Merge branch 'keras-team:master' into master

.github/workflows/scripts/auto-assignment.js

@@ -12,7 +12,7 @@ module.exports = async ({ github, context }) => {
   // Is this an issue? If so, assign the issue number. Otherwise, assign the PR number.
   if (context.payload.issue) {
     //assignee List for issues. 
-    assigneesList = ["SuryanarayanaY", "sachinprasadhs"];
+    assigneesList = ["mehtamansi29","sonali-kumari1", "sachinprasadhs"];
     issueNumber = context.payload.issue.number;
   } else {
     //assignee List for PRs. 

README.md

@@ -78,7 +78,7 @@ print(keras_hub.utils.decode_imagenet_predictions(preds))
 Load a Bert model and fine-tune it on IMDb movie reviews:
 
 ```python
-classifier = keras_hub.models.BertClassifier.from_preset(
+classifier = keras_hub.models.TextClassifier.from_preset(
     "bert_base_en_uncased",
     activation="softmax",
     num_classes=2,

keras_hub/src/utils/preset_utils.py

@@ -240,7 +240,7 @@ def tf_copy_gfile_to_cache(preset, path):
         try:
             import tensorflow as tf
 
-            os.make_dirs(os.path.dirname(local_path), exist_ok=True)
+            os.makedirs(os.path.dirname(local_path), exist_ok=True)
             tf.io.gfile.copy(url, local_path)
         except Exception as e:
             # gfile.copy will leave an empty file after an error.

keras_hub/src/utils/preset_utils_test.py

@@ -33,6 +33,18 @@ def test_preset_errors(self):
         with self.assertRaisesRegex(ValueError, "class keras_hub>BortBackbone"):
             BertBackbone.from_preset(preset_dir)
 
+    @pytest.mark.large
+    def test_tf_file_io(self):
+        # Load a model from Kaggle to use as a test model.
+        preset = "bert_tiny_en_uncased"
+        backbone = BertBackbone.from_preset(preset)
+        # Save the model on a local directory.
+        temp_dir = self.get_temp_dir()
+        local_preset_dir = os.path.join(temp_dir, "bert_preset")
+        backbone.save_to_preset(local_preset_dir)
+        # Load with "file://" which tf supports.
+        backbone = BertBackbone.from_preset("file://" + local_preset_dir)
+
     @pytest.mark.large
     def test_upload_empty_preset(self):
         temp_dir = self.get_temp_dir()