本文整理汇总了Python中nets.resnet_utils.Block方法的典型用法代码示例。如果您正苦于以下问题：Python resnet_utils.Block方法的具体用法？Python resnet_utils.Block怎么用？Python resnet_utils.Block使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类nets.resnet_utils的用法示例。
在下文中一共展示了resnet_utils.Block方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: resnet_v2_block
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
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
}] * (num_units - 1) + [{
'depth': base_depth * 4,
'depth_bottleneck': base_depth,
'stride': stride
}]) 示例2: resnet_v1_block
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_block(scope, base_depth, num_units, stride):
"""Helper function for creating a resnet_v1 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_v1 bottleneck block.
"""
return resnet_utils.Block(scope, bottleneck, [{
'depth': base_depth * 4,
'depth_bottleneck': base_depth,
'stride': 1
}] * (num_units - 1) + [{
'depth': base_depth * 4,
'depth_bottleneck': base_depth,
'stride': stride
}]) 示例3: resnet_v1_50
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_50(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v1_50'):
"""ResNet-50 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_utils.Block(
'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
resnet_utils.Block(
'block2', bottleneck, [(512, 128, 1)] * 3 + [(512, 128, 2)]),
resnet_utils.Block(
'block3', bottleneck, [(1024, 256, 1)] * 5 + [(1024, 256, 2)]),
resnet_utils.Block(
'block4', bottleneck, [(2048, 512, 1)] * 3)
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, reuse=reuse, scope=scope) 开发者ID:rayanelleuch，项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors，代码行数:23，代码来源:resnet_v1.py
示例4: resnet_v1_101
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v1_101'):
"""ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_utils.Block(
'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
resnet_utils.Block(
'block2', bottleneck, [(512, 128, 1)] * 3 + [(512, 128, 2)]),
resnet_utils.Block(
'block3', bottleneck, [(1024, 256, 1)] * 22 + [(1024, 256, 2)]),
resnet_utils.Block(
'block4', bottleneck, [(2048, 512, 1)] * 3)
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, reuse=reuse, scope=scope) 开发者ID:rayanelleuch，项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors，代码行数:23，代码来源:resnet_v1.py
示例5: resnet_v1_152
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_152(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v1_152'):
"""ResNet-152 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_utils.Block(
'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
resnet_utils.Block(
'block2', bottleneck, [(512, 128, 1)] * 7 + [(512, 128, 2)]),
resnet_utils.Block(
'block3', bottleneck, [(1024, 256, 1)] * 35 + [(1024, 256, 2)]),
resnet_utils.Block(
'block4', bottleneck, [(2048, 512, 1)] * 3)]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, reuse=reuse, scope=scope) 开发者ID:rayanelleuch，项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors，代码行数:22，代码来源:resnet_v1.py
示例6: resnet_v1_200
# 需要导入模块: from nets import resnet_utils [as 别名]
# 或者: from nets.resnet_utils import Block [as 别名]
def resnet_v1_200(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v1_200'):
"""ResNet-200 model of [2]. See resnet_v1() for arg and return description."""
blocks = [
resnet_utils.Block(
'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
resnet_utils.Block(
'block2', bottleneck, [(512, 128, 1)] * 23 + [(512, 128, 2)]),
resnet_utils.Block(
'block3', bottleneck, [(1024, 256, 1)] * 35 + [(1024, 256, 2)]),
resnet_utils.Block(
'block4', bottleneck, [(2048, 512, 1)] * 3)]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, reuse=reuse, scope=scope) 开发者ID:rayanelleuch，项目名称:Speed-accuracy-trade-offs-for-modern-convolutional-object-detectors，代码行数:22，代码来源:resnet_v1.py