docstr: Defines the TensorFlow model, loss, optimisation and accuracy. Then
  loads the weights into the model.
docstr_tok: ["Defines","the","TensorFlow","model",",","loss",",","optimisation","and","accuracy",".","Then","loads","the","weights","into","the","model","."]
code: def __init__(self, net_params, batch_size, num_classes):
      """
      Defines the TensorFlow model, loss, optimisation and accuracy. Then
      loads the weights into the model.
      """
      self.gpu_policy = _utils.TensorFlowGPUPolicy()
      self.gpu_policy.start()
  
      for key in net_params.keys():
          net_params[key] = _utils.convert_shared_float_array_to_numpy(
              net_params[key]
          )
  
      _tf = _lazy_import_tensorflow()
      self.dc_graph = _tf.Graph()
      self.num_classes = num_classes
      self.batch_size = batch_size
      self.sess = _tf.Session(graph=self.dc_graph)
      with self.dc_graph.as_default():
          self.init_drawing_classifier_graph(net_params)
  
file_path: turicreate/src/python/turicreate/toolkits/drawing_classifier/_tf_drawing_classifier.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from .._tf_model import TensorFlowModel
  import turicreate.toolkits._tf_utils
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 1 to create a new DrawingClassifierTensorFlowModel object from inherited base classes: TensorFlowModel with example: obj = DrawingClassifierTensorFlowModel(net_params, batch_size, num_classes)