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from gyraudio.default_locations import MIXED_AUDIO_ROOT
from gyraudio.audio_separation.properties import (
TRAIN, TEST, VALID, NAME, EPOCHS, LEARNING_RATE,
OPTIMIZER, BATCH_SIZE, DATALOADER, AUGMENTATION,
SHORT_NAME, AUG_TRIM, TRIM_PROB, LENGTH_DIVIDER, LENGTHS, SNR_FILTER
)
from gyraudio.audio_separation.data.remixed_fixed import RemixedFixedAudioDataset
from gyraudio.audio_separation.data.remixed_rnd import RemixedRandomAudioDataset
from gyraudio.audio_separation.data import get_dataloader, get_config_dataloader
from gyraudio.audio_separation.experiment_tracking.experiments_definition import get_experiment_generator
import torch
from typing import Tuple
def get_experience(exp_major: int, exp_minor: int = 0, snr_filter_test=None, dry_run=False) -> Tuple[str, torch.nn.Module, dict, dict]:
"""Get all experience details
Args:
exp_major (int): Major experience number
exp_minor (int, optional): Used for HP search. Defaults to 0.
Returns:
Tuple[str, torch.nn.Module, dict, dict]: short_name, model, config, dataloaders
"""
model = None
config = {}
dataloader_name = "remix"
config = {
NAME: None,
OPTIMIZER: {
NAME: "adam",
LEARNING_RATE: 0.001
},
EPOCHS: 60,
DATALOADER: {
NAME: dataloader_name,
},
BATCH_SIZE: [16, 16, 16],
SNR_FILTER : snr_filter_test
}
model, config = get_experiment_generator(exp_major=exp_major)(config, no_model=dry_run, minor=exp_minor)
# POST PROCESSING
if isinstance(config[BATCH_SIZE], list) or isinstance(config[BATCH_SIZE], tuple):
config[BATCH_SIZE] = {
TRAIN: config[BATCH_SIZE][0],
TEST: config[BATCH_SIZE][1],
VALID: config[BATCH_SIZE][2],
}
if config[DATALOADER][NAME] == "premix":
mixed_audio_root = MIXED_AUDIO_ROOT
dataloaders = get_dataloader({
TRAIN: get_config_dataloader(
audio_root=mixed_audio_root,
mode=TRAIN,
shuffle=True,
batch_size=config[BATCH_SIZE][TRAIN],
augmentation=config[DATALOADER].get(AUGMENTATION, {})
),
TEST: get_config_dataloader(
audio_root=mixed_audio_root,
mode=TEST,
shuffle=False,
batch_size=config[BATCH_SIZE][TEST],
snr_filter=config[SNR_FILTER]
)
})
elif config[DATALOADER][NAME] == "remix":
mixed_audio_root = MIXED_AUDIO_ROOT
aug_test = {}
if AUG_TRIM in config[DATALOADER].get(AUGMENTATION, {}):
aug_test = {
AUG_TRIM: {LENGTHS: [None, None], LENGTH_DIVIDER: config[DATALOADER][AUGMENTATION]
[AUG_TRIM][LENGTH_DIVIDER], TRIM_PROB: -1.}
}
try:
dl_train = get_dataloader(
{
TRAIN: get_config_dataloader(
audio_root=mixed_audio_root,
mode=TRAIN,
shuffle=True,
batch_size=config[BATCH_SIZE][TRAIN],
augmentation=config[DATALOADER].get(AUGMENTATION, {})
)
},
audio_dataset=RemixedRandomAudioDataset
)[TRAIN]
dl_test = get_dataloader(
{
TEST: get_config_dataloader(
audio_root=mixed_audio_root,
mode=TEST,
shuffle=False,
batch_size=config[BATCH_SIZE][TEST]
)
},
audio_dataset=RemixedFixedAudioDataset
)[TEST]
except Exception as e:
dl_train = None
dl_test = None
pass
dataloaders = {
TRAIN: dl_train,
TEST: dl_test
}
else:
raise NotImplementedError(f"Unknown dataloader {dataloader_name}")
assert config[NAME] is not None
short_name = f"{exp_major:04d}_{exp_minor:04d}"
config[SHORT_NAME] = short_name
return short_name, model, config, dataloaders
if __name__ == "__main__":
from gyraudio.audio_separation.parser import shared_parser
parser_def = shared_parser()
args = parser_def.parse_args()
for exp in args.experiments:
short_name, model, config, dl = get_experience(exp)
print(short_name)
print(config)
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