Merge pull request #11178 from tensorflow:typos3

PiperOrigin-RevId: 682027566

orbit/actions/conditional_action.py

@@ -47,7 +47,8 @@ def __init__(
     """Initializes the instance.
 
     Args:
-      condition: A callable accepting train or eval outputs and returing a bool.
+      condition: A callable accepting train or eval outputs and returning
+       a bool.
       action: The action (or optionally sequence of actions) to perform when
         `condition` is met.
     """

orbit/actions/new_best_metric.py

@@ -40,7 +40,7 @@ class NewBestMetric:
   if it is achieved. These separate methods enable the same `NewBestMetric`
   instance to be reused as a condition multiple times, and can also provide
   additional preemption/failure safety. For example, to avoid updating the best
-  metric if a model export fails or is pre-empted:
+  metric if a model export fails or is pre-emptied:
 
       new_best_metric = orbit.actions.NewBestMetric(
         'accuracy', filename='/model/dir/best_metric')

orbit/actions/new_best_metric_test.py

@@ -61,7 +61,7 @@ def test_json_persisted_value(self):
     tempfile = self.create_tempfile().full_path
     value = {'a': 1, 'b': 2}
     persisted_value = actions.JSONPersistedValue(value, tempfile)
-    # The inital value is used since tempfile is empty.
+    # The initial value is used since tempfile is empty.
     self.assertEqual(persisted_value.read(), value)
     persisted_value = actions.JSONPersistedValue('ignored', tempfile)
     # Initial value of 'ignored' is ignored, since there's a value in tempfile.

tensorflow_models/tensorflow_models_pypi.ipynb

@@ -49,7 +49,7 @@
         "\n",
         "## Colab environment setup. To use a stable TF release version\n",
         "##  because of the possible breakage in tf-nightly.\n",
-        "# !pip3 install -U numpy\u003e=1.20\n",
+        "# !pip3 install -U numpy>=1.20\n",
         "# !pip3 install -q tensorflow==2.8.0"
       ]
     },
@@ -101,7 +101,7 @@
         "## Check out modules\n",
         "\n",
         "**Note: As the TensorFlow Models (NLP + Vision) 2.9 release which is tested for this notebook, we partially exported selected modules but the APIs are not stable. Also be aware that, the\n",
-        "modeling libraries are advancing very fast, so we generally don't guarantee compatability between versions.** "
+        "modeling libraries are advancing very fast, so we generally don't guarantee compatibility between versions.** "
       ]
     },
     {
@@ -245,7 +245,7 @@
           "output_type": "stream",
           "text": [
             "spine_net\n",
-            "{'4': \u003cKerasTensor: shape=(1, 8, 8, 128) dtype=float32 (created by layer 'spine_net')\u003e, '5': \u003cKerasTensor: shape=(1, 4, 4, 128) dtype=float32 (created by layer 'spine_net')\u003e, '6': \u003cKerasTensor: shape=(1, 2, 2, 128) dtype=float32 (created by layer 'spine_net')\u003e}\n"
+            "{'4': <KerasTensor: shape=(1, 8, 8, 128) dtype=float32 (created by layer 'spine_net')>, '5': <KerasTensor: shape=(1, 4, 4, 128) dtype=float32 (created by layer 'spine_net')>, '6': <KerasTensor: shape=(1, 2, 2, 128) dtype=float32 (created by layer 'spine_net')>}\n"
           ]
         }
       ],