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Python源码示例：nets.nasnet.nasnet.large_imagenet_config()

示例1

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例2

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例3

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例4

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例5

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例6

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例7

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例8

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例9

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例10

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例11

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例12

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例13

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例14

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例15

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例16

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例17

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例18

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例19

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例20

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例21

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random.uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例22

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random.uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

示例23

def testNoAuxHeadLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    for use_aux_head in (True, False):
      tf.reset_default_graph()
      inputs = tf.random_uniform((batch_size, height, width, 3))
      tf.train.create_global_step()
      config = nasnet.large_imagenet_config()
      config.set_hparam('use_aux_head', int(use_aux_head))
      with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
        _, end_points = nasnet.build_nasnet_large(inputs, num_classes,
                                                  config=config)
      self.assertEqual('AuxLogits' in end_points, use_aux_head)

示例24

def testOverrideHParamsLargeModel(self):
    batch_size = 5
    height, width = 331, 331
    num_classes = 1000
    inputs = tf.random_uniform((batch_size, height, width, 3))
    tf.train.create_global_step()
    config = nasnet.large_imagenet_config()
    config.set_hparam('data_format', 'NCHW')
    with slim.arg_scope(nasnet.nasnet_large_arg_scope()):
      _, end_points = nasnet.build_nasnet_large(
          inputs, num_classes, config=config)
    self.assertListEqual(
        end_points['Stem'].shape.as_list(), [batch_size, 336, 42, 42])

Python源码示例：nets.nasnet.nasnet.large_imagenet_config()

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