Dgl ops 2

tests/nightly/test_large_array.py

@@ -841,7 +841,9 @@ def test_div():
     b = 3*nd.ones(shape=(LARGE_X, SMALL_Y))
     c = b
     c = c.__div__(a)
+    mx_divide = nd.divide(b, a)
     assert c[0][-1] == 3/2
+    assert mx_divide[0][-1] == c[0][-1]
     assert c.shape == a.shape
 
 
@@ -1212,6 +1214,80 @@ def test_full():
     assert a[-1][-1] == 3
 
 
+def test_hyperbolic():
+    def test_arccosh(a):
+        mx_res = mx.nd.arccosh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.arccosh(a[-1][-1].asnumpy()))
+
+    def test_arcsinh(a):
+        mx_res = mx.nd.arcsinh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.arcsinh(a[-1][-1].asnumpy()))
+
+    def test_arctanh(a):
+        a[-1][-1] = 0   # arctanh of 1 is inf, assert_almost_equal gives "divide by 0" for comparing 2 inf values
+        mx_res = mx.nd.arctanh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.arctanh(a[-1][-1].asnumpy()))
+
+    def test_cosh(a):
+        mx_res = mx.nd.cosh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.cosh(a[-1][-1].asnumpy()))
+
+    def test_sinh(a):
+        mx_res = mx.nd.sinh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.sinh(a[-1][-1].asnumpy()))
+
+    def test_tanh(a):
+        mx_res = mx.nd.tanh(a)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.tanh(a[-1][-1].asnumpy()))
+
+    a = mx.nd.ones((LARGE_X, SMALL_Y))
+    test_arccosh(a)
+    test_arcsinh(a)
+    test_arctanh(a)
+    test_cosh(a)
+    test_sinh(a)
+    test_tanh(a)
+
+
+def test_sign():
+    a = mx.nd.random.normal(-1,1, shape=(LARGE_X, SMALL_Y))
+    mx_res = mx.nd.sign(a)
+    assert_almost_equal(mx_res[-1][-1].asnumpy(), np.sign(a[-1][-1].asnumpy()))
+
+
+def test_logical():
+    def test_logical_and(a, b):
+        mx_res = mx.nd.logical_and(a, b)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.logical_and(a[-1][-1].asnumpy(), b[-1][-1].asnumpy()))
+
+    def test_logical_or(a, b):
+        mx_res = mx.nd.logical_and(a, b)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.logical_and(a[-1][-1].asnumpy(), b[-1][-1].asnumpy()))
+
+    def test_logical_not(a, b):
+        mx_res = mx.nd.logical_and(a, b)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.logical_and(a[-1][-1].asnumpy(), b[-1][-1].asnumpy()))
+
+    def test_logical_xor(a, b):
+        mx_res = mx.nd.logical_and(a, b)
+        assert_almost_equal(mx_res[-1][-1].asnumpy(), np.logical_and(a[-1][-1].asnumpy(), b[-1][-1].asnumpy()))
+
+    a = mx.nd.ones((LARGE_X, SMALL_Y))
+    b = mx.nd.zeros((LARGE_X, SMALL_Y))
+    test_logical_and(a, b)
+    test_logical_or(a, b)
+    test_logical_not(a, b)
+    test_logical_xor(a, b)
+
+
+def test_batch_dot():
+    a = mx.nd.ones((LARGE_X, 5, 10))
+    b = 2*mx.nd.ones((LARGE_X, 10, 6))
+    res = mx.nd.batch_dot(a, b)
+    assert res[0][0][0] == 20
+    assert res.shape == (LARGE_X, 5, 6)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule()