guild.yml

# Copyright 2023 Álvaro Goldar Dieste

# 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.


preprocess_dataset:

    description: Reads and preprocesses a given dataset for classification
    main: preprocess_dataset
    flags-dest: args
    flags-import: all
    output-scalars: no
    requires:
        - file: datasets/
    sourcecode:
        - datasets_helper.cpp
        - datasets.py
        - preprocess_dataset.py


run_network:

    description: Trains a certain network on a given dataset and evaluates its performance
    main: run_network
    flags-dest: args
    flags-import: all
    flags-import-skip:
        - device
    output-scalars:
        - step: 'Training epoch: (\step)'
        - dis_avg-loss: 'Dis.+ loss \(average\): (\value)'
        - dis_real-loss: 'Dis.+ loss \(real images\): (\value)'
        - dis_fake-loss: 'Dis.+ loss \(fake images\): (\value)'
        - gen_loss: 'Gen.+ loss: (\value)'
        - standalone_loss: 'Mean loss: (\value)'
        - val_acc: 'Val.+ accuracy: (\value)'
        - oa: '\(OA\): (\value)'
        - aa: '\(AA\): (\value)'
        - kappa: 'Cohen.+ \(k\): (\value)'
    requires:
        - operation: preprocess_dataset
    sourcecode:
        - datasets_helper.cpp
        - datasets.py
        - networks.py
        - run_network.py


test_synthesis:

    description: Tests the synthesis performance of a pretrained GAN network on a given dataset
    main: test_synthesis
    flags-dest: args
    flags-import: all
    flags-import-skip:
        - activation
        - data_augmentation
        - dataset_path
        - device
        - epochs
        - latent_size
        - learning_rate
        - p_dropout
        - weight_init
    output-scalars:
        - fid: 'FID score: (\value)'
    requires:
        - file: CNN2D_Residual_model.pt
        - operation: run_network
    sourcecode:
        - datasets_helper.cpp
        - datasets.py
        - networks.py
        - test_synthesis.py