[Bugfix] GINDataset check whether labels are all valid (#2319)

* PPIDataset

* Revert "PPIDataset"

This reverts commit 264bd0c960cfa698a7bb946dad132bf52c2d0c8a.

* check whether the original labels are valid

* add unit test for gin dataset

* bug of asscalar in mxnet<=1.6

* mxnet<=1.6 asscalar requires ndarray to be shaped (1,)

* skip gpu while testing datasets

* Update test_data.py

* test of gin dataset takes too much time

python/dgl/backend/mxnet/tensor.py

@@ -56,6 +56,10 @@ def tensor(data, dtype=None):
         return nd.array(data, dtype=dtype)
 
 def as_scalar(data):
+    if data.size != 1:
+        raise ValueError("The current array is not a scalar")
+    if data.shape != (1,):
+        data = data.expand_dims(axis=0)
     return data.asscalar()
 
 def get_preferred_sparse_format():

python/dgl/data/gindt.py

@@ -248,7 +248,8 @@ class GINDataset(DGLBuiltinDataset):
                 nlabel_set = nlabel_set.union(
                     set([F.as_scalar(nl) for nl in g.ndata['label']]))
             nlabel_set = list(nlabel_set)
-            if len(nlabel_set) == np.max(nlabel_set) + 1 and np.min(nlabel_set) == 0:
+            is_label_valid = all([label in self.nlabel_dict for label in nlabel_set])
+            if is_label_valid and len(nlabel_set) == np.max(nlabel_set) + 1 and np.min(nlabel_set) == 0:
                 # Note this is different from the author's implementation. In weihua916's implementation,
                 # the labels are relabeled anyway. But here we didn't relabel it if the labels are contiguous
                 # to make it consistent with the original dataset

tests/compute/test_data.py

 import dgl.data as data
+import unittest
+import backend as F
 
+
+@unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.")
 def test_minigc():
     ds = data.MiniGCDataset(16, 10, 20)
     g, l = list(zip(*ds))
     print(g, l)
 
+
+@unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.")
+def test_gin():
+    ds_n_graphs = {
+        'MUTAG': 188,
+        'IMDBBINARY': 1000,
+        'IMDBMULTI': 1500,
+        'PROTEINS': 1113,
+        'PTC': 344,
+    }
+    for name, n_graphs in ds_n_graphs.items():
+        ds = data.GINDataset(name, self_loop=False, degree_as_nlabel=False)
+        assert len(ds) == n_graphs, (len(ds), name)
+
+
+@unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.")
 def test_data_hash():
     class HashTestDataset(data.DGLDataset):
         def __init__(self, hash_key=()):
@@ -20,4 +40,5 @@ def test_data_hash():
 
 if __name__ == '__main__':
     test_minigc()
+    test_gin()
     test_data_hash()