Add changes for uroman package to handle non-Roman characters (#32404)

* Add changes for uroman package to handle non-Roman characters

* Update docs for uroman changes

* Modifying error message to warning, for backward compatibility

* Update instruction for user to install uroman

* Update docs for uroman python version dependency and backward compatibility

* Update warning message for python version compatibility with uroman

* Refine docs

docs/source/en/model_doc/vits.md

@@ -93,12 +93,33 @@ from transformers import VitsTokenizer
 tokenizer = VitsTokenizer.from_pretrained("facebook/mms-tts-eng")
 print(tokenizer.is_uroman)
 ```
+If the is_uroman attribute is `True`, the tokenizer will automatically apply the `uroman` package to your text inputs, but you need to install uroman if not already installed using:  
+```
+pip install --upgrade uroman
+```
+Note: Python version required to use `uroman` as python package should be >= `3.10`. 
+You can use the tokenizer as usual without any additional preprocessing steps:
+```python
+import torch
+from transformers import VitsTokenizer, VitsModel, set_seed
+import os
+import subprocess
 
-If required, you should apply the uroman package to your text inputs **prior** to passing them to the `VitsTokenizer`, 
-since currently the tokenizer does not support performing the pre-processing itself.  
+tokenizer = VitsTokenizer.from_pretrained("facebook/mms-tts-kor")
+model = VitsModel.from_pretrained("facebook/mms-tts-kor")
+text = "이봐 무슨 일이야"
+inputs = tokenizer(text=text, return_tensors="pt")
 
+set_seed(555)  # make deterministic
+with torch.no_grad():
+   outputs = model(inputs["input_ids"])
+
+waveform = outputs.waveform[0]
+```
+If you don't want to upgrade to python >= `3.10`, then you can use the `uroman` perl package to pre-process the text inputs to the Roman alphabet.
 To do this, first clone the uroman repository to your local machine and set the bash variable `UROMAN` to the local path:
 
+
 ```bash
 git clone https://github.com/isi-nlp/uroman.git
 cd uroman

src/transformers/models/vits/tokenization_vits.py

@@ -20,12 +20,14 @@ import re
 from typing import Any, Dict, List, Optional, Tuple, Union
 
 from ...tokenization_utils import PreTrainedTokenizer
-from ...utils import is_phonemizer_available, logging
+from ...utils import is_phonemizer_available, is_uroman_available, logging
 
 
 if is_phonemizer_available():
     import phonemizer
 
+if is_uroman_available():
+    import uroman as ur
 
 logger = logging.get_logger(__name__)
 
@@ -172,11 +174,16 @@ class VitsTokenizer(PreTrainedTokenizer):
         filtered_text = self._preprocess_char(text)
 
         if has_non_roman_characters(filtered_text) and self.is_uroman:
-            logger.warning(
-                "Text to the tokenizer contains non-Roman characters. Ensure the `uroman` Romanizer is "
-                "applied to the text prior to passing it to the tokenizer. See "
-                "`https://github.com/isi-nlp/uroman` for details."
-            )
+            if not is_uroman_available():
+                logger.warning(
+                    "Text to the tokenizer contains non-Roman characters. To apply the `uroman` pre-processing "
+                    "step automatically, ensure the `uroman` Romanizer is installed with: `pip install uroman` "
+                    "Note `uroman` requires python version >= 3.10"
+                    "Otherwise, apply the Romanizer manually as per the instructions: https://github.com/isi-nlp/uroman"
+                )
+            else:
+                uroman = ur.Uroman()
+                filtered_text = uroman.romanize_string(filtered_text)
 
         if self.phonemize:
             if not is_phonemizer_available():

src/transformers/utils/__init__.py

@@ -218,6 +218,7 @@ from .import_utils import (
     is_torchdynamo_compiling,
     is_torchvision_available,
     is_training_run_on_sagemaker,
+    is_uroman_available,
     is_vision_available,
     requires_backends,
     torch_only_method,

src/transformers/utils/import_utils.py

@@ -142,6 +142,7 @@ _quanto_available = _is_package_available("quanto")
 _pandas_available = _is_package_available("pandas")
 _peft_available = _is_package_available("peft")
 _phonemizer_available = _is_package_available("phonemizer")
+_uroman_available = _is_package_available("uroman")
 _psutil_available = _is_package_available("psutil")
 _py3nvml_available = _is_package_available("py3nvml")
 _pyctcdecode_available = _is_package_available("pyctcdecode")
@@ -1107,6 +1108,10 @@ def is_phonemizer_available():
     return _phonemizer_available
 
 
+def is_uroman_available():
+    return _uroman_available
+
+
 def torch_only_method(fn):
     def wrapper(*args, **kwargs):
         if not _torch_available:
@@ -1383,6 +1388,11 @@ PHONEMIZER_IMPORT_ERROR = """
 {0} requires the phonemizer library but it was not found in your environment. You can install it with pip:
 `pip install phonemizer`. Please note that you may need to restart your runtime after installation.
 """
+# docstyle-ignore
+UROMAN_IMPORT_ERROR = """
+{0} requires the uroman library but it was not found in your environment. You can install it with pip:
+`pip install uroman`. Please note that you may need to restart your runtime after installation.
+"""
 
 
 # docstyle-ignore
@@ -1523,6 +1533,7 @@ BACKENDS_MAPPING = OrderedDict(
         ("g2p_en", (is_g2p_en_available, G2P_EN_IMPORT_ERROR)),
         ("pandas", (is_pandas_available, PANDAS_IMPORT_ERROR)),
         ("phonemizer", (is_phonemizer_available, PHONEMIZER_IMPORT_ERROR)),
+        ("uroman", (is_uroman_available, UROMAN_IMPORT_ERROR)),
         ("pretty_midi", (is_pretty_midi_available, PRETTY_MIDI_IMPORT_ERROR)),
         ("levenshtein", (is_levenshtein_available, LEVENSHTEIN_IMPORT_ERROR)),
         ("librosa", (is_librosa_available, LIBROSA_IMPORT_ERROR)),