[TESTS] Make pytorch test_nn.py fully reproducible (#5887)

tests/backend/backend_unittest.py

@@ -126,6 +126,11 @@ def abs(a):
     pass
 
 
+def seed(a):
+    """Set seed to for random generator"""
+    pass
+
+
 ###############################################################################
 # Tensor functions used *only* on index tensor
 # ----------------

tests/backend/mxnet/__init__.py

@@ -100,3 +100,7 @@ def dot(a, b):
 
 def abs(a):
     return nd.abs(a)
+
+
+def seed(a):
+    return mx.random.seed(a)

tests/backend/pytorch/__init__.py

@@ -93,3 +93,7 @@ def dot(a, b):
 
 def abs(a):
     return a.abs()
+
+
+def seed(a):
+    return th.manual_seed(a)

tests/backend/tensorflow/__init__.py

@@ -104,3 +104,7 @@ def dot(a, b):
 
 def abs(a):
     return tf.abs(a)
+
+
+def seed(a):
+    return tf.random.set_seed(a)

tests/python/pytorch/nn/test_nn.py

 import io
 import pickle
+import random
 from copy import deepcopy
 
 import backend as F
@@ -8,6 +9,7 @@ import dgl
 import dgl.function as fn
 import dgl.nn.pytorch as nn
 import networkx as nx
+import numpy as np  # For setting seed for scipy
 import pytest
 import scipy as sp
 import torch
@@ -24,6 +26,13 @@ from utils.graph_cases import (
     random_graph,
 )
 
+# Set seeds to make tests fully reproducible.
+SEED = 12345  # random.randint(1, 99999)
+random.seed(SEED)  # For networkx
+np.random.seed(SEED)  # For scipy
+dgl.seed(SEED)
+F.seed(SEED)
+
 tmp_buffer = io.BytesIO()