Secure support of int32 for RandomState.uniform in tests.

Author: antonwolfy

dpnp/random/dpnp_iface_random.py

@@ -125,7 +125,7 @@ def uniform(self, low=0.0, high=1.0, size=None, dtype=numpy.float64, usm_type="d
         -----------
         Parameters ``low`` and ``high`` are supported as scalar.
         Otherwise, :obj:`numpy.random.uniform(low, high, size)` samples are drawn.
-        Parameter ``dtype`` is supported only for :obj:`dpnp.float32` or :obj:`dpnp.float64`.
+        Parameter ``dtype`` is supported only for :obj:`dpnp.int32`, :obj:`dpnp.float32` or :obj:`dpnp.float64`.
         Output array data type is the same as ``dtype``.
         """
 
@@ -137,7 +137,7 @@ def uniform(self, low=0.0, high=1.0, size=None, dtype=numpy.float64, usm_type="d
             else:
                 if low > high:
                     low, high = high, low
-                if not (dpnp.is_type_supported(dtype) and dtype in {dpnp.float32, dpnp.float64}):
+                if not (dpnp.is_type_supported(dtype) and dtype in {dpnp.int32, dpnp.float32, dpnp.float64}):
                     raise TypeError(f"{dtype} is unsupported.")
                 return self.random_state.uniform(low, high, size, dtype, usm_type).get_pyobj()
 

tests/test_randomstate.py

@@ -5,7 +5,7 @@
 import numpy
 
 from dpnp.random import RandomState
-from numpy.testing import (assert_allclose, assert_raises, assert_array_almost_equal)
+from numpy.testing import (assert_allclose, assert_raises, assert_array_equal, assert_array_almost_equal)
 
 
 class TestSeed:
@@ -87,14 +87,28 @@ class TestUniform:
     @pytest.mark.parametrize("usm_type",
                              ["host", "device", "shared"],
                              ids=['host', 'device', 'shared'])
-    def test_uniform(self, dtype, usm_type):
+    def test_uniform_float(self, dtype, usm_type):
         seed = 28041997
         actual = dpnp.asnumpy(RandomState(seed).uniform(low=1.23, high=10.54, size=(3, 2), dtype=dtype, usm_type=usm_type))
         desired = numpy.array([[3.700744485249743, 8.390019132522866],
                                [2.60340195777826,  4.473366308724508],
                                [1.773701806552708, 4.193498786306009]])
         assert_array_almost_equal(actual, desired, decimal=6)
 
+    @pytest.mark.parametrize("dtype",
+                             [dpnp.int32, numpy.int32, numpy.intc],
+                             ids=['dpnp.int32', 'numpy.int32', 'numpy.intc'])
+    @pytest.mark.parametrize("usm_type",
+                             ["host", "device", "shared"],
+                             ids=['host', 'device', 'shared'])
+    def test_uniform_int(self, dtype, usm_type):
+        seed = 28041997
+        actual = dpnp.asnumpy(RandomState(seed).uniform(low=1.23, high=10.54, size=(3, 2), dtype=dtype, usm_type=usm_type))
+        desired = numpy.array([[3, 8],
+                               [2,  4],
+                               [1, 4]])
+        assert_array_equal(actual, desired)
+
     @pytest.mark.parametrize("high",
                              [dpnp.array([3]), numpy.array([3])],
                              ids=['dpnp.array([3])', 'numpy.array([3])'])
@@ -109,8 +123,8 @@ def test_fallback(self, low, high):
         assert_array_almost_equal(actual, desired, decimal=15)
 
     @pytest.mark.parametrize("dtype",
-                             [dpnp.float16, numpy.integer, dpnp.int, dpnp.bool, numpy.int64, dpnp.int32],
-                             ids=['dpnp.float16', 'numpy.integer', 'dpnp.int', 'dpnp.bool', 'numpy.int64', 'dpnp.int32'])
+                             [dpnp.float16, numpy.integer, dpnp.int, dpnp.bool, numpy.int64],
+                             ids=['dpnp.float16', 'numpy.integer', 'dpnp.int', 'dpnp.bool', 'numpy.int64'])
     def test_invalid_dtype(self, dtype):
         # dtype must be float32 or float64
         assert_raises(TypeError, RandomState().uniform, dtype=dtype)