本文整理汇总了Python中nets.overfeat.overfeat方法的典型用法代码示例。如果您正苦于以下问题：Python overfeat.overfeat方法的具体用法？Python overfeat.overfeat怎么用？Python overfeat.overfeat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.overfeat的用法示例。
在下文中一共展示了overfeat.overfeat方法的9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: testEndPoints
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testEndPoints(self):
batch_size = 5
height, width = 231, 231
num_classes = 1000
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
_, end_points = overfeat.overfeat(inputs, num_classes)
expected_names = ['overfeat/conv1',
'overfeat/pool1',
'overfeat/conv2',
'overfeat/pool2',
'overfeat/conv3',
'overfeat/conv4',
'overfeat/conv5',
'overfeat/pool5',
'overfeat/fc6',
'overfeat/fc7',
'overfeat/fc8'
]
self.assertSetEqual(set(end_points.keys()), set(expected_names)) 示例2: testNoClasses
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testNoClasses(self):
batch_size = 5
height, width = 231, 231
num_classes = None
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
net, end_points = overfeat.overfeat(inputs, num_classes)
expected_names = ['overfeat/conv1',
'overfeat/pool1',
'overfeat/conv2',
'overfeat/pool2',
'overfeat/conv3',
'overfeat/conv4',
'overfeat/conv5',
'overfeat/pool5',
'overfeat/fc6',
'overfeat/fc7'
]
self.assertSetEqual(set(end_points.keys()), set(expected_names))
self.assertTrue(net.op.name.startswith('overfeat/fc7')) 示例3: testTrainEvalWithReuse
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testTrainEvalWithReuse(self):
train_batch_size = 2
eval_batch_size = 1
train_height, train_width = 231, 231
eval_height, eval_width = 281, 281
num_classes = 1000
with self.test_session():
train_inputs = tf.random_uniform(
(train_batch_size, train_height, train_width, 3))
logits, _ = overfeat.overfeat(train_inputs)
self.assertListEqual(logits.get_shape().as_list(),
[train_batch_size, num_classes])
tf.get_variable_scope().reuse_variables()
eval_inputs = tf.random_uniform(
(eval_batch_size, eval_height, eval_width, 3))
logits, _ = overfeat.overfeat(eval_inputs, is_training=False,
spatial_squeeze=False)
self.assertListEqual(logits.get_shape().as_list(),
[eval_batch_size, 2, 2, num_classes])
logits = tf.reduce_mean(logits, [1, 2])
predictions = tf.argmax(logits, 1)
self.assertEquals(predictions.get_shape().as_list(), [eval_batch_size]) 示例4: testBuild
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testBuild(self):
batch_size = 5
height, width = 231, 231
num_classes = 1000
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
logits, _ = overfeat.overfeat(inputs, num_classes)
self.assertEquals(logits.op.name, 'overfeat/fc8/squeezed')
self.assertListEqual(logits.get_shape().as_list(),
[batch_size, num_classes]) 示例5: testFullyConvolutional
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testFullyConvolutional(self):
batch_size = 1
height, width = 281, 281
num_classes = 1000
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
logits, _ = overfeat.overfeat(inputs, num_classes, spatial_squeeze=False)
self.assertEquals(logits.op.name, 'overfeat/fc8/BiasAdd')
self.assertListEqual(logits.get_shape().as_list(),
[batch_size, 2, 2, num_classes]) 示例6: testModelVariables
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testModelVariables(self):
batch_size = 5
height, width = 231, 231
num_classes = 1000
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
overfeat.overfeat(inputs, num_classes)
expected_names = ['overfeat/conv1/weights',
'overfeat/conv1/biases',
'overfeat/conv2/weights',
'overfeat/conv2/biases',
'overfeat/conv3/weights',
'overfeat/conv3/biases',
'overfeat/conv4/weights',
'overfeat/conv4/biases',
'overfeat/conv5/weights',
'overfeat/conv5/biases',
'overfeat/fc6/weights',
'overfeat/fc6/biases',
'overfeat/fc7/weights',
'overfeat/fc7/biases',
'overfeat/fc8/weights',
'overfeat/fc8/biases',
]
model_variables = [v.op.name for v in slim.get_model_variables()]
self.assertSetEqual(set(model_variables), set(expected_names)) 示例7: testEvaluation
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testEvaluation(self):
batch_size = 2
height, width = 231, 231
num_classes = 1000
with self.test_session():
eval_inputs = tf.random_uniform((batch_size, height, width, 3))
logits, _ = overfeat.overfeat(eval_inputs, is_training=False)
self.assertListEqual(logits.get_shape().as_list(),
[batch_size, num_classes])
predictions = tf.argmax(logits, 1)
self.assertListEqual(predictions.get_shape().as_list(), [batch_size]) 示例8: testForward
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testForward(self):
batch_size = 1
height, width = 231, 231
with self.test_session() as sess:
inputs = tf.random_uniform((batch_size, height, width, 3))
logits, _ = overfeat.overfeat(inputs)
sess.run(tf.global_variables_initializer())
output = sess.run(logits)
self.assertTrue(output.any()) 示例9: testGlobalPool
# 需要导入模块: from nets import overfeat [as 别名]
# 或者: from nets.overfeat import overfeat [as 别名]
def testGlobalPool(self):
batch_size = 1
height, width = 281, 281
num_classes = 1000
with self.test_session():
inputs = tf.random_uniform((batch_size, height, width, 3))
logits, _ = overfeat.overfeat(inputs, num_classes, spatial_squeeze=False,
global_pool=True)
self.assertEquals(logits.op.name, 'overfeat/fc8/BiasAdd')
self.assertListEqual(logits.get_shape().as_list(),
[batch_size, 1, 1, num_classes])