[pre-commit.ci] auto fixes from pre-commit.com hooks

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deepmodeling · Jan 5, 2024 · 0d20b8d · 0d20b8d
1 parent 5fbbd61
commit 0d20b8d
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Showing 2 changed files with 16 additions and 12 deletions.
diff --git a/deepmd_utils/model_format.py b/deepmd_utils/model_format.py
@@ -246,12 +246,16 @@ def call(self, x: np.ndarray) -> np.ndarray:
         if self.activation_function == "tanh":
             fn = np.tanh
         elif self.activation_function.lower() == "none":
+
             def fn(x):
                 return x
         else:
             raise NotImplementedError(self.activation_function)
-        y = np.matmul(x, self.w) + self.b \
-          if self.b is not None else np.matmul(x, self.w)
+        y = (
+            np.matmul(x, self.w) + self.b
+            if self.b is not None
+            else np.matmul(x, self.w)
+        )
         y = fn(y)
         if self.idt is not None:
             y *= self.idt

diff --git a/source/tests/test_model_format_utils.py b/source/tests/test_model_format_utils.py
@@ -1,10 +1,11 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
+import itertools
 import os
 import unittest
 from copy import (
     deepcopy,
 )
-import itertools
+
 import numpy as np
 
 from deepmd_utils.model_format import (
@@ -14,21 +15,21 @@
     save_dp_model,
 )
 
+
 class TestNativeLayer(unittest.TestCase):
     def setUp(self) -> None:
         self.w = np.full((2, 3), 3.0)
         self.b = np.full((3,), 4.0)
         self.idt = np.full((3,), 5.0)
 
     def test_serialize_deserize(self):
-      for ww,bb,idt,activation_function,resnet in \
-          itertools.product(
-            [self.w], [self.b, None], [self.idt, None], 
-            ["tanh", "none"], [True, False] ):
-        nl0 = NativeLayer(ww, bb, idt, activation_function, resnet)
-        nl1 = NativeLayer.deserialize(nl0.serialize())
-        inp = np.arange(self.w.shape[0])
-        np.testing.assert_allclose(nl0.call(inp), nl1.call(inp))        
+        for ww, bb, idt, activation_function, resnet in itertools.product(
+            [self.w], [self.b, None], [self.idt, None], ["tanh", "none"], [True, False]
+        ):
+            nl0 = NativeLayer(ww, bb, idt, activation_function, resnet)
+            nl1 = NativeLayer.deserialize(nl0.serialize())
+            inp = np.arange(self.w.shape[0])
+            np.testing.assert_allclose(nl0.call(inp), nl1.call(inp))
 
 
 class TestNativeNet(unittest.TestCase):
@@ -84,7 +85,6 @@ def test_deserialize(self):
         np.testing.assert_array_equal(network[1]["resnet"], True)
 
 
-
 class TestDPModel(unittest.TestCase):
     def setUp(self) -> None:
         self.w = np.full((3, 2), 3.0)