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[PaddlePaddle Hackathon] add ShuffleNetV2 #36313

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[PaddlePaddle Hackathon] add ShuffleNetV2 #36313

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3393fa6
Create shufflenetv2.py
tt8000 Oct 8, 2021
d9dcd18
Create __init__.py
tt8000 Oct 8, 2021
3a65412
Update __init__.py
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5ba9bb2
Update shufflenetv2.py
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Update shufflenetv2.py
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Update test_pretrained_model.py
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Update test_vision_models.py
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Update __init__.py
tt8000 Oct 9, 2021
87b6c74
Update shufflenetv2.py
tt8000 Oct 9, 2021
be4c2a9
Update shufflenetv2.py
tt8000 Oct 9, 2021
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Update test_pretrained_model.py
tt8000 Oct 9, 2021
d1d76d3
Create shufflenetv2.py
tt8000 Oct 9, 2021
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Update shufflenetv2.py
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Update shufflenetv2.py
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Update test_pretrained_model.py
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Update test_vision_models.py
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Update shufflenetv2.py
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5 changes: 4 additions & 1 deletion python/paddle/tests/test_pretrained_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,10 @@ def infer(self, arch):
np.testing.assert_allclose(res['dygraph'], res['static'])

def test_models(self):
arches = ['mobilenet_v1', 'mobilenet_v2', 'resnet18', 'vgg16']
arches = [
'mobilenet_v1', 'mobilenet_v2', 'resnet18', 'vgg16',
'shufflenetv2_swish'
]
for arch in arches:
self.infer(arch)

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23 changes: 22 additions & 1 deletion python/paddle/tests/test_vision_models.py
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Expand Up @@ -70,6 +70,27 @@ def test_resnet101(self):

def test_resnet152(self):
self.models_infer('resnet152')

def test_shufflenetv2_x0_25(self):
self.models_infer('shufflenetv2_x0_25')

def test_shufflenetv2_x0_33(self):
self.models_infer('shufflenetv2_x0_33')

def test_shufflenetv2_x0_5(self):
self.models_infer('shufflenetv2_x0_5')

def test_shufflenetv2_x1_0(self):
self.models_infer('shufflenetv2_x1_0')

def test_shufflenetv2_x1_5(self):
self.models_infer('shufflenetv2_x1_5')

def test_shufflenetv2_x2_0(self):
self.models_infer('shufflenetv2_x2_0')

def test_shufflenetv2_swish(self):
self.models_infer('shufflenetv2_swish')

def test_vgg16_num_classes(self):
vgg16 = models.__dict__['vgg16'](pretrained=False, num_classes=10)
Expand All @@ -81,7 +102,7 @@ def test_lenet(self):

x = np.array(np.random.random((2, 1, 28, 28)), dtype=np.float32)
lenet.predict_batch(x)


if __name__ == '__main__':
unittest.main()
8 changes: 8 additions & 0 deletions python/paddle/vision/__init__.py
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Expand Up @@ -44,6 +44,14 @@
from .models import vgg16 # noqa: F401
from .models import vgg19 # noqa: F401
from .models import LeNet # noqa: F401
from .models import ShuffleNetV2 # noqa: F401
from .models import shufflenetv2_x0_25 # noqa: F401
from .models import shufflenetv2_x0_33 # noqa: F401
from .models import shufflenetv2_x0_5 # noqa: F401
from .models import shufflenetv2_x1_0 # noqa: F401
from .models import shufflenetv2_x1_5 # noqa: F401
from .models import shufflenetv2_x2_0 # noqa: F401
from .models import shufflenetv2_swish # noqa: F401
from .transforms import BaseTransform # noqa: F401
from .transforms import Compose # noqa: F401
from .transforms import Resize # noqa: F401
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19 changes: 18 additions & 1 deletion python/paddle/vision/models/__init__.py
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Expand Up @@ -28,6 +28,15 @@
from .vgg import vgg16 # noqa: F401
from .vgg import vgg19 # noqa: F401
from .lenet import LeNet # noqa: F401
from .shufflenetv2 import ShuffleNetV2 # noqa: F401
from .shufflenetv2 import shufflenetv2_x0_25 # noqa: F401
from .shufflenetv2 import shufflenetv2_x0_33 # noqa: F401
from .shufflenetv2 import shufflenetv2_x0_5 # noqa: F401
from .shufflenetv2 import shufflenetv2_x1_0 # noqa: F401
from .shufflenetv2 import shufflenetv2_x1_5 # noqa: F401
from .shufflenetv2 import shufflenetv2_x2_0 # noqa: F401
from .shufflenetv2 import shufflenetv2_swish # noqa: F401


__all__ = [ #noqa
'ResNet',
Expand All @@ -45,5 +54,13 @@
'mobilenet_v1',
'MobileNetV2',
'mobilenet_v2',
'LeNet'
'LeNet',
'ShuffleNetV2',
'shufflenetv2_x0_25',
'shufflenetv2_x0_33',
'shufflenetv2_x0_5',
'shufflenetv2_x1_0',
'shufflenetv2_x1_5',
'shufflenetv2_x2_0',
'shufflenetv2_swish'
]
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