class_docstr: ResNet model.
class_docstr_tok: ["ResNet","model","."]
code: def __init__(self, batch_size=None, name=None, **kwargs):
      NB_CLASSES = 10
      super(ResNetTF, self).__init__(
          nb_classes=NB_CLASSES, layers=[], input_shape=None
      )
      self.global_step = (
          tf.contrib.framework.get_or_create_global_step()
      )
      self.hps = HParams(
          batch_size=batch_size,
          nb_classes=NB_CLASSES,
          min_lrn_rate=0.0001,
          lrn_rate=0.1,
          num_residual_units=5,
          use_bottleneck=False,
          weight_decay_rate=0.0002,
          relu_leakiness=0.1,
          momentum=0.9,
      )
      self.layers = []
      self.layer_idx = 0
      self.init_layers = True
      self.decay_cost = None
      self.training = None
      self.device_name = None
  
imports: from collections import namedtuple
  import tensorflow
  import six
  from model import MLPnGPU
  from model import Conv2DnGPU
  from model import LinearnGPU
  from model import LayerNorm
label_desc: Use image node_id 1 to create a new ResNetTF object from inherited base classes: MLPnGPU with example: obj = ResNetTF(batch_size, name)