Change GRANITE_VISION_MODEL_NAME to TINY_GRANITE_VISION_MODEL_NAME

Signed-off-by: Abhishek <maurya.abhishek@ibm.com>

Author: Abhishek-TAMU

tests/artifacts/vision_models/__init__.py

@@ -19,7 +19,7 @@
 
 ### Constants used for model path
 PREDEFINED_MODEL_PATH = os.path.join(os.path.dirname(__file__))
-LLAMA_VISION_MODEL_NAME = os.path.join(PREDEFINED_MODEL_PATH, "tiny_llama_vision_model")
-GRANITE_VISION_MODEL_NAME = os.path.join(
+TINY_LLAMA_VISION_MODEL_NAME = os.path.join(PREDEFINED_MODEL_PATH, "tiny_llama_vision_model")
+TINY_GRANITE_VISION_MODEL_NAME = os.path.join(
     PREDEFINED_MODEL_PATH, "tiny_granite_vision_model"
 )

tests/data/test_data_preprocessing.py

@@ -62,8 +62,8 @@
     TWITTER_COMPLAINTS_TOKENIZED_PARQUET,
 )
 from tests.artifacts.vision_models import (
-    GRANITE_VISION_MODEL_NAME,
-    LLAMA_VISION_MODEL_NAME,
+    TINY_GRANITE_VISION_MODEL_NAME,
+    TINY_LLAMA_VISION_MODEL_NAME,
 )
 
 # Local
@@ -1843,7 +1843,7 @@ def test_get_processed_dataset(datafile, datasetconfigname):
 
 @pytest.mark.parametrize(
     "model_name",
-    [LLAMA_VISION_MODEL_NAME, GRANITE_VISION_MODEL_NAME],
+    [TINY_LLAMA_VISION_MODEL_NAME, TINY_GRANITE_VISION_MODEL_NAME],
 )
 def test_vision_data_collator(model_name):
     """Test the VisionDataCollator with dummy Image data."""

tests/utils/test_embedding_resize.py

@@ -29,7 +29,7 @@
 
 # First Party
 from tests.artifacts.testdata import CUSTOM_TOKENIZER_TINYLLAMA
-from tests.artifacts.vision_models import LLAMA_VISION_MODEL_NAME
+from tests.artifacts.vision_models import TINY_LLAMA_VISION_MODEL_NAME
 
 # Local
 from tuning.utils.tokenizer_data_utils import tokenizer_and_embedding_resize
@@ -209,8 +209,8 @@ def test_resize_with_multiple_of():
 
 
 def test_resize_llama_vision_model():
-    model = AutoModelForVision2Seq.from_pretrained(LLAMA_VISION_MODEL_NAME)
-    processor = AutoProcessor.from_pretrained(LLAMA_VISION_MODEL_NAME)
+    model = AutoModelForVision2Seq.from_pretrained(TINY_LLAMA_VISION_MODEL_NAME)
+    processor = AutoProcessor.from_pretrained(TINY_LLAMA_VISION_MODEL_NAME)
     tokenizer = processor.tokenizer
 
     current_input_embeddings = model.get_input_embeddings()