"model_args": {
"out_kernel_size": (132, 29)
},
# "composed_transform": transforms.Compose([
# transform_utils.Normalizer()
# ]),
"data_set_cls":
Task1bDataSet2019,
"test_fn":
None, # no use here
# "resume_model": os.getenv("HOME") + "/dcase/dev/ray_results/2019_diff_net_report/Trainable_0_batch_size=32,feature_folder=logmel_delta2_128_44k,lr=0.0001,mixup_alpha=0,mixup_concat_ori=False,network=resnet_mod,o_2020-10-07_23-14-22_109tcpy/checkpoint_111/model.pth",
},
name="2019_diff_net_report",
num_samples=1,
local_dir=os.getenv("HOME") + "/dcase/result/ray_results",
stop=TrainStopper(max_ep=200, stop_thres=200),
checkpoint_freq=1,
keep_checkpoints_num=1,
checkpoint_at_end=True,
checkpoint_score_attr="acc",
resources_per_trial={"gpu": 1},
)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-test', action='store_true') # default = false
args = parser.parse_args()
if args.test:
transforms.Compose([
# transform_utils.SelectChannel(0),
transform_utils.Normalizer()
]),
"data_set_cls":
Task1bDataSet2019,
"test_fn":
None, # no use here
"resume_model":
os.getenv("HOME") +
"/dcase/dev/ray_results/2019_diff_net_report/Trainable_0_batch_size=32,feature_folder=logmel_delta2_128_44k,lr=0.0001,mixup_alpha=0,mixup_concat_ori=False,network=vgg13_bn,opt_2020-09-28_11-57-24tndznmo5/checkpoint_170/model.pth",
},
name="2019_diff_net_report",
num_samples=1,
local_dir=os.getenv("HOME") + "/dcase/result/ray_results",
stop=TrainStopper(max_ep=30, stop_thres=30),
checkpoint_freq=1,
keep_checkpoints_num=1,
checkpoint_at_end=True,
checkpoint_score_attr="acc",
resources_per_trial={
"gpu": 0,
"cpu": 64
},
)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
# "mixup_concat_ori": False, # tune.grid_search([False]),
# "feature_folder": "logmel_40_44k", #tune.grid_search(["logmel_40_44k"]),
# "db_path": os.getenv("HOME") + "/dcase/datasets/TAU-urban-acoustic-scenes-2019-mobile-development",
# "model_cls": Baseline,
# "model_args": {
# "full_connected_in": 128
# },
# "data_set_cls": Task1bDataSet2019,
# "test_fn": None, # no use here
# # "resume_model": "/home/hw1-a07/dcase/dev/ray_results/2020_diff_net2/Trainable_0_batch_size=256,feature_folder=mono256dim_norm,lr=0.0001,mixup_alpha=0,mixup_concat_ori=False,network=cnn9avg_amsgrad,o_2020-06-13_11-08-08mq3s_xxl/best_model.pth",
# },
# name="2019_diff_net_report",
name="test_resume",
num_samples=10,
local_dir=os.getenv("HOME") + "/dcase/result/ray_results",
stop=TrainStopper(max_ep=10, stop_thres=10),
checkpoint_freq=1,
keep_checkpoints_num=2,
checkpoint_at_end=True,
checkpoint_score_attr="acc",
resources_per_trial={"gpu": 1},
)
hp_space = {
# "network": hp.choice("network", [
# {
# "type": "baseline",
# "full_connected_in": 128
# }
# ]),
"network": hp.choice("network", (["baseline"])),
"feature_folder":
tune.grid_search(["openl3-music-mel256-emb512-hop0_1"]),
"db_path":
"/home/hw1-a07/dcase/datasets/TAU-urban-acoustic-scenes-2019-mobile-development",
"model_cls": Baseline,
"model_args": {
"full_connected_in": 256
},
"data_set_cls": Task1bDataSet2019,
"test_fn": None, # no use here
# "resume_model": "/home/hw1-a07/dcase/dev/ray_results/2020_diff_net2/Trainable_0_batch_size=256,feature_folder=mono256dim_norm,lr=0.0001,mixup_alpha=0,mixup_concat_ori=False,network=cnn9avg_amsgrad,o_2020-06-13_11-08-08mq3s_xxl/best_model.pth",
},
name="2019_diff_net",
num_samples=1,
local_dir="/home/hw1-a07/dcase/result/ray_results",
stop=TrainStopper(max_ep=200),
checkpoint_freq=1,
keep_checkpoints_num=1,
checkpoint_at_end=True,
checkpoint_score_attr="acc",
resources_per_trial={
"gpu": 0,
"cpu": 64
},
)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-test', action='store_true') # default = false
"mixup_alpha": tune.grid_search([1]),
"mixup_concat_ori": tune.grid_search([True]),
"feature_folder": tune.grid_search(["logmel_40_44k", "logmel_128_44k"]),
"db_path": "/home/hw1-a07/dcase/datasets/TAU-urban-acoustic-scenes-2019-mobile-development",
"model_cls": Xception,
"model_args": {
"in_channel": 1,
},
"data_set_cls": Task1bDataSet2019,
"test_fn": None, # no use here
"resume_model": None,
},
name="2019_diff_net",
num_samples=1,
local_dir="/home/hw1-a07/dcase/result/ray_results",
stop=TrainStopper(),
checkpoint_freq=1,
keep_checkpoints_num=1,
checkpoint_at_end=True,
checkpoint_score_attr="acc",
resources_per_trial={"gpu": 0, "cpu": 64},
)
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-test', action='store_true') # default = false
args = parser.parse_args()
