fix linter problems

graphcore-research · Oct 27, 2023 · ca1755c · ca1755c
1 parent 4781c12
commit ca1755c
Showing 1 changed file with 25 additions and 7 deletions.
diff --git a/test/test_benchmark_performance.py b/test/test_benchmark_performance.py
@@ -39,7 +39,11 @@
 @pytest.mark.parametrize("molecule", ["methane", "benzene"])
 def test_dense_eri(molecule):
 
-    opts, mol_str = nanoDFT_options(float32 = True, mol_str=molecule, backend="ipu")
+    opts, mol_str = nanoDFT_options(
+        float32 = True,
+        mol_str=molecule,
+        backend="ipu"
+    )
     mol = build_mol(mol_str, opts.basis)
 
     _, _, ipu_cycles_stamps = nanoDFT(mol, opts, profile_performance=True)
@@ -49,11 +53,15 @@ def test_dense_eri(molecule):
     end = np.asarray(end)
 
     diff = (end - start)[0][0][0]
-    print("----------------------------------------------------------------------------")
+    print(
+        "----------------------------------------------------------------------------"
+        )
     print("                                Diff cycle count:", diff)
     print("                            Diff cycle count [M]:", diff/1e6)
     print("Estimated time of execution on Bow-IPU [seconds]:", diff/(1.85*1e9))
-    print("----------------------------------------------------------------------------")
+    print(
+        "----------------------------------------------------------------------------"
+        )
 
     assert True
 
@@ -62,7 +70,13 @@ def test_dense_eri(molecule):
 @pytest.mark.parametrize("molecule", ["methane", "benzene", "c20"])
 def test_sparse_eri(molecule):
 
-    opts, mol_str = nanoDFT_options(float32 = True, mol_str=molecule, backend="ipu", dense_ERI=False, eri_threshold=1e-9)
+    opts, mol_str = nanoDFT_options(
+        float32=True,
+        mol_str=molecule,
+        backend="ipu",
+        dense_ERI=False,
+        eri_threshold=1e-9
+    )
     mol = build_mol(mol_str, opts.basis)
 
     _, _, ipu_cycles_stamps = nanoDFT(mol, opts, profile_performance=True)
@@ -72,10 +86,14 @@ def test_sparse_eri(molecule):
     end = np.asarray(end)
 
     diff = (end - start)[0][0][0]
-    print("----------------------------------------------------------------------------")
+    print(
+        "----------------------------------------------------------------------------"
+        )
     print("                                Diff cycle count:", diff)
     print("                            Diff cycle count [M]:", diff/1e6)
     print("Estimated time of execution on Bow-IPU [seconds]:", diff/(1.85*1e9))
-    print("----------------------------------------------------------------------------")
+    print(
+        "----------------------------------------------------------------------------"
+        )
 
-    assert True
+    assert True