Python nets.nasnet.nasnet.large_imagenet_config() Examples

The following are 24 code examples of nets.nasnet.nasnet.large_imagenet_config(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module nets.nasnet.nasnet , or try the search function .
Example #1
Source File: nasnet_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up 
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)
Example #2
Source File: nasnet_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
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])
Example #3
Source File: nasnet_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
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)
Example #4
Source File: nasnet_test.py    From models with Apache License 2.0 5 votes vote down vote up 
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])
Example #5
Source File: nasnet_test.py    From models with Apache License 2.0 5 votes vote down vote up 
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)
Example #6
Source File: nasnet_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
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])
Example #7
Source File: nasnet_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
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)
Example #8
Source File: nasnet_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
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])
Example #9
Source File: nasnet_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
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)
Example #10
Source File: nasnet_test.py    From SENet-tensorflow-slim with MIT License 5 votes vote down vote up 
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])
Example #11
Source File: nasnet_test.py    From SENet-tensorflow-slim with MIT License 5 votes vote down vote up 
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)
Example #12
Source File: nasnet_test.py    From MAX-Image-Segmenter with Apache License 2.0 5 votes vote down vote up 
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])
Example #13
Source File: nasnet_test.py    From DeepLab_v3 with MIT License 5 votes vote down vote up 
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)
Example #14
Source File: nasnet_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
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])
Example #15
Source File: nasnet_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
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)
Example #16
Source File: nasnet_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
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])
Example #17
Source File: nasnet_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
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)
Example #18
Source File: nasnet_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up 
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])
Example #19
Source File: nasnet_test.py    From CBAM-tensorflow-slim with MIT License 5 votes vote down vote up 
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)
Example #20
Source File: nasnet_test.py    From edafa with MIT License 5 votes vote down vote up 
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])
Example #21
Source File: nasnet_test.py    From edafa with MIT License 5 votes vote down vote up 
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)
Example #22
Source File: nasnet_test.py    From CVTron with Apache License 2.0 5 votes vote down vote up 
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])
Example #23
Source File: nasnet_test.py    From CVTron with Apache License 2.0 5 votes vote down vote up 
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)
Example #24
Source File: nasnet_test.py    From DeepLab_v3 with MIT License 5 votes vote down vote up 
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])