本文整理匯總了Python中nets.mobilenet.mobilenet.op方法的典型用法代碼示例。如果您正苦於以下問題：Python mobilenet.op方法的具體用法？Python mobilenet.op怎麽用？Python mobilenet.op使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nets.mobilenet.mobilenet的用法示例。
在下文中一共展示了mobilenet.op方法的6個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: mbv3_op
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def mbv3_op(ef, n, k, s=1, act=tf.nn.relu, se=None, **kwargs):
"""Defines a single Mobilenet V3 convolution block.
Args:
ef: expansion factor
n: number of output channels
k: stride of depthwise
s: stride
act: activation function in inner layers
se: squeeze excite function.
**kwargs: passed to expanded_conv
Returns:
An object (lib._Op) for inserting in conv_def, representing this operation.
"""
return op(
ops.expanded_conv,
expansion_size=expand_input(ef),
kernel_size=(k, k),
stride=s,
num_outputs=n,
inner_activation_fn=act,
expansion_transform=se,
**kwargs) 示例2: _create_modified_mobilenet_config
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def _create_modified_mobilenet_config():
conv_defs = copy.deepcopy(mobilenet_v2.V2_DEF)
conv_defs['spec'][-1] = mobilenet.op(
slim.conv2d, stride=1, kernel_size=[1, 1], num_outputs=256)
return conv_defs 開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:7，代碼來源:ssd_mobilenet_v2_fpn_feature_extractor.py
示例3: testWithSplits
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def testWithSplits(self):
spec = copy.deepcopy(mobilenet_v2.V2_DEF)
spec['overrides'] = {
(ops.expanded_conv,): dict(split_expansion=2),
}
_, _ = mobilenet.mobilenet(
tf.placeholder(tf.float32, (10, 224, 224, 16)),
conv_defs=spec)
num_convs = len(find_ops('Conv2D'))
# All but 3 op has 3 conv operatore, the remainign 3 have one
# and there is one unaccounted.
self.assertEqual(num_convs, len(spec['spec']) * 3 - 5) 示例4: testDivisibleBy
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def testDivisibleBy(self):
tf.reset_default_graph()
mobilenet_v2.mobilenet(
tf.placeholder(tf.float32, (10, 224, 224, 16)),
conv_defs=mobilenet_v2.V2_DEF,
divisible_by=16,
min_depth=32)
s = [op.outputs[0].get_shape().as_list()[-1] for op in find_ops('Conv2D')]
s = set(s)
self.assertSameElements([32, 64, 96, 160, 192, 320, 384, 576, 960, 1280,
1001], s) 示例5: testDivisibleByWithArgScope
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def testDivisibleByWithArgScope(self):
tf.reset_default_graph()
# Verifies that depth_multiplier arg scope actually works
# if no default min_depth is provided.
with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32):
mobilenet_v2.mobilenet(
tf.placeholder(tf.float32, (10, 224, 224, 2)),
conv_defs=mobilenet_v2.V2_DEF,
depth_multiplier=0.1)
s = [op.outputs[0].get_shape().as_list()[-1] for op in find_ops('Conv2D')]
s = set(s)
self.assertSameElements(s, [32, 192, 128, 1001]) 示例6: testFineGrained
# 需要導入模塊: from nets.mobilenet import mobilenet [as 別名]
# 或者: from nets.mobilenet.mobilenet import op [as 別名]
def testFineGrained(self):
tf.reset_default_graph()
# Verifies that depth_multiplier arg scope actually works
# if no default min_depth is provided.
mobilenet_v2.mobilenet(
tf.placeholder(tf.float32, (10, 224, 224, 2)),
conv_defs=mobilenet_v2.V2_DEF,
depth_multiplier=0.01,
finegrain_classification_mode=True)
s = [op.outputs[0].get_shape().as_list()[-1] for op in find_ops('Conv2D')]
s = set(s)
# All convolutions will be 8->48, except for the last one.
self.assertSameElements(s, [8, 48, 1001, 1280])