[FX] refactor experimental tracer and adapt it with hf models (#3157)

* pass gpt trace and meta_prop

* pass t5 trace and meta_prop

* [FX] refactor experimental tracer and adapt it with hf models

* pass all mainstream model zoo

* fix CI

* fix CI

* fix CI

* fix CI

* fix CI

* fix CI

* fix CI

* fix CI

* skip tests

* fix CI

* using packaging version

* polish

tests/test_fx/test_tracer/test_torchaudio_model/test_torchaudio_model.py

@@ -1,20 +1,18 @@
-import re
-
+import pytest
 import torch
+from packaging import version
 from torchaudio_utils import trace_and_compare
 
 from tests.kit.model_zoo import model_zoo
 
 
+@pytest.mark.skipif(version.parse(torch.__version__) < version.parse('1.12.0'), reason='torch version < 12')
 def test_torchaudio_models():
     torch.backends.cudnn.deterministic = True
 
     sub_model_zoo = model_zoo.get_sub_registry('torchaudio')
 
     for name, (model_fn, data_gen_fn, output_transform_fn, attribute) in sub_model_zoo.items():
-        # FIXME(ver217): temporarily skip these models
-        if re.search(f'(conformer|emformer|tacotron|wav2vec2_base|hubert_base)', name):
-            continue
         model = model_fn()
         trace_and_compare(model,
                           data_gen_fn,

tests/test_fx/test_tracer/test_torchaudio_model/torchaudio_utils.py

@@ -1,6 +1,6 @@
 import torch
 
-from colossalai.fx import symbolic_trace
+from colossalai._analyzer.fx import symbolic_trace
 
 
 def trace_and_compare(model, data_gen, output_transform_fn, need_meta=False, need_concrete=False):