Tests that the seeds get set as the user desires

test/test_utils.py

@@ -2,11 +2,15 @@
 import os
 import pytest
 import random
+import tensorflow as tf
+import torch
 import utils
 
 __author__ = "Christopher Potts"
 __version__ = "CS224u, Stanford, Spring 2019"
 
+tf.enable_eager_execution()
+
 
 @pytest.mark.parametrize("arg, expected", [
     [
@@ -79,3 +83,30 @@ def test_glove2dict():
 def test_get_vocab(X, n_words, expected):
     result = utils.get_vocab(X, n_words=n_words)
     assert result == expected
+
+
+@pytest.mark.parametrize("set_value", [True, False])
+def test_fix_random_seeds_system(set_value):
+    utils.fix_random_seeds(seed=42, set_system=set_value)
+    x = np.random.random()
+    utils.fix_random_seeds(seed=42, set_system=set_value)
+    y = np.random.random()
+    assert (x == y) == set_value
+
+
+@pytest.mark.parametrize("set_value", [True, False])
+def test_fix_random_seeds_pytorch(set_value):
+    utils.fix_random_seeds(seed=42, set_torch=set_value)
+    x = torch.rand(1)
+    utils.fix_random_seeds(seed=42, set_torch=set_value)
+    y = torch.rand(1)
+    assert (x == y) == set_value
+
+
+@pytest.mark.parametrize("set_value", [True, False])
+def test_fix_random_seeds_tensorflow(set_value):
+    utils.fix_random_seeds(seed=42, set_tensorflow=set_value)
+    x = tf.random.uniform([1]).numpy()
+    utils.fix_random_seeds(seed=42, set_tensorflow=set_value)
+    y = tf.random.uniform([1]).numpy()
+    assert (x == y) == set_value