logical_and reduction (#1123)

* Adding functionality for logical_and.reduce() with appropriate modifications in tests \n\n Joseph Guman <joeytg@stanford.edu>

* Minor style change to test for logical_and.reduce() \n\nSigned-off-by: Joseph Guman <joeytg@stanford.edu>

* Style changes and adding logical_or.reduce() functionality with UnaryRedCode.ANY Signed-off-by: Joseph Guman <joeytg@stanford.edu>

* Minor fixes

---------

Co-authored-by: Joseph Thomas Guman <joeytg@sapling2.stanford.edu>
Co-authored-by: Manolis Papadakis <mpapadakis@nvidia.com>
Co-authored-by: Manolis Papadakis <manopapad@gmail.com>

Author: 3 people

cunumeric/_ufunc/comparison.py

@@ -73,13 +73,15 @@
     "logical_and",
     BinaryOpCode.LOGICAL_AND,
     relation_types_of(all_dtypes),
+    red_code=UnaryRedCode.ALL,
 )
 
 logical_or = create_binary_ufunc(
     "Compute the truth value of x1 OR x2 element-wise.",
     "logical_or",
     BinaryOpCode.LOGICAL_OR,
     relation_types_of(all_dtypes),
+    red_code=UnaryRedCode.ANY,
 )
 
 logical_xor = create_binary_ufunc(

cunumeric/_ufunc/ufunc.py

@@ -753,6 +753,16 @@ def reduce(
                 f"reduction for {self} is not yet implemented"
             )
 
+        if self._op_code in [
+            BinaryOpCode.LOGICAL_AND,
+            BinaryOpCode.LOGICAL_OR,
+        ]:
+            res_dtype = bool
+            if dtype is not None:
+                raise TypeError("Cannot set dtype on a logical reduction")
+        else:
+            res_dtype = None
+
         # NumPy seems to be using None as the default axis value for scalars
         if array.ndim == 0 and axis == 0:
             axis = None
@@ -767,6 +777,7 @@ def reduce(
             keepdims=keepdims,
             initial=initial,
             where=where,
+            res_dtype=res_dtype,
         )
 
 

tests/integration/test_fallback.py

@@ -28,8 +28,15 @@ def test_ufunc():
     in_num = num.array([0, 1, 2, 3])
     in_np = in_num.__array__()
 
-    out_num = np.logical_and.reduce(in_num)
-    out_np = np.logical_and.reduce(in_np)
+    # This test uses logical_and.accumulate because it is currently
+    # unimplemented, and we want to verify a behaviour of unimplemented ufunc
+    # methods. If logical_and.accumulate becomes implemented in the future,
+    # this assertion will start to fail, and a new (unimplemented) ufunc method
+    # should be found to replace it
+    assert not num.logical_and.accumulate._cunumeric.implemented
+
+    out_num = num.logical_and.accumulate(in_num)
+    out_np = np.logical_and.accumulate(in_np)
     assert np.array_equal(out_num, out_np)
 
 

tests/integration/test_logical_reduction.py

@@ -0,0 +1,25 @@
+import numpy as np
+import pytest
+
+import cunumeric as num
+
+
+@pytest.mark.parametrize("axis", [None, 0, 1, 2, (0, 1, 2)])
+def test_logical_reductions(axis):
+    input = [[[12, 0, 1, 2], [9, 0, 0, 1]], [[0, 0, 0, 5], [1, 1, 1, 1]]]
+    in_num = num.array(input)
+    in_np = np.array(input)
+
+    out_num = num.logical_and.reduce(in_num, axis=axis)
+    out_np = np.logical_and.reduce(in_np, axis=axis)
+    assert num.array_equal(out_num, out_np)
+
+    out_num = num.logical_or.reduce(in_num, axis=axis)
+    out_np = np.logical_or.reduce(in_np, axis=axis)
+    assert num.array_equal(out_num, out_np)
+
+
+if __name__ == "__main__":
+    import sys
+
+    sys.exit(pytest.main(sys.argv))