Add Kaggle upload validation tests.

keras_nlp/utils/preset_utils.py

@@ -223,7 +223,7 @@ def _validate_backbone(preset):
         weights_path = os.path.join(preset, config["weights"])
         if not os.path.exists(weights_path):
             raise FileNotFoundError(
-                f"The weights file doesn't exist in preset directory `{preset}`."
+                f"The weights file is missing from the preset directory `{preset}`."
             )
     else:
         raise ValueError(

keras_nlp/utils/preset_utils_test.py

@@ -19,12 +19,16 @@
 from absl.testing import parameterized
 
 from keras_nlp import upload_preset
+from keras_nlp.models import DistilBertBackbone
+from keras_nlp.models import DistilBertTokenizer
 from keras_nlp.models.albert.albert_classifier import AlbertClassifier
 from keras_nlp.models.backbone import Backbone
 from keras_nlp.models.bert.bert_classifier import BertClassifier
 from keras_nlp.models.roberta.roberta_classifier import RobertaClassifier
 from keras_nlp.models.task import Task
 from keras_nlp.tests.test_case import TestCase
+from keras_nlp.utils.preset_utils import CONFIG_FILE
+from keras_nlp.utils.preset_utils import TOKENIZER_CONFIG_FILE
 from keras_nlp.utils.preset_utils import check_preset_class
 from keras_nlp.utils.preset_utils import load_from_preset
 from keras_nlp.utils.preset_utils import save_to_preset
@@ -116,4 +120,51 @@ def test_upload_empty_preset(self):
         with self.assertRaises(FileNotFoundError):
             upload_preset(uri, empty_preset)
 
-    # TODO: add more test to cover various invalid scenarios such as invalid json, missing files, etc.
+    @parameterized.parameters(
+        (TOKENIZER_CONFIG_FILE), (CONFIG_FILE), ("model.weights.h5")
+    )
+    @pytest.mark.keras_3_only
+    @pytest.mark.large
+    def test_upload_with_missing_file(self, missing_file):
+        # Load a model from Kaggle to run tests on it.
+        preset = "distil_bert_base_en"
+        backbone = DistilBertBackbone.from_preset(preset)
+        tokenizer = DistilBertTokenizer.from_preset(preset)
+
+        # Save the model on a local directory.
+        temp_dir = self.get_temp_dir()
+        local_preset_dir = os.path.join(temp_dir, "distil_bert_preset")
+        backbone.save_to_preset(local_preset_dir)
+        tokenizer.save_to_preset(local_preset_dir)
+
+        # Delete the file that is supposed to be missing.
+        missing_path = os.path.join(local_preset_dir, missing_file)
+        os.remove(missing_path)
+
+        # Verify error handling.
+        with self.assertRaisesRegex(FileNotFoundError, "is missing"):
+            upload_preset("kaggle://test/test/test", local_preset_dir)
+
+    @parameterized.parameters((TOKENIZER_CONFIG_FILE), (CONFIG_FILE))
+    @pytest.mark.keras_3_only
+    @pytest.mark.large
+    def test_upload_with_invalid_json(self, json_file):
+        # Load a model from Kaggle to run tests on it.
+        preset = "distil_bert_base_en"
+        backbone = DistilBertBackbone.from_preset(preset)
+        tokenizer = DistilBertTokenizer.from_preset(preset)
+
+        # Save the model on a local directory.
+        temp_dir = self.get_temp_dir()
+        local_preset_dir = os.path.join(temp_dir, "distil_bert_preset")
+        backbone.save_to_preset(local_preset_dir)
+        tokenizer.save_to_preset(local_preset_dir)
+
+        # Re-write json file content to an invalid format.
+        json_path = os.path.join(local_preset_dir, json_file)
+        with open(json_path, "w") as file:
+            file.write("Invalid!")
+
+        # Verify error handling.
+        with self.assertRaisesRegex(ValueError, "is an invalid json"):
+            upload_preset("kaggle://test/test/test", local_preset_dir)