[fx/profiler] tuned the calculation of memory estimation (#1619)

* [fx] tuned the meta info and rotor solver.

* [fx] remove import.

* [fx] remove import.

* [fx] remove import.

* [fx] tune the meta calculations.

* [fx] polish comments.

* [fx] remove assertions.

* [fx] modify test cases.

* [fx] modify test cases.

* [fx] optimize import.

* [fx

tests/test_fx/test_meta/test_meta_trace.py

@@ -0,0 +1,48 @@
+import torchvision.models as tm
+import timm.models as tmm
+import torch
+from colossalai import META_COMPATIBILITY
+import pytest
+
+if META_COMPATIBILITY:
+    from colossalai.fx import meta_trace
+
+tm_models = [
+    tm.vgg11,
+    tm.resnet18,
+    tm.densenet121,
+    tm.mobilenet_v3_small,
+    tm.resnext50_32x4d,
+    tm.wide_resnet50_2,
+    tm.regnet_x_16gf,
+    tm.mnasnet0_5,
+    tm.efficientnet_b0,
+]
+
+tmm_models = [
+    tmm.resnest.resnest50d, tmm.beit.beit_base_patch16_224, tmm.cait.cait_s24_224, tmm.efficientnet.efficientnetv2_m,
+    tmm.resmlp_12_224, tmm.vision_transformer.vit_base_patch16_224, tmm.deit_base_distilled_patch16_224,
+    tmm.convnext.convnext_base, tmm.vgg.vgg11, tmm.dpn.dpn68, tmm.densenet.densenet121, tmm.rexnet.rexnet_100,
+    tmm.swin_transformer.swin_base_patch4_window7_224
+]
+
+
+@pytest.mark.skipif(not META_COMPATIBILITY, reason='torch version is lower than 1.12.0')
+def test_torchvision_models_trace():
+    for m in tm_models:
+        model = m()
+        data = torch.rand(1000, 3, 224, 224, device='meta')
+        graph = meta_trace(model, torch.device('cpu'), data)
+
+
+@pytest.mark.skipif(not META_COMPATIBILITY, reason='torch version is lower than 1.12.0')
+def test_timm_models_trace():
+    for m in tmm_models:
+        model = m()
+        data = torch.rand(1000, 3, 224, 224, device='meta')
+        graph = meta_trace(model, torch.device('cpu'), data)
+
+
+if __name__ == '__main__':
+    test_torchvision_models_trace()
+    test_timm_models_trace()