github/ColossalAI
1
0
Fork 0
mirror of https://github.com/hpcaitech/ColossalAI.git synced 2025-09-05 11:02:05 +00:00
Code Issues Packages Projects Releases Wiki Activity

[misc] update pre-commit and run all files (#4752)

Browse Source 
* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
tests/test_analyzer/test_fx/test_shape_prop.py
View File

@@ -1,6 +1,5 @@
import pytest
import torch
import torchvision.models as tm
from packaging import version
from colossalai.testing.utils import clear_cache_before_run, parameterize
@@ -16,24 +15,25 @@ try:
def linear_impl(*args, **kwargs):
assert True
return torch.nn.functional.linear(*args, **kwargs)
except:
pass
def _check_gm_validity(gm: torch.fx.GraphModule):
for node in gm.graph.nodes:
assert node.meta['info'].outputs, f'In {gm.__class__.__name__}, {node} has no output shape.'
assert node.meta["info"].outputs, f"In {gm.__class__.__name__}, {node} has no output shape."
if node.op in [
'call_module', # can apply to params
'call_function', # can apply to params
'call_method', # can apply to params
"call_module", # can apply to params
"call_function", # can apply to params
"call_method", # can apply to params
]:
assert hasattr(node.meta['info'], 'inputs'), f'In {gm.__class__.__name__}, {node} has no input shape.'
assert hasattr(node.meta["info"], "inputs"), f"In {gm.__class__.__name__}, {node} has no input shape."
@pytest.mark.skipif(version.parse(torch.__version__) < version.parse('1.12.0'), reason='torch version < 12')
@pytest.mark.skipif(version.parse(torch.__version__) < version.parse("1.12.0"), reason="torch version < 12")
@clear_cache_before_run()
@parameterize('m', tm_models)
@parameterize("m", tm_models)
def test_torchvision_shape_prop(m):
with MetaTensorMode():
model = m()
@@ -46,9 +46,9 @@ def test_torchvision_shape_prop(m):
_check_gm_validity(gm)
@pytest.mark.skipif(version.parse(torch.__version__) < version.parse('1.12.0'), reason='torch version < 12')
@pytest.mark.skipif(version.parse(torch.__version__) < version.parse("1.12.0"), reason="torch version < 12")
@clear_cache_before_run()
@parameterize('m', tmm_models)
@parameterize("m", tmm_models)
def test_timm_shape_prop(m):
with MetaTensorMode():
model = m()