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funit_animals.yaml
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funit_animals.yaml
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# Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
# Licensed under the CC BY-NC-SA 4.0 license
# (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
# logger options
image_save_iter: 2500 # How often do you want to save output images during training
image_display_iter: 100 # How often do you want to display output images during training
snapshot_save_iter: 5000 # How often do you want to save trained models
log_iter: 1 # How often do you want to log the training stats
# optimization options
max_iter: 100000 # maximum number of training iterations
weight_decay: 0.0001 # weight decay
lr_gen: 0.0001 # learning rate for the generator
lr_dis: 0.0001 # learning rate for the discriminator
init: kaiming # initialization [gaussian/kaiming/xavier/orthogonal]
gan_w: 1 # weight of adversarial loss for image translation
fm_w: 1 # weight on distance between gan features of style and translated image
r_w: 0.1 # weight of image reconstruction loss
# model options
gen:
nf: 64 # number of base filters in the generator
n_res_blks: 2 # number of residual blocks in content encoder/decoder
nf_mlp: 256 # number of base filters in MLP module
latent_dim: 64 # dimension of the latent code for the class model
n_mlp_blks: 3 # number of mlp blocks
n_downs_content: 3 # number of downsampling layers in content encoder
n_downs_class: 4 # number of downsampling layers in class model encoder
dis:
nf: 64 # base number of filters
n_res_blks: 10 # number of residual blocks in the discriminator
num_classes: 119 # number of classes in the training set
# data options
num_workers: 4
batch_size: 64
new_size: 140 # first resize the shortest image side to this size
crop_image_height: 128 # random crop image of this height
crop_image_width: 128 # random crop image of this width
data_folder_train: ./datasets/animals
data_list_train: ./datasets/animals_list_train.txt
data_folder_test: ./datasets/animals
data_list_test: ./datasets/animals_list_test.txt