Revert Workaround of Disabling QWEN2_VL in Convergence Tests (#466)

## Summary

After fix #464

We can revert some changes in

- #463
- #459

Which are workarounds of

#461

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- [X] run `make test-convergence` to ensure convergence

---------

Signed-off-by: Austin Liu <[email protected]>

test/convergence/test_mini_models_multimodal.py

@@ -16,9 +16,7 @@
 
 import pytest
 import torch
-import transformers
 from datasets import load_dataset
-from packaging import version
 from torch.utils.data import DataLoader
 from transformers import PreTrainedTokenizerFast
 
@@ -380,9 +378,8 @@ def run_mini_model_multimodal(
             5e-3,
             1e-5,
             marks=pytest.mark.skipif(
-                not QWEN2_VL_AVAILABLE
-                or version.parse(transformers.__version__) >= version.parse("4.47.0"),
-                reason="Qwen2-VL not available in this version of transformers or transformers version >= 4.47.0",
+                not QWEN2_VL_AVAILABLE,
+                reason="Qwen2-VL not available in this version of transformers",
             ),
         ),
         pytest.param(
@@ -401,10 +398,8 @@ def run_mini_model_multimodal(
                     not supports_bfloat16(), reason="bfloat16 not supported on this GPU"
                 ),
                 pytest.mark.skipif(
-                    not QWEN2_VL_AVAILABLE
-                    or version.parse(transformers.__version__)
-                    >= version.parse("4.47.0"),
-                    reason="Qwen2-VL not available in this version of transformers or transformers version >= 4.47.0",
+                    not QWEN2_VL_AVAILABLE,
+                    reason="Qwen2-VL not available in this version of transformers",
                 ),
             ],
         ),

test/convergence/test_mini_models_with_logits.py

@@ -18,9 +18,7 @@
 
 import pytest
 import torch
-import transformers
 from datasets import load_from_disk
-from packaging import version
 from torch.utils.data import DataLoader
 from transformers.models.gemma import GemmaConfig, GemmaForCausalLM
 from transformers.models.gemma2 import Gemma2Config, Gemma2ForCausalLM
@@ -540,9 +538,8 @@ def run_mini_model(
             5e-3,
             1e-5,
             marks=pytest.mark.skipif(
-                not QWEN2_VL_AVAILABLE
-                or version.parse(transformers.__version__) >= version.parse("4.47.0"),
-                reason="Qwen2-VL not available in this version of transformers or transformers version >= 4.47.0",
+                not QWEN2_VL_AVAILABLE,
+                reason="Qwen2-VL not available in this version of transformers",
             ),
         ),
         pytest.param(
@@ -561,10 +558,8 @@ def run_mini_model(
                     not supports_bfloat16(), reason="bfloat16 not supported on this GPU"
                 ),
                 pytest.mark.skipif(
-                    not QWEN2_VL_AVAILABLE
-                    or version.parse(transformers.__version__)
-                    >= version.parse("4.47.0"),
-                    reason="Qwen2-VL not available in this version of transformers or transformers version >= 4.47.0",
+                    not QWEN2_VL_AVAILABLE,
+                    reason="Qwen2-VL not available in this version of transformers",
                 ),
             ],
         ),