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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import json
import os
from abc import abstractmethod
from pathlib import Path
import json5
import torch
import yaml
# TODO: for training and validating
class BaseDataset(torch.utils.data.Dataset):
r"""Base dataset for training and validating."""
def __init__(self, args, cfg, is_valid=False):
pass
class BaseTestDataset(torch.utils.data.Dataset):
r"""Test dataset for inference."""
def __init__(self, args=None, cfg=None, infer_type="from_dataset"):
assert infer_type in ["from_dataset", "from_file"]
self.args = args
self.cfg = cfg
self.infer_type = infer_type
@abstractmethod
def __getitem__(self, index):
pass
def __len__(self):
return len(self.metadata)
def get_metadata(self):
path = Path(self.args.source)
if path.suffix == ".json" or path.suffix == ".jsonc":
metadata = json5.load(open(self.args.source, "r"))
elif path.suffix == ".yaml" or path.suffix == ".yml":
metadata = yaml.full_load(open(self.args.source, "r"))
else:
raise ValueError(f"Unsupported file type: {path.suffix}")
return metadata
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