(inputs,
                  num_classes=None,
                  is_training=True,
                  global_pool=True,
                  output_stride=None,
                  reuse=None,
                  scope='resnet_v1_152')
return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope)
ResNet-152 model of [1]. See resnet_v1() for arg and return description.
ResNet-152 model of [1]. See resnet_v1() for arg and return description.
ResNet - 152 model of [ 1 ] . See resnet_v1 () for arg and return description .
def resnet_v1_152(inputs,
                  num_classes=None,
                  is_training=True,
                  global_pool=True,
                  output_stride=None,
                  reuse=None,
                  scope='resnet_v1_152'):
  """ResNet-152 model of [1]. See resnet_v1() for arg and return description."""
  blocks = [
      resnet_utils.Block(
          'block1', bottleneck, [(256, 64, 1)] * 2 + [(256, 64, 2)]),
      resnet_utils.Block(
          'block2', bottleneck, [(512, 128, 1)] * 7 + [(512, 128, 2)]),
      resnet_utils.Block(
          'block3', bottleneck, [(1024, 256, 1)] * 35 + [(1024, 256, 2)]),
      resnet_utils.Block(
          'block4', bottleneck, [(2048, 512, 1)] * 3)]
  return resnet_v1(inputs, blocks, num_classes, is_training,
                   global_pool=global_pool, output_stride=output_stride,
                   include_root_block=True, reuse=reuse, scope=scope)
def resnet_v1_152 ( inputs , num_classes = None , is_training = True , global_pool = True , output_stride = None , reuse = None , scope = 'resnet_v1_152' ) : blocks = [ resnet_utils . Block ( 'block1' , bottleneck , [ ( 256 , 64 , 1 ) ] * 2 + [ ( 256 , 64 , 2 ) ] ) , resnet_utils . Block ( 'block2' , bottleneck , [ ( 512 , 128 , 1 ) ] * 7 + [ ( 512 , 128 , 2 ) ] ) , resnet_utils . Block ( 'block3' , bottleneck , [ ( 1024 , 256 , 1 ) ] * 35 + [ ( 1024 , 256 , 2 ) ] ) , resnet_utils . Block ( 'block4' , bottleneck , [ ( 2048 , 512 , 1 ) ] * 3 ) ] return resnet_v1 ( inputs , blocks , num_classes , is_training , global_pool = global_pool , output_stride = output_stride , include_root_block = True , reuse = reuse , scope = scope )