xp_video_level_models.py 文件源码

def create_model(self, model_input, vocab_size, l2_penalty=1e-4, **unused_params):
    """Creates a logistic model.

    Args:
      model_input: 'batch' x 'num_features' matrix of input features.
      vocab_size: The number of classes in the dataset.

    Returns:
      A dictionary with a tensor containing the probability predictions of the
      model in the 'predictions' key. The dimensions of the tensor are
      batch_size x num_classes."""
    with tf.name_scope('MyNNModel0'):
        h1Units = 2400
        a1 = slim.fully_connected(
                model_input, h1Units, activation_fn=tf.nn.relu,
                weights_regularizer=slim.l2_regularizer(l2_penalty),
                scope='FC1')
        output = slim.fully_connected(
                a1, vocab_size, activation_fn=tf.nn.sigmoid,
                weights_regularizer=slim.l2_regularizer(l2_penalty),
                scope='FC2')
    return {"predictions": output}

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