Refactor to use traverse_dps instead of traverse

test/test_dataloader2.py

@@ -9,15 +9,15 @@
 import unittest
 from unittest import TestCase
 
-from torch.utils.data.graph import DataPipe
-
 from torchdata.dataloader2 import (
     DataLoader2,
     MultiProcessingReadingService,
     PrototypeMultiProcessingReadingService,
     ReadingServiceInterface,
 )
 from torchdata.dataloader2.dataloader2 import READING_SERVICE_STATE_KEY_NAME, SERIALIZED_DATAPIPE_KEY_NAME
+
+from torchdata.dataloader2.graph import DataPipe
 from torchdata.datapipes.iter import IterableWrapper, IterDataPipe
 
 

test/test_graph.py

@@ -13,7 +13,7 @@
 from _utils._common_utils_for_test import IS_WINDOWS
 from torch.utils.data import IterDataPipe
 from torchdata.dataloader2 import DataLoader2, MultiProcessingReadingService, ReadingServiceInterface
-from torchdata.dataloader2.graph import find_dps, remove_dp, replace_dp, traverse
+from torchdata.dataloader2.graph import find_dps, remove_dp, replace_dp, traverse_dps
 from torchdata.datapipes.iter import IterableWrapper, Mapper
 
 T_co = TypeVar("T_co", covariant=True)
@@ -37,7 +37,7 @@ class TempReadingService(ReadingServiceInterface):
     adaptors: List[IterDataPipe] = []
 
     def initialize(self, datapipe: IterDataPipe) -> IterDataPipe:
-        graph = traverse(datapipe, only_datapipe=True)
+        graph = traverse_dps(datapipe)
         dps = find_dps(graph, Mapper)
 
         for dp in reversed(dps):
@@ -78,7 +78,7 @@ def _get_datapipes(self) -> Tuple[IterDataPipe, IterDataPipe, IterDataPipe]:
         m2 = c1.map(_x_mult_2)
         dp = m2.zip(c2)
 
-        return traverse(dp, only_datapipe=True), (src_dp, m1, ub, dm, c1, c2, m2, dp)
+        return traverse_dps(dp), (src_dp, m1, ub, dm, c1, c2, m2, dp)
 
     def test_find_dps(self) -> None:
         graph, (_, m1, *_, m2, _) = self._get_datapipes()  # pyre-ignore
@@ -123,7 +123,7 @@ def test_replace_dps(self) -> None:
                 ],
             ]
         ]
-        self._validate_graph(traverse(dp, only_datapipe=True), exp_g1)
+        self._validate_graph(traverse_dps(dp), exp_g1)
 
         graph = replace_dp(graph, m2, new_dp2)
         exp_g2 = [
@@ -135,7 +135,7 @@ def test_replace_dps(self) -> None:
                 ],
             ]
         ]
-        self._validate_graph(traverse(dp, only_datapipe=True), exp_g2)
+        self._validate_graph(traverse_dps(dp), exp_g2)
 
         graph = replace_dp(graph, m1, new_dp3)
         exp_g3 = [
@@ -147,7 +147,7 @@ def test_replace_dps(self) -> None:
                 ],
             ]
         ]
-        self._validate_graph(traverse(dp, only_datapipe=True), exp_g3)
+        self._validate_graph(traverse_dps(dp), exp_g3)
 
     def test_remove_dps(self) -> None:
         # pyre-fixme[23]: Unable to unpack 3 values, 2 were expected.
@@ -164,11 +164,11 @@ def test_remove_dps(self) -> None:
 
         graph = remove_dp(graph, m1)
         exp_g1 = [[dp, [[m2, [[c1, [[dm, [[ub, [[src_dp, []]]]]]]]]], [c2, [[dm, [[ub, [[src_dp, []]]]]]]]]]]
-        self._validate_graph(traverse(dp, only_datapipe=True), exp_g1)
+        self._validate_graph(traverse_dps(dp), exp_g1)
 
         graph = remove_dp(graph, m2)
         exp_g2 = [[dp, [[c1, [[dm, [[ub, [[src_dp, []]]]]]]], [c2, [[dm, [[ub, [[src_dp, []]]]]]]]]]]
-        self._validate_graph(traverse(dp, only_datapipe=True), exp_g2)
+        self._validate_graph(traverse_dps(dp), exp_g2)
 
         with self.assertRaisesRegex(RuntimeError, "Cannot remove the source DataPipe"):
             remove_dp(graph, src_dp)

torchdata/dataloader2/adapter.py

@@ -8,7 +8,7 @@
 
 import torch
 
-from torch.utils.data.graph import DataPipe
+from torchdata.dataloader2.graph import DataPipe, traverse_dps
 from torchdata.datapipes.iter.util.cacheholder import _WaitPendingCacheItemIterDataPipe
 
 
@@ -68,7 +68,7 @@ def __init__(self, timeout=None):
         self.timeout = timeout
 
     def __call__(self, datapipe: DataPipe) -> DataPipe:
-        graph = torch.utils.data.graph.traverse(datapipe, only_datapipe=True)
+        graph = traverse_dps(datapipe)
         all_pipes = torch.utils.data.graph_settings.get_all_graph_pipes(graph)
         cache_locks = {pipe for pipe in all_pipes if isinstance(pipe, _WaitPendingCacheItemIterDataPipe)}
 

torchdata/dataloader2/dataloader2.py

@@ -9,10 +9,10 @@
 from dataclasses import dataclass
 from typing import Any, Dict, Generic, Iterable, Iterator, Optional, TypeVar, Union
 
-from torch.utils.data.graph import DataPipe
-
 from torchdata.dataloader2.adapter import Adapter
 
+from torchdata.dataloader2.graph import DataPipe
+
 from .error import PauseIteration
 from .reading_service import CheckpointableReadingServiceInterface, ReadingServiceInterface
 

torchdata/dataloader2/graph.py

@@ -7,7 +7,7 @@
 
 from typing import List, Type
 
-from torch.utils.data.graph import DataPipe, DataPipeGraph, traverse
+from torch.utils.data.graph import DataPipe, DataPipeGraph, traverse_dps
 
 from torchdata.datapipes.iter import IterDataPipe
 from torchdata.datapipes.map import MapDataPipe
@@ -18,7 +18,7 @@
 
 def find_dps(graph: DataPipeGraph, dp_type: Type[DataPipe]) -> List[DataPipe]:
     r"""
-    Given the graph of DataPipe generated by ``traverse`` function, return DataPipe
+    Given the graph of DataPipe generated by ``traverse_dps`` function, return DataPipe
     instances with the provided DataPipe type.
     """
     dps: List[DataPipe] = []
@@ -37,33 +37,33 @@ def helper(g) -> None:  # pyre-ignore
 # Given the DataPipe needs to be replaced and the expected DataPipe, return a new graph
 def replace_dp(graph: DataPipeGraph, old_datapipe: DataPipe, new_datapipe: DataPipe) -> DataPipeGraph:
     r"""
-    Given the graph of DataPipe generated by ``traverse`` function and the DataPipe to be replaced and
+    Given the graph of DataPipe generated by ``traverse_dps`` function and the DataPipe to be replaced and
     the new DataPipe, return the new graph of DataPipe.
     """
     assert len(graph) == 1
 
     if id(old_datapipe) in graph:
-        graph = traverse(new_datapipe, only_datapipe=True)
+        graph = traverse_dps(new_datapipe)
 
     final_datapipe = list(graph.values())[0][0]
 
     for recv_dp, send_graph in graph.values():
         _replace_dp(recv_dp, send_graph, old_datapipe, new_datapipe)
 
-    return traverse(final_datapipe, only_datapipe=True)
+    return traverse_dps(final_datapipe)
 
 
 def remove_dp(graph: DataPipeGraph, datapipe: DataPipe) -> DataPipeGraph:
     r"""
-    Given the graph of DataPipe generated by ``traverse`` function and the DataPipe to be removed,
+    Given the graph of DataPipe generated by ``traverse_dps`` function and the DataPipe to be removed,
     return the new graph of DataPipe.
 
     Note:
         - This function can not remove DataPipe that takes multiple DataPipes as the input.
     """
     assert len(graph) == 1
 
-    dp_graph = traverse(datapipe, only_datapipe=True)
+    dp_graph = traverse_dps(datapipe)
     dp_id = id(datapipe)
     if len(dp_graph[dp_id][1]) == 0:
         raise RuntimeError("Cannot remove the source DataPipe from the graph of DataPipe")
@@ -80,7 +80,7 @@ def remove_dp(graph: DataPipeGraph, datapipe: DataPipe) -> DataPipeGraph:
     assert len(graph) == 1
     datapipe = list(graph.values())[0][0]
 
-    return traverse(datapipe, only_datapipe=True)
+    return traverse_dps(datapipe)
 
 
 # For each `recv_dp`, find if the source_datapipe needs to be replaced by the new one.

torchdata/dataloader2/linter.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-from torch.utils.data.graph import DataPipe, DataPipeGraph, traverse
+from torchdata.dataloader2.graph import DataPipe, DataPipeGraph, traverse_dps
 
 from torchdata.datapipes.iter import ShardingFilter, Shuffler
 
@@ -14,7 +14,7 @@ def _check_shuffle_before_sharding(datapipe: DataPipe) -> bool:
     This function will check if a ``shuffle`` operation is presented before each
     ``sharding_filter`` operation for every single path in the ``DataPipe`` graph.
     """
-    graph: DataPipeGraph = traverse(datapipe)  # type: ignore[arg-type]
+    graph: DataPipeGraph = traverse_dps(datapipe)  # type: ignore[arg-type]
     return _check_shuffler_before_sharding_helper(graph)
 
 

torchdata/dataloader2/reading_service.py

@@ -17,10 +17,10 @@
 import torch.distributed as dist
 
 from torch.utils.data import DataLoader
-from torch.utils.data.graph import DataPipe
 
 from torchdata._constants import default_timeout_in_s
 from torchdata.dataloader2 import communication
+from torchdata.dataloader2.graph import DataPipe
 from torchdata.datapipes.iter import FullSync, IterableWrapper
 
 

torchdata/datapipes/iter/util/cacheholder.py

@@ -28,7 +28,7 @@
 
 from torch.utils.data.datapipes.utils.common import _check_unpickable_fn, DILL_AVAILABLE
 
-from torch.utils.data.graph import traverse
+from torch.utils.data.graph import traverse_dps
 from torchdata.datapipes import functional_datapipe
 from torchdata.datapipes.iter import FileLister, IterDataPipe
 
@@ -396,7 +396,7 @@ def __new__(cls, datapipe, mode="wb", filepath_fn=None, *, same_filepath_fn=Fals
         if filepath_fn is not None and same_filepath_fn:
             raise ValueError("`filepath_fn` is mutually exclusive with `same_filepath_fn`")
 
-        graph = traverse(datapipe, only_datapipe=True)
+        graph = traverse_dps(datapipe)
         # Get the last CacheHolder
         cache_holder = EndOnDiskCacheHolderIterDataPipe._recursive_search(graph)
         if cache_holder is None:

torchdata/datapipes/utils/_visualization.py

@@ -10,7 +10,7 @@
 from typing import Optional, Set, TYPE_CHECKING
 
 from torch.utils.data.datapipes.iter.combining import _ChildDataPipe, IterDataPipe
-from torch.utils.data.graph import traverse
+from torch.utils.data.graph import traverse_dps
 
 if TYPE_CHECKING:
     import graphviz
@@ -117,7 +117,7 @@ def aggregate(nodes):
 
         return nodes
 
-    return aggregate(recurse(traverse(dp, only_datapipe=True)))
+    return aggregate(recurse(traverse_dps(dp)))
 
 
 def to_graph(dp, *, debug: bool = False) -> "graphviz.Digraph":