本文整理汇总了Python中tensorflow.contrib.slim.nets.resnet_v1.resnet_v1_101方法的典型用法代码示例。如果您正苦于以下问题：Python resnet_v1.resnet_v1_101方法的具体用法？Python resnet_v1.resnet_v1_101怎么用？Python resnet_v1.resnet_v1_101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tensorflow.contrib.slim.nets.resnet_v1的用法示例。
在下文中一共展示了resnet_v1.resnet_v1_101方法的7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_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=None,
scope='resnet_v1_101'):
"""ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_v1_block('block1', base_depth=64, num_units=3, stride=2),
resnet_v1_block('block2', base_depth=128, num_units=4, stride=2),
resnet_v1_block('block3', base_depth=256, num_units=23, stride=2),
resnet_v1_block('block4', base_depth=512, num_units=3, stride=1),
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
reuse=reuse, scope=scope) 示例2: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
store_non_strided_activations=False,
reuse=None,
scope='resnet_v1_101'):
"""ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_v1_block('block1', base_depth=64, num_units=3, stride=2),
resnet_v1_block('block2', base_depth=128, num_units=4, stride=2),
resnet_v1_block('block3', base_depth=256, num_units=23, stride=2),
resnet_v1_block('block4', base_depth=512, num_units=3, stride=1),
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
store_non_strided_activations=store_non_strided_activations,
reuse=reuse, scope=scope) 示例3: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [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) 示例4: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
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, global_pool, output_stride,
include_root_block=True, reuse=reuse, scope=scope) 示例5: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
store_non_strided_activations=False,
reuse=False,
scope='resnet_v1_101'):
"""ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_v1_block('block1', base_depth=64, num_units=3, stride=2),
resnet_v1_block('block2', base_depth=128, num_units=4, stride=2),
resnet_v1_block('block3', base_depth=256, num_units=23, stride=2),
resnet_v1_block('block4', base_depth=512, num_units=3, stride=1),
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
store_non_strided_activations=store_non_strided_activations,
reuse=reuse, scope=scope) 示例6: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
store_non_strided_activations=False,
reuse=None,
scope='resnet_v1_101',
attention_module=None):
"""ResNet-101 model of [1]. See resnet_v1() for arg and return description."""
blocks = [
resnet_v1_block('block1', base_depth=64, num_units=3, stride=2, attention_module=attention_module),
resnet_v1_block('block2', base_depth=128, num_units=4, stride=2, attention_module=attention_module),
resnet_v1_block('block3', base_depth=256, num_units=23, stride=2, attention_module=attention_module),
resnet_v1_block('block4', base_depth=512, num_units=3, stride=1, attention_module=attention_module),
]
return resnet_v1(inputs, blocks, num_classes, is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, spatial_squeeze=spatial_squeeze,
store_non_strided_activations=store_non_strided_activations,
reuse=reuse, scope=scope) 示例7: resnet_v1_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v1 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v1 import resnet_v1_101 [as 别名]
def resnet_v1_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
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, spatial_squeeze=spatial_squeeze,
reuse=reuse, scope=scope)