Module delta.subcommands.commands

# Copyright © 2020, United States Government, as represented by the
# Administrator of the National Aeronautics and Space Administration.
# All rights reserved.
#
# The DELTA (Deep Earth Learning, Tools, and Analysis) platform is
# licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#        http://www.apache.org/licenses/LICENSE-2.0.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
Lists all avaiable commands.
"""
from delta.config import config

#pylint:disable=import-outside-toplevel

# we put this here because tensorflow takes so long to load, we don't do it unless we have to
def main_classify(options):
    from . import classify
    classify.main(options)

def main_train(options):
    from . import train
    train.main(options)

def main_mlflow_ui(options):
    from .import mlflow_ui
    mlflow_ui.main(options)

def main_validate(options):
    from .import validate
    validate.main(options)

def main_visualize(options):
    from .import visualize
    visualize.main(options)

def setup_classify(subparsers):
    sub = subparsers.add_parser('classify', help='Classify images given a model.')
    config.setup_arg_parser(sub, ['general', 'io', 'dataset', 'classify'])

    sub.add_argument('--autoencoder', dest='autoencoder', action='store_true', help='Classify with the autoencoder.')
    sub.add_argument('--no-colormap', dest='noColormap', action='store_true',
                     help='Save raw classification values instead of colormapped values.')
    sub.add_argument('--validation', dest='validation', help='Classify validation images instead.')
    sub.add_argument('--outdir', dest='outdir', type=str, help='Directory to save output to.')
    sub.add_argument('--basedir', dest='basedir', type=str, help='Preserve paths of files relative to this directory.')
    sub.add_argument('--outprefix', dest='outprefix', type=str, help='Prefix to output filenames.')
    sub.add_argument('--confusion', dest='confusion', action='store_true', help='Save confusion matrix.')
    sub.add_argument('--error', dest='error', action='store_true',
                     help='Save image of model errors. Values will be difference between predicted probability and '
                          'the binary labels.')
    sub.add_argument('--error-abs', dest='error_abs', action='store_true',
                     help='Save image of absolute value of model errors. Values will be the absolute value of the '
                          'difference between predicted probability and binary label. If both --error and --error-abs '
                          'are provided, --error-abs will take precidence.')
    sub.add_argument('model', help='File to save the network to.')

    sub.set_defaults(function=main_classify)

def setup_train(subparsers):
    sub = subparsers.add_parser('train', help='Train a task-specific classifier.')
    config.setup_arg_parser(sub)
    sub.add_argument('--autoencoder', action='store_true',
                     help='Train autoencoder (ignores labels).')
    sub.add_argument('--resume', help='Use the model as a starting point for the training.')
    sub.add_argument('model', nargs='?', default=None, help='File to save the network to.')
    sub.set_defaults(function=main_train)

def setup_mlflow_ui(subparsers):
    sub = subparsers.add_parser('mlflow_ui', help='Launch mlflow user interface to visualize run history.')
    config.setup_arg_parser(sub, ['mlflow'])

    sub.set_defaults(function=main_mlflow_ui)

def setup_validate(subparsers):
    sub = subparsers.add_parser('validate', help='Validate input dataset.')
    config.setup_arg_parser(sub, ['general', 'io', 'dataset', 'train'])

    sub.set_defaults(function=main_validate)

def setup_visualize(subparsers):
    sub = subparsers.add_parser('visualize', help='Visualize input dataset.')
    sub.add_argument('--autoencoder', dest='autoencoder', action='store_true', help='Visualize for the autoencoder.')
    config.setup_arg_parser(sub, ['general', 'io', 'dataset', 'train'])

    sub.set_defaults(function=main_visualize)

SETUP_COMMANDS = [setup_train, setup_classify, setup_mlflow_ui, setup_validate, setup_visualize]