"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()