[GraphBolt] Remove coo from neighborsampler. (#6844)

Co-authored-by: Ubuntu <ubuntu@ip-172-31-0-133.us-west-2.compute.internal>

python/dgl/graphbolt/impl/neighbor_sampler.py

@@ -3,14 +3,10 @@
 import torch
 from torch.utils.data import functional_datapipe
 
-from ..internal import (
-    compact_csc_format,
-    unique_and_compact_csc_formats,
-    unique_and_compact_node_pairs,
-)
+from ..internal import compact_csc_format, unique_and_compact_csc_formats
 
 from ..subgraph_sampler import SubgraphSampler
-from .sampled_subgraph_impl import FusedSampledSubgraphImpl, SampledSubgraphImpl
+from .sampled_subgraph_impl import SampledSubgraphImpl
 
 
 __all__ = ["NeighborSampler", "LayerNeighborSampler"]
@@ -102,8 +98,6 @@ class NeighborSampler(SubgraphSampler):
         replace=False,
         prob_name=None,
         deduplicate=True,
-        # TODO: clean up once the migration is done.
-        output_cscformat=True,
     ):
         super().__init__(datapipe)
         self.graph = graph
@@ -116,7 +110,6 @@ class NeighborSampler(SubgraphSampler):
         self.replace = replace
         self.prob_name = prob_name
         self.deduplicate = deduplicate
-        self.output_cscformat = output_cscformat
         self.sampler = graph.sample_neighbors
 
     def sample_subgraphs(self, seeds):
@@ -135,35 +128,18 @@ class NeighborSampler(SubgraphSampler):
                 self.fanouts[hop],
                 self.replace,
                 self.prob_name,
-                not self.deduplicate or self.output_cscformat,
             )
             if self.deduplicate:
-                if self.output_cscformat:
                 (
                     original_row_node_ids,
                     compacted_csc_format,
-                    ) = unique_and_compact_csc_formats(
-                        subgraph.sampled_csc, seeds
-                    )
+                ) = unique_and_compact_csc_formats(subgraph.sampled_csc, seeds)
                 subgraph = SampledSubgraphImpl(
                     sampled_csc=compacted_csc_format,
                     original_column_node_ids=seeds,
                     original_row_node_ids=original_row_node_ids,
                     original_edge_ids=subgraph.original_edge_ids,
                 )
-                else:
-                    (
-                        original_row_node_ids,
-                        compacted_node_pairs,
-                    ) = unique_and_compact_node_pairs(
-                        subgraph.sampled_csc, seeds
-                    )
-                    subgraph = FusedSampledSubgraphImpl(
-                        sampled_csc=compacted_node_pairs,
-                        original_column_node_ids=seeds,
-                        original_row_node_ids=original_row_node_ids,
-                        original_edge_ids=subgraph.original_edge_ids,
-                    )
             else:
                 (
                     original_row_node_ids,
@@ -279,8 +255,6 @@ class LayerNeighborSampler(NeighborSampler):
         replace=False,
         prob_name=None,
         deduplicate=True,
-        # TODO: clean up once the migration is done.
-        output_cscformat=True,
     ):
         super().__init__(
             datapipe,
@@ -289,6 +263,5 @@ class LayerNeighborSampler(NeighborSampler):
             replace,
             prob_name,
             deduplicate,
-            output_cscformat,
         )
         self.sampler = graph.sample_layer_neighbors

tests/python/pytorch/graphbolt/test_subgraph_sampler.py

@@ -402,7 +402,6 @@ def test_SubgraphSampler_unique_csc_format_Homo(labor):
         fanouts,
         replace=False,
         deduplicate=True,
-        output_cscformat=True,
     )
 
     original_row_node_ids = [
@@ -450,7 +449,6 @@ def test_SubgraphSampler_unique_csc_format_Hetero(labor):
         graph,
         fanouts,
         deduplicate=True,
-        output_cscformat=True,
     )
     csc_formats = [
         {