class_docstr: A wrapper class for tf.keras.Sequential adding more functions for BigDL-Nano.
docstr: Create a nano Sequential model, having the same arguments with tf.keras.Sequential.
docstr_tok: ["Create","a","nano","Sequential","model",",","having","the","same","arguments","with","tf.keras.Sequential","."]
code: def __init__(self, *args, **kwargs):
      """Create a nano Sequential model, having the same arguments with tf.keras.Sequential."""
      super().__init__(*args, **kwargs)
  
file_path: BigDL/python/nano/src/bigdl/nano/tf/keras/Sequential.py
imports: import tensorflow
  from bigdl.nano.tf.keras.inference_utils import InferenceUtils
  from bigdl.nano.tf.keras.training_utils import TrainingUtils
label_desc: Use image node_id 1 to create a new Sequential object from inherited base classes: TrainingUtils, InferenceUtils, tf.keras with example: obj = Sequential()