Update: Test for Compatibility with Transformers 4.48 (#239)

* Update: test for new transformers release

* fix bug

* check layers exist with counting

---------

Co-authored-by: George Ohashi <[email protected]>

Author: rahul-tuli

tests/test_quantization/lifecycle/test_apply.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import re
+from collections import defaultdict
 from typing import Optional
 from unittest.mock import MagicMock
 
@@ -114,31 +115,36 @@ def test_apply_quantization_config_tinyllama():
     for module in model.modules():
         _test_layer_quantization_status(module, inputs=False, weights=False)
 
+    count_layer_names = ("Linear", "Embeddidng", "LlamaRotaryEmbedding")
+    count_layer_num = defaultdict(int)
+
+    for name, module in model.named_modules():
+        if name in quant_config.ignore:
+            continue
+        module_type = module.__class__.__name__
+        if module_type in count_layer_names:
+            count_layer_num[module_type] += 1
+
+    assert len(count_layer_num) > 0, f"None of {count_layer_names} found in model"
+    assert all(value > 0 for value in count_layer_num.values())
+
     # apply quant config to model
     apply_quantization_config(model, quant_config)
 
     # check for correct application of quant config
-    num_linears = 0
-    num_embeddings = 0
-    num_rotary_embeddings = 0
     for name, module in model.named_modules():
         if name in quant_config.ignore:
             continue
         module_type = module.__class__.__name__
-        if module_type == "Linear":
-            num_linears += 1
-            _test_layer_quantization_status(module, inputs=True, weights=True)
-        elif module_type == "Embedding":
-            num_embeddings += 1
-            _test_layer_quantization_status(module, inputs=False, weights=True)
-        elif module_type == "LlamaRotaryEmbedding":
-            num_rotary_embeddings += 1
-            _test_layer_quantization_status(module, inputs=False, weights=False)
-
-    # sanity check correct number of layers targeted
-    assert num_linears == 154  # 155 Linear layers - 1 that gets ignored
-    assert num_embeddings == 1
-    assert num_rotary_embeddings == 23  # model updated, now has model.rotary_embedding
+        if module_type in count_layer_names:
+            count_layer_num[module_type] -= 1
+            _inputs = module_type == "Linear"
+            _weights = not module_type == "LlamaRotaryEmbedding"
+            _test_layer_quantization_status(module, inputs=_inputs, weights=_weights)
+
+    assert all(
+        value == 0 for value in count_layer_num.values()
+    ), "Not all values are zero"
 
     # test quantization compression
     # sample forward pass to fill scales, zps