(x,
                 is_training,
                 weight_decay,
                 params=None,
                 moments=None,
                 reuse=tf.AUTO_REUSE,
                 scope='resnet18',
                 backprop_through_moments=True,
                 use_bounded_activation=False,
                 max_stride=None,
                 deeplab_alignment=True,
                 keep_spatial_dims=False,
                 film_selector=None)
return _resnet(
      x,
      is_training,
      weight_decay,
      scope,
      reuse=reuse,
      params=params,
      moments=moments,
      backprop_through_moments=backprop_through_moments,
      use_bounded_activation=use_bounded_activation,
      blocks=(2, 2, 2, 2),
      max_stride=max_stride,
      deeplab_alignment=deeplab_alignment,
      keep_spatial_dims=keep_spatial_dims,
      film_selector=film_selector)
ResNet18 embedding function for FLUTE.
ResNet18 embedding function for FLUTE.
ResNet18 embedding function for FLUTE .
def flute_resnet(x,
                 is_training,
                 weight_decay,
                 params=None,
                 moments=None,
                 reuse=tf.AUTO_REUSE,
                 scope='resnet18',
                 backprop_through_moments=True,
                 use_bounded_activation=False,
                 max_stride=None,
                 deeplab_alignment=True,
                 keep_spatial_dims=False,
                 film_selector=None):
  """ResNet18 embedding function for FLUTE."""
  return _resnet(
      x,
      is_training,
      weight_decay,
      scope,
      reuse=reuse,
      params=params,
      moments=moments,
      backprop_through_moments=backprop_through_moments,
      use_bounded_activation=use_bounded_activation,
      blocks=(2, 2, 2, 2),
      max_stride=max_stride,
      deeplab_alignment=deeplab_alignment,
      keep_spatial_dims=keep_spatial_dims,
      film_selector=film_selector)
def flute_resnet ( x , is_training , weight_decay , params = None , moments = None , reuse = tf . AUTO_REUSE , scope = 'resnet18' , backprop_through_moments = True , use_bounded_activation = False , max_stride = None , deeplab_alignment = True , keep_spatial_dims = False , film_selector = None ) : return _resnet ( x , is_training , weight_decay , scope , reuse = reuse , params = params , moments = moments , backprop_through_moments = backprop_through_moments , use_bounded_activation = use_bounded_activation , blocks = ( 2 , 2 , 2 , 2 ) , max_stride = max_stride , deeplab_alignment = deeplab_alignment , keep_spatial_dims = keep_spatial_dims , film_selector = film_selector )