model.py 文件源码

def parse_csv(rows_string_tensor):
  """Takes the string input tensor and returns a dict of rank-2 tensors."""

  # Takes a rank-1 tensor and converts it into rank-2 tensor
  # Example if the data is ['csv,line,1', 'csv,line,2', ..] to
  # [['csv,line,1'], ['csv,line,2']] which after parsing will result in a
  # tuple of tensors: [['csv'], ['csv']], [['line'], ['line']], [[1], [2]]
  columns = tf.decode_csv(
      rows_string_tensor, record_defaults=CSV_COLUMN_DEFAULTS)
  features = dict(zip(CSV_COLUMNS, columns))

  # Remove unused columns
  for col in UNUSED_COLUMNS:
    features.pop(col)
  return features