本文整理匯總了Python中nets.inception.inception_v2_base方法的典型用法代碼示例。如果您正苦於以下問題：Python inception.inception_v2_base方法的具體用法？Python inception.inception_v2_base怎麽用？Python inception.inception_v2_base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.inception的用法示例。
在下文中一共展示了inception.inception_v2_base方法的7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: testBuildEndPointsWithUseSeparableConvolutionFalse
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildEndPointsWithUseSeparableConvolutionFalse(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
_, end_points = inception.inception_v2_base(inputs)
endpoint_keys = [
key for key in end_points.keys()
if key.startswith('Mixed') or key.startswith('Conv')
]
_, end_points_with_replacement = inception.inception_v2_base(
inputs, use_separable_conv=False)
# The endpoint shapes must be equal to the original shape even when the
# separable convolution is replaced with a normal convolution.
for key in endpoint_keys:
original_shape = end_points[key].get_shape().as_list()
self.assertTrue(key in end_points_with_replacement)
new_shape = end_points_with_replacement[key].get_shape().as_list()
self.assertListEqual(original_shape, new_shape) 示例2: testBuildBaseNetwork
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildBaseNetwork(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
mixed_5c, end_points = inception.inception_v2_base(inputs)
self.assertTrue(mixed_5c.op.name.startswith('InceptionV2/Mixed_5c'))
self.assertListEqual(mixed_5c.get_shape().as_list(),
[batch_size, 7, 7, 1024])
expected_endpoints = ['Mixed_3b', 'Mixed_3c', 'Mixed_4a', 'Mixed_4b',
'Mixed_4c', 'Mixed_4d', 'Mixed_4e', 'Mixed_5a',
'Mixed_5b', 'Mixed_5c', 'Conv2d_1a_7x7',
'MaxPool_2a_3x3', 'Conv2d_2b_1x1', 'Conv2d_2c_3x3',
'MaxPool_3a_3x3']
self.assertItemsEqual(end_points.keys(), expected_endpoints) 示例3: testBuildOnlyUptoFinalEndpoint
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildOnlyUptoFinalEndpoint(self):
batch_size = 5
height, width = 224, 224
endpoints = ['Conv2d_1a_7x7', 'MaxPool_2a_3x3', 'Conv2d_2b_1x1',
'Conv2d_2c_3x3', 'MaxPool_3a_3x3', 'Mixed_3b', 'Mixed_3c',
'Mixed_4a', 'Mixed_4b', 'Mixed_4c', 'Mixed_4d', 'Mixed_4e',
'Mixed_5a', 'Mixed_5b', 'Mixed_5c']
for index, endpoint in enumerate(endpoints):
with tf.Graph().as_default():
inputs = tf.random_uniform((batch_size, height, width, 3))
out_tensor, end_points = inception.inception_v2_base(
inputs, final_endpoint=endpoint)
self.assertTrue(out_tensor.op.name.startswith(
'InceptionV2/' + endpoint))
self.assertItemsEqual(endpoints[:index+1], end_points) 示例4: testBuildAndCheckAllEndPointsUptoMixed5c
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildAndCheckAllEndPointsUptoMixed5c(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
_, end_points = inception.inception_v2_base(inputs,
final_endpoint='Mixed_5c')
endpoints_shapes = {'Mixed_3b': [batch_size, 28, 28, 256],
'Mixed_3c': [batch_size, 28, 28, 320],
'Mixed_4a': [batch_size, 14, 14, 576],
'Mixed_4b': [batch_size, 14, 14, 576],
'Mixed_4c': [batch_size, 14, 14, 576],
'Mixed_4d': [batch_size, 14, 14, 576],
'Mixed_4e': [batch_size, 14, 14, 576],
'Mixed_5a': [batch_size, 7, 7, 1024],
'Mixed_5b': [batch_size, 7, 7, 1024],
'Mixed_5c': [batch_size, 7, 7, 1024],
'Conv2d_1a_7x7': [batch_size, 112, 112, 64],
'MaxPool_2a_3x3': [batch_size, 56, 56, 64],
'Conv2d_2b_1x1': [batch_size, 56, 56, 64],
'Conv2d_2c_3x3': [batch_size, 56, 56, 192],
'MaxPool_3a_3x3': [batch_size, 28, 28, 192]}
self.assertItemsEqual(endpoints_shapes.keys(), end_points.keys())
for endpoint_name in endpoints_shapes:
expected_shape = endpoints_shapes[endpoint_name]
self.assertTrue(endpoint_name in end_points)
self.assertListEqual(end_points[endpoint_name].get_shape().as_list(),
expected_shape) 示例5: testModelHasExpectedNumberOfParameters
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testModelHasExpectedNumberOfParameters(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
with slim.arg_scope(inception.inception_v2_arg_scope()):
inception.inception_v2_base(inputs)
total_params, _ = slim.model_analyzer.analyze_vars(
slim.get_model_variables())
self.assertAlmostEqual(10173112, total_params) 示例6: testBuildOnlyUptoFinalEndpoint
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildOnlyUptoFinalEndpoint(self):
batch_size = 5
height, width = 224, 224
endpoints = ['Conv2d_1a_7x7', 'MaxPool_2a_3x3', 'Conv2d_2b_1x1',
'Conv2d_2c_3x3', 'MaxPool_3a_3x3', 'Mixed_3b', 'Mixed_3c',
'Mixed_4a', 'Mixed_4b', 'Mixed_4c', 'Mixed_4d', 'Mixed_4e',
'Mixed_5a', 'Mixed_5b', 'Mixed_5c']
for index, endpoint in enumerate(endpoints):
with tf.Graph().as_default():
inputs = tf.random_uniform((batch_size, height, width, 3))
out_tensor, end_points = inception.inception_v2_base(
inputs, final_endpoint=endpoint)
self.assertTrue(out_tensor.op.name.startswith(
'InceptionV2/' + endpoint))
self.assertItemsEqual(endpoints[:index+1], end_points.keys()) 示例7: testBuildErrorsForDataFormats
# 需要導入模塊: from nets import inception [as 別名]
# 或者: from nets.inception import inception_v2_base [as 別名]
def testBuildErrorsForDataFormats(self):
batch_size = 5
height, width = 224, 224
inputs = tf.random_uniform((batch_size, height, width, 3))
# 'NCWH' data format is not supported.
with self.assertRaises(ValueError):
_ = inception.inception_v2_base(inputs, data_format='NCWH')
# 'NCHW' data format is not supported for separable convolution.
with self.assertRaises(ValueError):
_ = inception.inception_v2_base(inputs, data_format='NCHW')