def resnet_v2_101_multi(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=None,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
block3_rate = [1, 4, 2]
block3_rates = [
None, # 1
None, # 2
None, # 3
None, # 4
None, # 5
None, # 6
None, # 7
None, # 8
None, # 9
None, # 10
None, # 11
None, # 12
None, # 13
None, # 14
None, # 15
None, # 16
None, # 17
None, # 18
None, # 19
None, # 20
None, # 21
None, # 22
None # 23
]
block4_rates = [
1, 2, 4
]
blocks = [
resnet_v2_block('block1', base_depth=64, num_units=3, stride=2),
resnet_v2_block('block2', base_depth=128, num_units=4, stride=2),
resnet_utils.Block('block3', bottleneck, [
{'depth': 1024,
'depth_bottleneck': 256,
'stride': 2,
'scale_rates': rate} for rate in block3_rates]),
resnet_utils.Block('block4', bottleneck, [
{'depth': 2048,
'depth_bottleneck': 512,
'stride': 1,
'unit_rate': rate} for rate in block4_rates]),
]
return resnet_v2(inputs, blocks, num_classes, is_training=is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
reuse=reuse, scope=scope)
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
multi_grid=None,
reuse=None,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
if multi_grid is None:
multi_grid = _DEFAULT_MULTI_GRID
else:
if len(multi_grid) != 3:
raise ValueError('Expect multi_grid to have length 3.')
blocks = [
resnet_v2_block('block1', base_depth=64, num_units=3, stride=2),
resnet_v2_block('block2', base_depth=128, num_units=4, stride=2),
resnet_v2_block('block3', base_depth=256, num_units=23, stride=2),
resnet_utils.Block('block4', bottleneck, [
{'depth': 2048,
'depth_bottleneck': 512,
'stride': 1,
'unit_rate': rate} for rate in multi_grid]),
]
return resnet_v2(inputs, blocks, num_classes, is_training=is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
reuse=reuse, scope=scope)
def resnet_v2_block(scope, base_depth, num_units, stride):
"""Helper function for creating a resnet_v2 bottleneck block.
Args:
scope: The scope of the block.
base_depth: The depth of the bottleneck layer for each unit.
num_units: The number of units in the block.
stride: The stride of the block, implemented as a stride in the last unit.
All other units have stride=1.
Returns:
A resnet_v2 bottleneck block.
"""
return resnet_utils.Block(scope, bottleneck, [{
'depth': base_depth * 4,
'depth_bottleneck': base_depth,
'stride': 1,
'unit_rate': 1
}] * (num_units - 1) + [{
'depth': base_depth * 4,
'depth_bottleneck': base_depth,
'stride': stride,
'unit_rate': 1
}])
