change greater, greater_equal, less, less_equal (#484)

Author: Rubtsowa

dpnp/dpnp_algo/dpnp_algo.pxd

@@ -198,11 +198,11 @@ cpdef dparray dpnp_right_shift(dparray array1, dparray array2)
 Logic functions
 """
 cpdef dparray dpnp_equal(dparray array1, input2)
-cpdef dparray dpnp_greater(dparray input1, dparray input2)
-cpdef dparray dpnp_greater_equal(dparray input1, dparray input2)
+cpdef dparray dpnp_greater(dparray input1, input2)
+cpdef dparray dpnp_greater_equal(dparray input1, input2)
 cpdef dparray dpnp_isclose(dparray input1, input2, double rtol=*, double atol=*, cpp_bool equal_nan=*)
-cpdef dparray dpnp_less(dparray input1, dparray input2)
-cpdef dparray dpnp_less_equal(dparray input1, dparray input2)
+cpdef dparray dpnp_less(dparray input1, input2)
+cpdef dparray dpnp_less_equal(dparray input1, input2)
 cpdef dparray dpnp_logical_and(dparray input1, dparray input2)
 cpdef dparray dpnp_logical_not(dparray input1)
 cpdef dparray dpnp_logical_or(dparray input1, dparray input2)

dpnp/dpnp_algo/dpnp_algo_logic.pyx

@@ -97,20 +97,32 @@ cpdef dparray dpnp_equal(dparray array1, input2):
     return result
 
 
-cpdef dparray dpnp_greater(dparray input1, dparray input2):
+cpdef dparray dpnp_greater(dparray input1, input2):
+    input2_is_scalar = dpnp.isscalar(input2)
+
     cdef dparray result = dparray(input1.shape, dtype=numpy.bool)
 
-    for i in range(result.size):
-        result[i] = numpy.bool(input1[i] > input2[i])
+    if input2_is_scalar:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] > input2)
+    else:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] > input2[i])
 
     return result
 
 
-cpdef dparray dpnp_greater_equal(dparray input1, dparray input2):
+cpdef dparray dpnp_greater_equal(dparray input1, input2):
+    input2_is_scalar = dpnp.isscalar(input2)
+
     cdef dparray result = dparray(input1.shape, dtype=numpy.bool)
 
-    for i in range(result.size):
-        result[i] = numpy.bool(input1[i] >= input2[i])
+    if input2_is_scalar:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] >= input2)
+    else:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] >= input2[i])
 
     return result
 
@@ -155,20 +167,32 @@ cpdef dparray dpnp_isnan(dparray input1):
     return result
 
 
-cpdef dparray dpnp_less(dparray input1, dparray input2):
+cpdef dparray dpnp_less(dparray input1, input2):
+    input2_is_scalar = dpnp.isscalar(input2)
+
     cdef dparray result = dparray(input1.shape, dtype=numpy.bool)
 
-    for i in range(result.size):
-        result[i] = numpy.bool(input1[i] < input2[i])
+    if input2_is_scalar:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] < input2)
+    else:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] < input2[i])
 
     return result
 
 
-cpdef dparray dpnp_less_equal(dparray input1, dparray input2):
+cpdef dparray dpnp_less_equal(dparray input1, input2):
+    input2_is_scalar = dpnp.isscalar(input2)
+
     cdef dparray result = dparray(input1.shape, dtype=numpy.bool)
 
-    for i in range(result.size):
-        result[i] = numpy.bool(input1[i] <= input2[i])
+    if input2_is_scalar:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] <= input2)
+    else:
+        for i in range(result.size):
+            result[i] = dpnp.bool(input1[i] <= input2[i])
 
     return result
 

dpnp/dpnp_iface_logic.py

@@ -269,11 +269,11 @@ def greater(x1, x2):
 
     """
 
-    if (use_origin_backend(x1)):
-        return numpy.greater(x1, x2)
-
-    if isinstance(x1, dparray) or isinstance(x2, dparray):
-        return dpnp_greater(x1, x2)
+    if not (use_origin_backend(x1)):
+        if not isinstance(x1, dparray):
+            pass
+        else:
+            return dpnp_greater(x1, x2)
 
     return numpy.greater(x1, x2)
 
@@ -309,11 +309,11 @@ def greater_equal(x1, x2):
 
     """
 
-    if (use_origin_backend(x1)):
-        return numpy.greater_equal(x1, x2)
-
-    if isinstance(x1, dparray) or isinstance(x2, dparray):
-        return dpnp_greater_equal(x1, x2)
+    if not (use_origin_backend(x1)):
+        if not isinstance(x1, dparray):
+            pass
+        else:
+            return dpnp_greater_equal(x1, x2)
 
     return numpy.greater_equal(x1, x2)
 
@@ -545,11 +545,11 @@ def less(x1, x2):
 
     """
 
-    if (use_origin_backend(x1)):
-        return numpy.less(x1, x2)
-
-    if isinstance(x1, dparray) or isinstance(x2, dparray):
-        return dpnp_less(x1, x2)
+    if not (use_origin_backend(x1)):
+        if not isinstance(x1, dparray):
+            pass
+        else:
+            return dpnp_less(x1, x2)
 
     return numpy.less(x1, x2)
 
@@ -585,11 +585,11 @@ def less_equal(x1, x2):
 
     """
 
-    if (use_origin_backend(x1)):
-        return numpy.less_equal(x1, x2)
-
-    if isinstance(x1, dparray) or isinstance(x2, dparray):
-        return dpnp_less_equal(x1, x2)
+    if not (use_origin_backend(x1)):
+        if not isinstance(x1, dparray):
+            pass
+        else:
+            return dpnp_less_equal(x1, x2)
 
     return numpy.less_equal(x1, x2)
 

tests/test_logic.py

@@ -71,6 +71,42 @@ def test_any(type, shape):
         numpy.testing.assert_allclose(dpnp_res, np_res)
 
 
+def test_greater():
+    a = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
+    ia = dpnp.array(a)
+    for i in range(len(a) + 1):
+        np_res = (a > i)
+        dpnp_res = (ia > i)
+        numpy.testing.assert_equal(dpnp_res, np_res)
+
+
+def test_greater_equal():
+    a = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
+    ia = dpnp.array(a)
+    for i in range(len(a) + 1):
+        np_res = (a >= i)
+        dpnp_res = (ia >= i)
+        numpy.testing.assert_equal(dpnp_res, np_res)
+
+
+def test_less():
+    a = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
+    ia = dpnp.array(a)
+    for i in range(len(a) + 1):
+        np_res = (a < i)
+        dpnp_res = (ia < i)
+        numpy.testing.assert_equal(dpnp_res, np_res)
+
+
+def test_less_equal():
+    a = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
+    ia = dpnp.array(a)
+    for i in range(len(a) + 1):
+        np_res = (a <= i)
+        dpnp_res = (ia <= i)
+        numpy.testing.assert_equal(dpnp_res, np_res)
+
+
 def test_not_equal():
     a = numpy.array([1, 2, 3, 4, 5, 6, 7, 8])
     ia = dpnp.array(a)