Tensorflow Feature Columns: AttributeError: 'tuple' object has no attribute 'name'

Question

I'm attempting to train a simple dataset using 8 feature columns, 3 numeric, and 5 categorical. My basic training script currently looks like so:

import tensorflow as tf

feature_names = [
    'col1', 'col2', 'col3', 'col4', 'col5', 'col6',
    'col7', 'col8'
]


def input_fn(file_path, perform_shuffle=False, repeat_count=1):
    """
    """

    def decode_csv(line):
        """
        """
        parsed_line = tf.decode_csv(line, [[0], [0], [0], [''],[''],[''],[''],[''], [0]], na_value='?')

        label = parsed_line[-1:] # Last element is the label
        del parsed_line[-1] # Delete last element
        features = parsed_line
        d = dict(zip(feature_names, features)), label

        return d

    # Read in our file, skip the header row, and transform each element
    dataset = (tf.data.TextLineDataset(file_path)
       .skip(1)
       .map(decode_csv)) 

    # Randomizes input using a window of 256 elements (read into memory)
    if perform_shuffle:
        dataset = dataset.shuffle(buffer_size=256)

    dataset = dataset.repeat(repeat_count) # Repeats dataset this # times
    dataset = dataset.batch(32)  # Batch size to use

    iterator = dataset.make_one_shot_iterator()
    batch_features, batch_labels = iterator.get_next()

    return batch_features, batch_labels

I then build my feature columns:

col4 = tf.feature_column.categorical_column_with_identity(key='col4', num_buckets=3), 
col5 = tf.feature_column.categorical_column_with_identity(key='col5', num_buckets=3), 
col6 = tf.feature_column.categorical_column_with_identity(key='col6', num_buckets=2), 
col7 = tf.feature_column.categorical_column_with_identity(key='col7', num_buckets=2), 
col8 = tf.feature_column.categorical_column_with_identity(key='col8', num_buckets=2)    

feature_columns = [
    tf.feature_column.numeric_column(key='col1'), 
    tf.feature_column.numeric_column(key='col2'), 
    tf.feature_column.numeric_column(key='col3'), 
    tf.feature_column.indicator_column(col4),
    tf.feature_column.indicator_column(col5),
    tf.feature_column.indicator_column(col6),
    tf.feature_column.indicator_column(col7),
    tf.feature_column.indicator_column(col8)
]

classifier = tf.estimator.DNNClassifier(
    feature_columns=feature_columns,
    hidden_units=[10,10],
    n_classes=14,
    model_dir="data"
)

classifier.train(input_fn=lambda: input_fn("data/development.csv", True, 8))

However, I'm getting a very bland error message of:

AttributeError: 'tuple' object has no attribute 'name'

The stack trace indicates the indicator columns that the categorical columns wrap need a name. But I'm not sure why this would be the case, and all of the documentation and tutorials on using feature columns make no reference to any name argument being needed, as far as I can see.

Answer 1

Im sure you figured it out yourself by now, but for anyone who has the same error and probably just copied it out from the list with the comma at the end.

The trailing comma makes 'col4' a tuple

col4 = tf.feature_column.categorical_column_with_identity(key='col4', num_buckets=3),