[Bug] fugashi.Tagger causes pickling error during multiprocessing in tokenizer (Japanese)

[easyautoml]

Describe the bug

When fine-tuning the XTTS model with num_workers > 0 for Japanese dataset, a TypeError occurs related to fugashi.Tagger.

Specifically, the error self.c_tagger cannot be converted to a Python object for pickling is triggered because fugashi.Tagger, used in the cutlet library for Japanese text processing, cannot be serialized for multiprocessing.

To Reproduce

Steps to Reproduce:

• Load training and evaluation samples using load_tts_samples().
• Initialize the Trainer object.
• Create a training DataLoader using trainer.get_train_dataloader().
• Set num_workers=2 in the DataLoader to enable multiprocessing.
• Attempt to iterate through the DataLoader and observe the error.

train_samples, eval_samples = load_tts_samples(
    # Your loading code here...
)

# Initialize the trainer
trainer = Trainer(
    # Trainer initialization code here...
)

train_loader = trainer.get_train_dataloader(
    {},
    train_samples,
    True
)

dataset = train_loader.dataset

# Create DataLoader with num_workers > 0, which uses multiprocessing and may trigger the pickling issue
loader = DataLoader(
    dataset,
    batch_size=1,
    shuffle=False,
    collate_fn=dataset.collate_fn,
    drop_last=False,
    sampler=None,
    num_workers=2,  # Setting this to 2 will use multiple workers (multiprocessing)
    pin_memory=False,
)

# Create an iterator from the dataloader
data_iter = iter(loader)

# Try to fetch the first batch, this should trigger the pickling error
try:
    first_batch = next(data_iter)
    pd.DataFrame(list(first_batch.items()), columns=['Key', 'Value'])
except Exception as e:
    print(f"Error: {e}")

Expected behavior

The data should be processed without any errors, even with num_workers > 0.

Logs

No response

Environment

{
    "CUDA": {
        "GPU": [
            "NVIDIA GeForce RTX 3070 Laptop GPU"
        ],
        "available": true,
        "version": "12.1"
    },
    "Packages": {
        "PyTorch_debug": false,
        "PyTorch_version": "2.4.0+cu121",
        "TTS": "0.22.0",
        "numpy": "1.22.0"
    },
    "System": {
        "OS": "Windows",
        "architecture": [
            "64bit",
            "WindowsPE"
        ],
        "processor": "Intel64 Family 6 Model 165 Stepping 2, GenuineIntel",
        "python": "3.9.19",
        "version": "10.0.22631"
    }
}

Additional context

This issue only occurs when processing Japanese text, due to the use of fugashi.Tagger in the tokenization process, which is not compatible with multiprocessing.