class_docstr: Simple Conv-1D classifier.
  This is a combination of the
  :class:`~texar.tf.modules.Conv1DEncoder` with a classification layer.
  
  Args:
      hparams (dict, optional): Hyperparameters. Missing
          hyperparamerter will be set to default values. See
          :meth:`default_hparams` for the hyperparameter sturcture and
          default values.
  
  Example:
  
      .. code-block:: python
  
          clas = Conv1DClassifier(hparams={'num_classes': 10})
  
          inputs = tf.random_uniform([64, 20, 256])
          logits, pred = clas(inputs)
          # logits == Tensor of shape [64, 10]
          # pred   == Tensor of shape [64]
  
  .. document private functions
  .. automethod:: _build
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docstr: Returns `True` if the network with the name exists. Returns `False`
  otherwise.
  
  Args:
      layer_name (str): Name of the layer.
docstr_tok: ["Returns","`","True","`","if","the","network","with","the","name","exists",".","Returns","`","False","`","otherwise",".","Args",":","layer_name","(","str",")",":","Name","of","the","layer","."]
code: def has_layer(self, layer_name):
      """Returns `True` if the network with the name exists. Returns `False`
      otherwise.
  
      Args:
          layer_name (str): Name of the layer.
      """
      return self._encoder.has_layer(layer_name)
  
imports: import tensorflow
  from texar.tf.utils.exceptions import TexarError
  from texar.tf.modules.classifiers.classifier_base import ClassifierBase
  from texar.tf.modules.encoders.conv_encoders import Conv1DEncoder
  from texar.tf.utils import utils
  from texar.tf.hyperparams import HParams
label_desc: Use image node_id 7 for calling the Conv1DClassifier obj's underlying member method code with example usage: obj.has_layer(layer_name) and returns: self