make feature list with list comprehension

test_1_works.py

INPUT_COLUMNS = [
  
  # Define features
  tf.feature_column.categorical_column_with_vocabulary_list('dayofweek', vocabulary_list = ['Sun', 'Mon', 'Tues', 'Wed', 'Thu', 'Fri', 'Sat']),
  tf.feature_column.categorical_column_with_identity('hourofday', num_buckets = 24),

]

test_2_works.py

INPUT_COLUMNS = [
  
  # Numeric Columns
  tf.feature_column.numeric_column(column) for column in CSV_COLUMNS[2:]
]

test_3_fails.py

INPUT_COLUMNS = [
  
  # Define features
  tf.feature_column.categorical_column_with_vocabulary_list('dayofweek', vocabulary_list = ['Sun', 'Mon', 'Tues', 'Wed', 'Thu', 'Fri', 'Sat']),
  tf.feature_column.categorical_column_with_identity('hourofday', num_buckets = 24),

  # Numeric Columns
  tf.feature_column.numeric_column(column) for column in CSV_COLUMNS[2:]
]

test_4_fails.py

INPUT_COLUMNS = [
  
  # Use a list comprehension and concatenation
  
  # Define features
  [
    tf.feature_column.categorical_column_with_vocabulary_list('dayofweek', vocabulary_list = ['Sun', 'Mon', 'Tues', 'Wed', 'Thu', 'Fri', 'Sat']),
    tf.feature_column.categorical_column_with_identity('hourofday', num_buckets = 24)
  ] + 

  # Numeric Columns
  tf.feature_column.numeric_column(column) for column in CSV_COLUMNS[2:]
]

test_5_works.py

INPUT_COLUMNS_1 = [
  
  # Define features
  tf.feature_column.categorical_column_with_vocabulary_list('dayofweek', vocabulary_list = ['Sun', 'Mon', 'Tues', 'Wed', 'Thu', 'Fri', 'Sat']),
  tf.feature_column.categorical_column_with_identity('hourofday', num_buckets = 24)

]

INPUT_COLUMNS_2 = [
  
  # Numeric Columns
  tf.feature_column.numeric_column(column) for column in CSV_COLUMNS[2:]
]

INPUT_COLUMNS = INPUT_COLUMNS_1 + INPUT_COLUMNS_2