style25JUN2021 (#746)

Author: shssf

benchmarks/pytest_benchmark/test_random.py

@@ -31,41 +31,42 @@
 import dpnp
 import numpy as np
 
-ROUNDS=30
-ITERATIONS=4
+ROUNDS = 30
+ITERATIONS = 4
+
+NNUMBERS = 2**26
 
-NNUMBERS=2**26
 
 @pytest.mark.parametrize("function", [dpnp.random.beta, np.random.beta],
-                                     ids=["dpnp", "numpy"])
+                         ids=["dpnp", "numpy"])
 def test_beta(benchmark, function):
     result = benchmark.pedantic(target=function, args=(4.0, 5.0, NNUMBERS,),
                                 rounds=ROUNDS, iterations=ITERATIONS)
 
 
 @pytest.mark.parametrize("function", [dpnp.random.exponential, np.random.exponential],
-                                     ids=["dpnp", "numpy"])
+                         ids=["dpnp", "numpy"])
 def test_exponential(benchmark, function):
     result = benchmark.pedantic(target=function, args=(4.0, NNUMBERS,),
                                 rounds=ROUNDS, iterations=ITERATIONS)
 
 
 @pytest.mark.parametrize("function", [dpnp.random.gamma, np.random.gamma],
-                                     ids=["dpnp", "numpy"])
+                         ids=["dpnp", "numpy"])
 def test_gamma(benchmark, function):
     result = benchmark.pedantic(target=function, args=(2.0, 4.0, NNUMBERS,),
                                 rounds=ROUNDS, iterations=ITERATIONS)
 
 
 @pytest.mark.parametrize("function", [dpnp.random.normal, np.random.normal],
-                                     ids=["dpnp", "numpy"])
+                         ids=["dpnp", "numpy"])
 def test_normal(benchmark, function):
     result = benchmark.pedantic(target=function, args=(0.0, 1.0, NNUMBERS,),
                                 rounds=ROUNDS, iterations=ITERATIONS)
 
 
 @pytest.mark.parametrize("function", [dpnp.random.uniform, np.random.uniform],
-                                     ids=["dpnp", "numpy"])
+                         ids=["dpnp", "numpy"])
 def test_uniform(benchmark, function):
     result = benchmark.pedantic(target=function, args=(0.0, 1.0, NNUMBERS,),
                                 rounds=ROUNDS, iterations=ITERATIONS)

tests/test_statistics.py

@@ -31,6 +31,7 @@ def test_max(axis):
 
     numpy.testing.assert_allclose(dpnp_res, np_res)
 
+
 @pytest.mark.parametrize("array",
                          [[2, 0, 6, 2],
                           [2, 0, 6, 2, 5, 6, 7, 8],