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# mac generated | ||
.DS_Store | ||
*.DS_Store | ||
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# pycharm | ||
.idea |
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[DEFAULT] | ||
run_name = Run-test | ||
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[debug] | ||
debug_path = /Users/ryanqnelson/Desktop/test/ | ||
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[wandb] | ||
wandb_dir = /Users/ryanqnelson/Desktop/test | ||
entity = ryanquinnnelson | ||
project = CMU-02699-PROJECT | ||
notes = Image Segmentation using GANs | ||
tags = octopus,GAN,DAN | ||
mode = online | ||
config_sections_to_track=dataloader,model,hyperparameters | ||
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[output] | ||
output_dir = /Users/ryanqnelson/Desktop/test/output | ||
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[checkpoint] | ||
checkpoint_dir = /Users/ryanqnelson/Desktop/test/checkpoints | ||
checkpoint_cadence = 5 | ||
delete_existing_checkpoints = True | ||
load_from_checkpoint=False | ||
checkpoint_file = None | ||
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[data] | ||
data_dir = /Users/ryanqnelson/Desktop/test/data/warwick | ||
train_dir = /Users/ryanqnelson/Desktop/test/data/warwick/training | ||
train_target_dir = /Users/ryanqnelson/Desktop/test/data/warwick/training_anno | ||
val_dir = /Users/ryanqnelson/Desktop/test/data/warwick/a | ||
val_target_dir = /Users/ryanqnelson/Desktop/test/data/warwick/a_anno | ||
test_dir = /Users/ryanqnelson/Desktop/test/data/warwick/b | ||
test_target_dir = /Users/ryanqnelson/Desktop/test/data/warwick/b_anno | ||
transforms_list = Resize,ToTensor | ||
resize_height = 224 | ||
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########################################################################################## | ||
# Sweep parameters below this line # | ||
########################################################################################## | ||
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[dataloader] | ||
num_workers=8 | ||
pin_memory=True | ||
batch_size=10 | ||
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# TODO: avoid specifying original_width and original_height; calculate from resize_height | ||
[model] | ||
sn_model_type=ConcatenationFCN | ||
en_model_type=ENLite | ||
num_fcn_blocks=3 | ||
block_depth=1 | ||
input_channels=3 | ||
output_channels=2 | ||
first_layer_out_channels=64 | ||
block_pattern=single_run | ||
upsampling_pattern=last_three | ||
original_height=224 | ||
original_width=332 | ||
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[hyperparameters] | ||
num_epochs = 3 | ||
sn_criterion=CrossEntropyLoss | ||
en_criterion=BCELoss | ||
optimizer_type=adam | ||
lr=0.002 | ||
scheduler_type=ReduceLROnPlateau | ||
scheduler_factor=0.5 | ||
scheduler_patience=5 | ||
scheduler_mode=min | ||
scheduler_verbose=True | ||
scheduler_plateau_metric=val_loss | ||
scheduler_min_lr=0.00001 | ||
use_gan = False | ||
sigma=0.1 | ||
sigma_weight=300 | ||
gan_start_epoch=2 |
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[DEFAULT] | ||
run_name = GAN_Concat_Flex_014_0 | ||
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[debug] | ||
debug_path = /home/ubuntu | ||
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[wandb] | ||
wandb_dir = /home/ubuntu/wandb | ||
entity = ryanquinnnelson | ||
project = CMU-02699-PROJECT | ||
notes = Image Segmentation using GANs | ||
tags = octopus,GAN,DAN | ||
mode = online | ||
config_sections_to_track=dataloader,model,hyperparameters | ||
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[output] | ||
output_dir = /home/ubuntu/output | ||
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[checkpoint] | ||
checkpoint_dir = /data/checkpoints | ||
checkpoint_cadence = 20 | ||
delete_existing_checkpoints = False | ||
load_from_checkpoint=False | ||
checkpoint_file = None | ||
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[data] | ||
data_dir = /home/ubuntu/data/warwick | ||
train_dir = /home/ubuntu/data/warwick/training | ||
train_target_dir = /home/ubuntu/data/warwick/training_anno | ||
val_dir = /home/ubuntu/data/warwick/a | ||
val_target_dir = /home/ubuntu/data/warwick/a_anno | ||
test_dir = /home/ubuntu/data/warwick/b | ||
test_target_dir = /home/ubuntu/data/warwick/b_anno | ||
transforms_list = Resize,ToTensor | ||
resize_height = 224 | ||
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########################################################################################## | ||
# Sweep parameters below this line # | ||
########################################################################################## | ||
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[dataloader] | ||
num_workers=0 | ||
pin_memory=False | ||
batch_size=8 | ||
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# TODO: avoid specifying original_width and original_height; calculate from resize_height | ||
[model] | ||
sn_model_type=ConcatenationFCN | ||
sn_input_block_depth=1 | ||
sn_num_fcn_blocks=5 | ||
sn_fcn_block_depth=1 | ||
sn_input_channels=3 | ||
sn_output_channels=2 | ||
sn_first_layer_out_channels=64 | ||
sn_block_pattern=double_run | ||
sn_upsampling_pattern=last_three | ||
original_height=224 | ||
original_width=332 | ||
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en_model_type=FlexVGG | ||
en_input_block_depth=1 | ||
en_num_fcn_blocks=4 | ||
en_depth_fcn_block=2 | ||
en_input_channels=4 | ||
en_first_layer_out_channels=64 | ||
en_fcn_block_pattern=double_run | ||
en_depth_linear_block=1 | ||
en_linear_block_pattern=single_run | ||
en_first_linear_layer_out_features=128 | ||
en_out_features=1 | ||
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[hyperparameters] | ||
num_epochs = 300 | ||
sn_criterion=CrossEntropyLoss | ||
en_criterion=BCELoss | ||
optimizer_type=adam | ||
sn_lr=0.001 | ||
en_lr=0.0001 | ||
scheduler_type=ReduceLROnPlateau | ||
scheduler_factor=0.8 | ||
scheduler_patience=10 | ||
scheduler_mode=min | ||
scheduler_verbose=True | ||
scheduler_plateau_metric=val_loss | ||
scheduler_min_lr=0.00001 | ||
use_gan = True | ||
sigma=0.1 | ||
sigma_weight=300 | ||
gan_start_epoch=1 |
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