Merge branch 'master' into structural-shifts

tests/go/test_model.py

@@ -1,7 +1,7 @@
 import dgl
 import pytest
 import torch
-from test_utils.graph_cases import get_cases
+from pytests_utils.graph_cases import get_cases
 from dglgo.model import *
 
 

tests/python/common/dataloading/test_dataloader.py

@@ -8,7 +8,7 @@
     negative_sampler,
     NeighborSampler,
 )
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def create_test_graph(idtype):

tests/python/common/function/test_basics.py

@@ -8,7 +8,7 @@
 import numpy as np
 import scipy.sparse as ssp
 from dgl import DGLGraph
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 D = 5
 reduce_msg_shapes = set()

tests/python/common/ops/test_edge_softmax.py

@@ -10,12 +10,12 @@
 import networkx as nx
 import numpy as np
 import pytest
+import pytests_utils
 import scipy.sparse as ssp
-import test_utils
 from dgl import DGLError
 from dgl.ops import edge_softmax
+from pytests_utils import get_cases, parametrize_idtype
 from scipy.sparse import rand
-from test_utils import get_cases, parametrize_idtype
 
 edge_softmax_shapes = [(1,), (1, 3), (3, 4, 5)]
 rfuncs = {"sum": fn.sum, "max": fn.max, "min": fn.min, "mean": fn.mean}

tests/python/common/ops/test_ops.py

@@ -8,8 +8,8 @@
 import pytest
 import torch
 from dgl.ops import gather_mm, gsddmm, gspmm, segment_reduce
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import get_cases
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import get_cases
 
 random.seed(42)
 np.random.seed(42)

tests/python/common/test_batch-graph.py

@@ -4,7 +4,7 @@
 
 import dgl
 import numpy as np
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def tree1(idtype):

tests/python/common/test_batch-heterograph.py

@@ -5,7 +5,7 @@
 import dgl
 import pytest
 from dgl.base import ALL
-from test_utils import check_graph_equal, get_cases, parametrize_idtype
+from pytests_utils import check_graph_equal, get_cases, parametrize_idtype
 
 
 def check_equivalence_between_heterographs(

tests/python/common/test_frame.py

@@ -7,7 +7,7 @@
 import dgl.ndarray as nd
 import numpy as np
 from dgl.frame import Column
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def test_column_subcolumn():

tests/python/common/test_heterograph-apply-edges.py

@@ -10,11 +10,11 @@
 import networkx as nx
 import numpy as np
 import pytest
+import pytests_utils
 import scipy.sparse as ssp
-import test_utils
 from dgl import DGLError
+from pytests_utils import get_cases, parametrize_idtype
 from scipy.sparse import rand
-from test_utils import get_cases, parametrize_idtype
 
 rfuncs = {"sum": fn.sum, "max": fn.max, "min": fn.min, "mean": fn.mean}
 fill_value = {"sum": 0, "max": float("-inf")}

tests/python/common/test_heterograph-kernel.py

@@ -7,7 +7,7 @@
 import networkx as nx
 import numpy as np
 import pytest
-from test_utils import get_cases, parametrize_idtype
+from pytests_utils import get_cases, parametrize_idtype
 
 
 def udf_copy_src(edges):

tests/python/common/test_heterograph-pickle.py

@@ -8,11 +8,11 @@
 import dgl.function as fn
 import networkx as nx
 import pytest
+import pytests_utils
 import scipy.sparse as ssp
-import test_utils
 from dgl.graph_index import create_graph_index
 from dgl.utils import toindex
-from test_utils import get_cases, parametrize_idtype
+from pytests_utils import get_cases, parametrize_idtype
 from utils import assert_is_identical, assert_is_identical_hetero
 
 
@@ -110,7 +110,7 @@ def _global_message_func(nodes):
 def test_pickling_graph(g, idtype):
     g = g.astype(idtype)
     new_g = _reconstruct_pickle(g)
-    test_utils.check_graph_equal(g, new_g, check_feature=True)
+    pytests_utils.check_graph_equal(g, new_g, check_feature=True)
 
 
 @unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
@@ -142,7 +142,7 @@ def test_pickling_batched_heterograph():
 
     bg = dgl.batch([g, g2])
     new_bg = _reconstruct_pickle(bg)
-    test_utils.check_graph_equal(bg, new_bg)
+    pytests_utils.check_graph_equal(bg, new_bg)
 
 
 @unittest.skipIf(

tests/python/common/test_heterograph-remove.py

@@ -2,7 +2,7 @@
 
 import dgl
 import numpy as np
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @parametrize_idtype

tests/python/common/test_heterograph-shared-memory.py

@@ -12,7 +12,7 @@
 import scipy.sparse as ssp
 from dgl.graph_index import create_graph_index
 from dgl.utils import toindex
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def create_test_graph(idtype):

tests/python/common/test_heterograph-specialization.py

@@ -4,7 +4,7 @@
 import dgl.function as fn
 import numpy as np
 import scipy.sparse as sp
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 D = 5
 

tests/python/common/test_heterograph-update-all.py

@@ -10,11 +10,11 @@
 import networkx as nx
 import numpy as np
 import pytest
+import pytests_utils
 import scipy.sparse as ssp
-import test_utils
 from dgl import DGLError
+from pytests_utils import get_cases, parametrize_idtype
 from scipy.sparse import rand
-from test_utils import get_cases, parametrize_idtype
 
 rfuncs = {"sum": fn.sum, "max": fn.max, "min": fn.min, "mean": fn.mean}
 feat_size = 2

tests/python/common/test_heterograph.py

@@ -10,11 +10,11 @@
 import networkx as nx
 import numpy as np
 import pytest
+import pytests_utils
 import scipy.sparse as ssp
-import test_utils
 from dgl import DGLError
+from pytests_utils import get_cases, parametrize_idtype
 from scipy.sparse import rand
-from test_utils import get_cases, parametrize_idtype
 from utils import assert_is_identical_hetero
 
 
@@ -2419,7 +2419,7 @@ def test_dtype_cast(idtype):
     else:
         g_cast = g.int()
         assert g_cast.idtype == F.int32
-    test_utils.check_graph_equal(g, g_cast, check_idtype=False)
+    pytests_utils.check_graph_equal(g, g_cast, check_idtype=False)
 
 
 def test_float_cast():

tests/python/common/test_homophily.py

@@ -4,7 +4,7 @@
 import backend as F
 
 import dgl
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @unittest.skipIf(

tests/python/common/test_merge.py

@@ -1,7 +1,7 @@
 import backend as F
 
 import dgl
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @parametrize_idtype

tests/python/common/test_partition.py

@@ -4,7 +4,7 @@
 
 from dgl.distributed import graph_partition_book as gpb
 from dgl.partition import NDArrayPartition
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @unittest.skipIf(

tests/python/common/test_propagate.py

@@ -5,7 +5,7 @@
 import dgl
 import networkx as nx
 import utils as U
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def create_graph(idtype):

tests/python/common/test_readout.py

@@ -6,8 +6,8 @@
 import networkx as nx
 import numpy as np
 import pytest
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import get_cases
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import get_cases
 
 
 @parametrize_idtype

tests/python/common/test_sparse_ops-csr.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pytest
 import scipy.sparse as ssp
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 if F.backend_name == "pytorch":
     import torch

tests/python/common/test_subgraph.py

@@ -7,7 +7,7 @@
 import numpy as np
 import pytest
 import scipy.sparse as ssp
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 D = 5
 

tests/python/common/test_traversal.py

@@ -10,7 +10,7 @@
 import networkx as nx
 import numpy as np
 import scipy.sparse as sp
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 np.random.seed(42)
 

tests/python/common/transforms/test_functional-sort.py

@@ -11,7 +11,7 @@
 import pytest
 import scipy.sparse as ssp
 from dgl import DGLError
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def create_test_heterograph(num_nodes, num_adj, idtype):

tests/python/common/transforms/test_to_block.py

@@ -18,7 +18,7 @@
 
 import dgl
 import dgl.partition
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @parametrize_idtype

tests/python/common/transforms/test_transform.py

@@ -26,9 +26,9 @@
 import networkx as nx
 import numpy as np
 import pytest
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import get_cases
 from scipy import sparse as spsp
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import get_cases
 
 D = 5
 

tests/python/common/utils/test_filter.py

@@ -5,7 +5,7 @@
 import dgl
 import numpy as np
 from dgl.utils import Filter
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 def test_graph_filter():

tests/python/mxnet/test_nn.py

@@ -9,8 +9,8 @@
 import pytest
 import scipy as sp
 from mxnet import autograd, gluon, nd
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import (
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import (
     get_cases,
     random_bipartite,
     random_dglgraph,

tests/python/pytorch/dataloading/test_dataloader.py

@@ -11,7 +11,7 @@
 import pytest
 import torch
 import torch.distributed as dist
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 
 @pytest.mark.parametrize("batch_size", [None, 16])

tests/python/pytorch/geometry/test_geometry.py

@@ -8,8 +8,8 @@
 from dgl import DGLError
 from dgl.base import DGLWarning
 from dgl.geometry import farthest_point_sampler, neighbor_matching
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import get_cases
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import get_cases
 
 
 def test_fps():

tests/python/pytorch/mpops/test_edgewise.py

@@ -6,7 +6,7 @@
 import numpy as np
 import pytest
 import torch
-from test_utils import parametrize_idtype
+from pytests_utils import parametrize_idtype
 
 random.seed(42)
 np.random.seed(42)

tests/python/pytorch/nn/test_nn.py

@@ -12,8 +12,8 @@
 import scipy as sp
 import torch
 import torch as th
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import (
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import (
     get_cases,
     random_bipartite,
     random_dglgraph,

tests/python/tensorflow/test_nn.py

@@ -10,14 +10,14 @@
 import pytest
 import scipy as sp
 import tensorflow as tf
-from tensorflow.keras import layers
-from test_utils import parametrize_idtype
-from test_utils.graph_cases import (
+from pytests_utils import parametrize_idtype
+from pytests_utils.graph_cases import (
     get_cases,
     random_bipartite,
     random_dglgraph,
     random_graph,
 )
+from tensorflow.keras import layers
 
 
 def _AXWb(A, X, W, b):