本文整理汇总了Python中tensorflow.contrib.slim.nets.resnet_v2.resnet_v2_101方法的典型用法代码示例。如果您正苦于以下问题：Python resnet_v2.resnet_v2_101方法的具体用法？Python resnet_v2.resnet_v2_101怎么用？Python resnet_v2.resnet_v2_101使用的例子？那么, 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_v2的用法示例。
在下文中一共展示了resnet_v2.resnet_v2_101方法的11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_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(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."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
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) 示例2: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=False,
reuse=None,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
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) 示例3: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=tf.AUTO_REUSE,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
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) 示例4: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
multi_grid=[1, 2, 4],
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."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
return resnet_v2(inputs, blocks, num_classes, is_training=is_training,
global_pool=global_pool, output_stride=output_stride, multi_grid=multi_grid,
include_root_block=True, spatial_squeeze=spatial_squeeze,
reuse=reuse, scope=scope) 示例5: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=False,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
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) 示例6: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() 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_v2(inputs, blocks, num_classes, is_training=is_training,
global_pool=global_pool, output_stride=output_stride,
include_root_block=True, reuse=reuse, scope=scope) 示例7: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
is_training=True,
global_pool=True,
output_stride=None,
spatial_squeeze=True,
reuse=None,
scope='resnet_v2_101',
attention_module=None):
"""ResNet-101 model of [1]. See resnet_v2() for arg and return description."""
blocks = [
resnet_v2_block('block1', base_depth=64, num_units=3, stride=2, attention_module=attention_module),
resnet_v2_block('block2', base_depth=128, num_units=4, stride=2, attention_module=attention_module),
resnet_v2_block('block3', base_depth=256, num_units=23, stride=2, attention_module=attention_module),
resnet_v2_block('block4', base_depth=512, num_units=3, stride=1, attention_module=attention_module),
]
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) 示例8: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(inputs,
num_classes=None,
global_pool=True,
output_stride=None,
reuse=None,
scope='resnet_v2_101'):
"""ResNet-101 model of [1]. See resnet_v2() 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_v2(inputs, blocks, num_classes, global_pool, output_stride,
include_root_block=True, reuse=reuse, scope=scope) 示例9: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(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."""
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_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) 示例10: forward
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def forward(self, inputs, num_classes, data_format, is_training):
sc = resnet_arg_scope(
weight_decay=0.0001,
data_format=data_format,
batch_norm_decay=0.997,
batch_norm_epsilon=1e-5,
batch_norm_scale=True,
activation_fn=tf.nn.relu,
use_batch_norm=True,
is_training=is_training)
with slim.arg_scope(sc):
logits, end_points = resnet_v2_101(
inputs,
num_classes=num_classes,
is_training=is_training,
global_pool=True,
output_stride=None,
reuse=None,
scope=self.scope)
return logits, end_points 示例11: resnet_v2_101
# 需要导入模块: from tensorflow.contrib.slim.nets import resnet_v2 [as 别名]
# 或者: from tensorflow.contrib.slim.nets.resnet_v2 import resnet_v2_101 [as 别名]
def resnet_v2_101(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."""
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_v2_block('block4', base_depth=512, num_units=3, stride=1),
]
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)