ad_tf.py 文件源码

def input_fn(df):
    """Input builder function."""
    # Creates a dictionary mapping from each continuous feature column name (k) to
    # the values of that column stored in a constant Tensor.
    continuous_cols = {k: tf.constant(df[k].values) for k in CONTINUOUS_COLUMNS}
    # Creates a dictionary mapping from each categorical feature column name (k)
    # to the values of that column stored in a tf.SparseTensor.
    categorical_cols = {
        k: tf.SparseTensor(
                indices=[[i, 0] for i in range(df[k].size)],
                values=df[k].values,
                dense_shape=[df[k].size, 1])
        for k in CATEGORICAL_COLUMNS}
    # Merges the two dictionaries into one.
    feature_cols = dict(continuous_cols)
    feature_cols.update(categorical_cols)

    label = tf.constant(df[LABEL_COLUMN].values)

    # Returns the feature columns and the label.
    return feature_cols, label