@ -20,6 +20,8 @@ __all__ = ["NeighborSampler", "LayerNeighborSampler"]
 class NeighborSampler(SubgraphSampler):
     """Sample neighbor edges from a graph and return a subgraph.
 
+    Functional name: :obj:`sample_neighbor`.
+
     Neighbor sampler is responsible for sampling a subgraph from given data. It
     returns an induced subgraph along with compacted information. In the
     context of a node classification task, the neighbor sampler directly
@@ -183,6 +185,8 @@ class NeighborSampler(SubgraphSampler):
 class LayerNeighborSampler(NeighborSampler):
     """Sample layer neighbor edges from a graph and return a subgraph.
 
+    Functional name: :obj:`sample_layer_neighbor`.
+
     Sampler that builds computational dependency of node representations via
     labor sampling for multilayer GNN from the NeurIPS 2023 paper
     `Layer-Neighbor Sampling -- Defusing Neighborhood Explosion in GNNs

python/dgl/graphbolt/impl/uniform_negative_sampler.py

@@ -12,6 +12,8 @@ class UniformNegativeSampler(NegativeSampler):
     """Sample negative destination nodes for each source node based on a uniform
     distribution.
 
+    Functional name: :obj:`sample_uniform_negative`.
+
     It's important to note that the term 'negative' refers to false negatives,
     indicating that the sampled pairs are not ensured to be absent in the graph.
     For each edge ``(u, v)``, it is supposed to generate `negative_ratio` pairs

python/dgl/graphbolt/minibatch_transformer.py

@@ -14,15 +14,10 @@ __all__ = [
 
 @functional_datapipe("transform")
 class MiniBatchTransformer(Mapper):
-    """A mini-batch transformer used to manipulate mini-batch"""
+    """A mini-batch transformer used to manipulate mini-batch.
+
+    Functional name: :obj:`transform`.
 
-    def __init__(
-        self,
-        datapipe,
-        transformer,
-    ):
-        """
-        Initlization for a subgraph transformer.
     Parameters
     ----------
     datapipe : DataPipe
@@ -31,6 +26,12 @@ class MiniBatchTransformer(Mapper):
         The function applied to each minibatch which is responsible for
         transforming the minibatch.
     """
+
+    def __init__(
+        self,
+        datapipe,
+        transformer,
+    ):
         super().__init__(datapipe, self._transformer)
         self.transformer = transformer
 
@@ -44,17 +45,18 @@ class MiniBatchTransformer(Mapper):
 
 @functional_datapipe("to_dgl")
 class DGLMiniBatchConverter(Mapper):
-    """Convert a graphbolt mini-batch to a dgl mini-batch."""
+    """Convert a graphbolt mini-batch to a dgl mini-batch.
+
+    Functional name: :obj:`to_dgl`.
 
-    def __init__(
-        self,
-        datapipe,
-    ):
-        """
-        Initlization for a subgraph transformer.
     Parameters
     ----------
     datapipe : DataPipe
         The datapipe.
     """
+
+    def __init__(
+        self,
+        datapipe,
+    ):
         super().__init__(datapipe, MiniBatch.to_dgl)

python/dgl/graphbolt/negative_sampler.py

@@ -16,15 +16,8 @@ class NegativeSampler(MiniBatchTransformer):
     """
     A negative sampler used to generate negative samples and return
     a mix of positive and negative samples.
-    """
 
-    def __init__(
-        self,
-        datapipe,
-        negative_ratio,
-    ):
-        """
-        Initlization for a negative sampler.
+    Functional name: :obj:`sample_negative`.
 
     Parameters
     ----------
@@ -33,6 +26,12 @@ class NegativeSampler(MiniBatchTransformer):
     negative_ratio : int
         The proportion of negative samples to positive samples.
     """
+
+    def __init__(
+        self,
+        datapipe,
+        negative_ratio,
+    ):
         super().__init__(datapipe, self._sample)
         assert negative_ratio > 0, "Negative_ratio should be positive Integer."
         self.negative_ratio = negative_ratio

python/dgl/graphbolt/subgraph_sampler.py

@@ -17,20 +17,20 @@ __all__ = [
 @functional_datapipe("sample_subgraph")
 class SubgraphSampler(MiniBatchTransformer):
     """A subgraph sampler used to sample a subgraph from a given set of nodes
-    from a larger graph."""
+    from a larger graph.
 
-    def __init__(
-        self,
-        datapipe,
-    ):
-        """
-        Initlization for a subgraph sampler.
+    Functional name: :obj:`sample_subgraph`.
 
     Parameters
     ----------
     datapipe : DataPipe
         The datapipe.
     """
+
+    def __init__(
+        self,
+        datapipe,
+    ):
         super().__init__(datapipe, self._sample)
 
     def _sample(self, minibatch):