Merge pull request #4856 from KKZ20/test/model_support_for_low_level_zero

[test] remove the redundant code of model output transformation in torchrec

docs/source/en/basics/booster_plugins.md

@@ -44,12 +44,6 @@ We've tested compatibility on some famous models, following models may not be su
 
 - `timm.models.convit_base`
 - dlrm and deepfm models in `torchrec`
-- `diffusers.VQModel`
-- `transformers.AlbertModel`
-- `transformers.AlbertForPreTraining`
-- `transformers.BertModel`
-- `transformers.BertForPreTraining`
-- `transformers.GPT2DoubleHeadsModel`
 
 Compatibility problems will be fixed in the future.
 

docs/source/zh-Hans/basics/booster_plugins.md

@@ -42,12 +42,6 @@ Zero-2 不支持局部梯度累积。如果您坚持使用，虽然可以积累
 
 - `timm.models.convit_base`
 - dlrm and deepfm models in `torchrec`
-- `diffusers.VQModel`
-- `transformers.AlbertModel`
-- `transformers.AlbertForPreTraining`
-- `transformers.BertModel`
-- `transformers.BertForPreTraining`
-- `transformers.GPT2DoubleHeadsModel`
 
 兼容性问题将在未来修复。
 

tests/kit/model_zoo/torchrec/torchrec.py

@@ -53,16 +53,6 @@ def output_transform_fn(x):
         return dict(output=x)
 
 
-def output_transform_fn(x):
-    if isinstance(x, KeyedTensor):
-        output = dict()
-        for key in x.keys():
-            output[key] = x[key]
-        return output
-    else:
-        return dict(output=x)
-
-
 def get_ebc():
     # EmbeddingBagCollection
     eb1_config = EmbeddingBagConfig(name="t1", embedding_dim=SHAPE, num_embeddings=SHAPE, feature_names=["f1"])