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Fix / improve tests for features

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Ross Wightman 2024-04-10 21:14:02 -07:00
parent 4b2565e4cb
commit fe3cf542fa
1 changed files with 6 additions and 6 deletions
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12
tests/test_models.py
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@ -55,8 +55,8 @@ FEAT_INTER_FILTERS = [
# transformer models don't support many of the spatial / feature based model functionalities # transformer models don't support many of the spatial / feature based model functionalities
NON_STD_FILTERS = [ NON_STD_FILTERS = [
'vit_*', 'tnt_*', 'pit_*', 'coat_*', 'cait_*', '*mixer_*', 'gmlp_*', 'resmlp_*', 'twins_*', 'vit_*', 'tnt_*', 'pit_*', 'coat_*', 'cait_*', '*mixer_*', 'gmlp_*', 'resmlp_*', 'twins_*',
'convit_*', 'levit*', 'visformer*', 'deit*', 'jx_nest_*', 'nest_*', 'xcit_*', 'crossvit_*', 'beit*', 'convit_*', 'levit*', 'visformer*', 'deit*', 'xcit_*', 'crossvit_*', 'beit*',
'poolformer_*', 'volo_*', 'sequencer2d_*', 'pvt_v2*', 'mvitv2*', 'gcvit*', 'efficientformer*', 'poolformer_*', 'volo_*', 'sequencer2d_*', 'mvitv2*', 'gcvit*', 'efficientformer*',
'eva_*', 'flexivit*', 'eva02*', 'samvit_*', 'efficientvit_m*', 'tiny_vit_*' 'eva_*', 'flexivit*', 'eva02*', 'samvit_*', 'efficientvit_m*', 'tiny_vit_*'
] ]
NUM_NON_STD = len(NON_STD_FILTERS) NUM_NON_STD = len(NON_STD_FILTERS)
@ -356,7 +356,7 @@ if 'GITHUB_ACTIONS' in os.environ: # and 'Linux' in platform.system():
@pytest.mark.features @pytest.mark.features
@pytest.mark.timeout(120) @pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FEAT_FILTERS, include_tags=True)) @pytest.mark.parametrize('model_name', list_models(exclude_filters=EXCLUDE_FILTERS + EXCLUDE_FEAT_FILTERS))
@pytest.mark.parametrize('batch_size', [1]) @pytest.mark.parametrize('batch_size', [1])
def test_model_forward_features(model_name, batch_size): def test_model_forward_features(model_name, batch_size):
"""Run a single forward pass with each model in feature extraction mode""" """Run a single forward pass with each model in feature extraction mode"""
@ -364,7 +364,7 @@ def test_model_forward_features(model_name, batch_size):
model.eval() model.eval()
expected_channels = model.feature_info.channels() expected_channels = model.feature_info.channels()
expected_reduction = model.feature_info.reduction() expected_reduction = model.feature_info.reduction()
assert len(expected_channels) >= 4 # all models here should have at least 4 feature levels by default, some 5 or 6 assert len(expected_channels) >= 3 # all models here should have at least 3 default feat levels
input_size = _get_input_size(model=model, target=TARGET_FFEAT_SIZE) input_size = _get_input_size(model=model, target=TARGET_FFEAT_SIZE)
if max(input_size) > MAX_FFEAT_SIZE: if max(input_size) > MAX_FFEAT_SIZE:
@ -387,7 +387,7 @@ def test_model_forward_features(model_name, batch_size):
@pytest.mark.features @pytest.mark.features
@pytest.mark.timeout(120) @pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models(FEAT_INTER_FILTERS, include_tags=True)) @pytest.mark.parametrize('model_name', list_models(FEAT_INTER_FILTERS, exclude_filters=EXCLUDE_FILTERS))
@pytest.mark.parametrize('batch_size', [1]) @pytest.mark.parametrize('batch_size', [1])
def test_model_forward_intermediates_features(model_name, batch_size): def test_model_forward_intermediates_features(model_name, batch_size):
"""Run a single forward pass with each model in feature extraction mode""" """Run a single forward pass with each model in feature extraction mode"""
@ -419,7 +419,7 @@ def test_model_forward_intermediates_features(model_name, batch_size):
@pytest.mark.features @pytest.mark.features
@pytest.mark.timeout(120) @pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models(FEAT_INTER_FILTERS, include_tags=True)) @pytest.mark.parametrize('model_name', list_models(FEAT_INTER_FILTERS, exclude_filters=EXCLUDE_FILTERS))
@pytest.mark.parametrize('batch_size', [1]) @pytest.mark.parametrize('batch_size', [1])
def test_model_forward_intermediates(model_name, batch_size): def test_model_forward_intermediates(model_name, batch_size):
"""Run a single forward pass with each model in feature extraction mode""" """Run a single forward pass with each model in feature extraction mode"""