ENH: dpnp.convolve fallback; tests (#798)

Author: samir-nasibli

dpnp/dpnp_iface_mathematical.py

@@ -56,6 +56,7 @@
     "ceil",
     "conj",
     "conjugate",
+    "convolve",
     "copysign",
     "cross",
     "cumprod",
@@ -317,6 +318,23 @@ def conjugate(x1, **kwargs):
 conj = conjugate
 
 
+def convolve(a, v, mode='full'):
+    """
+    Returns the discrete, linear convolution of two one-dimensional sequences.
+
+    For full documentation refer to :obj:`numpy.convolve`.
+
+    Examples
+    --------
+    >>> ca = dpnp.convolve([1, 2, 3], [0, 1, 0.5])
+    >>> print(ca)
+    [0. , 1. , 2.5, 4. , 1.5]
+
+    """
+
+    return call_origin(numpy.convolve, a=a, v=v, mode=mode)
+
+
 def copysign(x1, x2, dtype=None, out=None, where=True, **kwargs):
     """
     Change the sign of x1 to that of x2, element-wise.

tests/test_mathematical.py

@@ -5,6 +5,34 @@
 import numpy
 
 
+class TestConvolve:
+    def test_object(self):
+        d = [1.] * 100
+        k = [1.] * 3
+        numpy.testing.assert_array_almost_equal(dpnp.convolve(d, k)[2:-2], dpnp.full(98, 3))
+
+    def test_no_overwrite(self):
+        d = dpnp.ones(100)
+        k = dpnp.ones(3)
+        dpnp.convolve(d, k)
+        numpy.testing.assert_array_equal(d, dpnp.ones(100))
+        numpy.testing.assert_array_equal(k, dpnp.ones(3))
+
+    def test_mode(self):
+        d = dpnp.ones(100)
+        k = dpnp.ones(3)
+        default_mode = dpnp.convolve(d, k, mode='full')
+        full_mode = dpnp.convolve(d, k, mode='f')
+        numpy.testing.assert_array_equal(full_mode, default_mode)
+        # integer mode
+        with numpy.testing.assert_raises(ValueError):
+            dpnp.convolve(d, k, mode=-1)
+        numpy.testing.assert_array_equal(dpnp.convolve(d, k, mode=2), full_mode)
+        # illegal arguments
+        with numpy.testing.assert_raises(TypeError):
+            dpnp.convolve(d, k, mode=None)
+
+
 @pytest.mark.parametrize("array",
                          [[[0, 0], [0, 0]],
                           [[1, 2], [1, 2]],