def ResNet101V2(
include_top=True,
weights="imagenet",
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
classifier_activation="softmax",
):
"""Instantiates the ResNet101V2 architecture."""
def stack_fn(x):
x = resnet.stack2(x, 64, 3, name="conv2")
x = resnet.stack2(x, 128, 4, name="conv3")
x = resnet.stack2(x, 256, 23, name="conv4")
return resnet.stack2(x, 512, 3, stride1=1, name="conv5")
return resnet.ResNet(
stack_fn,
True,
True,
"resnet101v2",
include_top,
weights,
input_tensor,
input_shape,
pooling,
classes,
classifier_activation=classifier_activation,
)
def ResNet152V2(
include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
classifier_activation='softmax'):
"""Instantiates the ResNet152V2 architecture."""
def stack_fn(x):
x = resnet.stack2(x, 64, 3, name='conv2')
x = resnet.stack2(x, 128, 8, name='conv3')
x = resnet.stack2(x, 256, 36, name='conv4')
return resnet.stack2(x, 512, 3, stride1=1, name='conv5')
return resnet.ResNet(
stack_fn,
True,
True,
'resnet152v2',
include_top,
weights,
input_tensor,
input_shape,
pooling,
classes,
classifier_activation=classifier_activation)
def resnet_v1_18(include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
classifier_activation='softmax'):
"""Instantiates the ResNet18 architecture."""
def stack_fn(x):
x = stack_basic(x, 64, 2, stride1=1, name='conv2')
x = stack_basic(x, 128, 2, name='conv3')
x = stack_basic(x, 256, 2, name='conv4')
return stack_basic(x, 512, 2, name='conv5')
return resnet.ResNet(stack_fn,
True,
True,
'resnet18',
include_top,
weights,
input_tensor,
input_shape,
pooling,
classes,
classifier_activation=classifier_activation)
