mirror of https://github.com/hpcaitech/ColossalAI
[hotfix] fix testcase in test_fx/test_tracer (#5779)
* [fix] branch for fix testcase; * [fix] fix test_analyzer & test_auto_parallel; * [fix] remove local change about moe; * [fix] rm local change moe; * [fix] fix test_deepfm_model & test_dlrf_model; * [fix] fix test_hf_albert & test_hf_gpt;pull/5782/head
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@ -17,6 +17,11 @@ def test_albert():
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for name, (model_fn, data_gen_fn, _, _, _) in sub_registry.items():
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model = model_fn()
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# TODO: support the following models
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# 1. "AlbertForPreTraining"
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# as they are not supported, let's skip them
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if model.__class__.__name__ in ["AlbertForPreTraining"]:
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continue
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trace_model_and_compare_output(model, data_gen_fn)
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@ -16,9 +16,9 @@ def test_gpt():
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model = model_fn()
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# TODO(ver217): support the following models
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# 1. GPT2DoubleHeadsModel
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# 1. "GPT2DoubleHeadsModel", "GPT2ForQuestionAnswering", "GPTJForQuestionAnswering"
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# as they are not supported, let's skip them
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if model.__class__.__name__ in ["GPT2DoubleHeadsModel", "GPT2ForQuestionAnswering"]:
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if model.__class__.__name__ in ["GPT2DoubleHeadsModel", "GPT2ForQuestionAnswering", "GPTJForQuestionAnswering"]:
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continue
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trace_model_and_compare_output(model, data_gen_fn, ignore_data=["labels"])
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@ -52,7 +52,7 @@ def trace_and_compare(model_cls, data, output_transform_fn, meta_args=None):
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@clear_cache_before_run()
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def test_torchrec_deepfm_models():
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deepfm_models = model_zoo.get_sub_registry("deepfm")
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deepfm_models = model_zoo.get_sub_registry(keyword="deepfm", allow_empty=True)
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torch.backends.cudnn.deterministic = True
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for name, (model_fn, data_gen_fn, output_transform_fn, _, attribute) in deepfm_models.items():
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@ -53,7 +53,7 @@ def trace_and_compare(model_cls, data, output_transform_fn, meta_args=None):
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@clear_cache_before_run()
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def test_torchrec_dlrm_models():
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torch.backends.cudnn.deterministic = True
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dlrm_models = model_zoo.get_sub_registry("dlrm")
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dlrm_models = model_zoo.get_sub_registry(keyword="deepfm", allow_empty=True)
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for name, (model_fn, data_gen_fn, output_transform_fn, _, attribute) in dlrm_models.items():
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data = data_gen_fn()
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